Parallel workflow manager for non-parallel bioinformatic applications to solve large-scale biological problems on a supercomputer.

PubMed

Suplatov, Dmitry; Popova, Nina; Zhumatiy, Sergey; Voevodin, Vladimir; Švedas, Vytas

2016-04-01

Rapid expansion of online resources providing access to genomic, structural, and functional information associated with biological macromolecules opens an opportunity to gain a deeper understanding of the mechanisms of biological processes due to systematic analysis of large datasets. This, however, requires novel strategies to optimally utilize computer processing power. Some methods in bioinformatics and molecular modeling require extensive computational resources. Other algorithms have fast implementations which take at most several hours to analyze a common input on a modern desktop station, however, due to multiple invocations for a large number of subtasks the full task requires a significant computing power. Therefore, an efficient computational solution to large-scale biological problems requires both a wise parallel implementation of resource-hungry methods as well as a smart workflow to manage multiple invocations of relatively fast algorithms. In this work, a new computer software mpiWrapper has been developed to accommodate non-parallel implementations of scientific algorithms within the parallel supercomputing environment. The Message Passing Interface has been implemented to exchange information between nodes. Two specialized threads - one for task management and communication, and another for subtask execution - are invoked on each processing unit to avoid deadlock while using blocking calls to MPI. The mpiWrapper can be used to launch all conventional Linux applications without the need to modify their original source codes and supports resubmission of subtasks on node failure. We show that this approach can be used to process huge amounts of biological data efficiently by running non-parallel programs in parallel mode on a supercomputer. The C++ source code and documentation are available from http://biokinet.belozersky.msu.ru/mpiWrapper .

Portable parallel portfolio optimization in the Aurora Financial Management System

NASA Astrophysics Data System (ADS)

Laure, Erwin; Moritsch, Hans

2001-07-01

Financial planning problems are formulated as large scale, stochastic, multiperiod, tree structured optimization problems. An efficient technique for solving this kind of problems is the nested Benders decomposition method. In this paper we present a parallel, portable, asynchronous implementation of this technique. To achieve our portability goals we elected the programming language Java for our implementation and used a high level Java based framework, called OpusJava, for expressing the parallelism potential as well as synchronization constraints. Our implementation is embedded within a modular decision support tool for portfolio and asset liability management, the Aurora Financial Management System.

Development and Applications of a Modular Parallel Process for Large Scale Fluid/Structures Problems

NASA Technical Reports Server (NTRS)

Guruswamy, Guru P.; Kwak, Dochan (Technical Monitor)

2002-01-01

A modular process that can efficiently solve large scale multidisciplinary problems using massively parallel supercomputers is presented. The process integrates disciplines with diverse physical characteristics by retaining the efficiency of individual disciplines. Computational domain independence of individual disciplines is maintained using a meta programming approach. The process integrates disciplines without affecting the combined performance. Results are demonstrated for large scale aerospace problems on several supercomputers. The super scalability and portability of the approach is demonstrated on several parallel computers.

Development and Applications of a Modular Parallel Process for Large Scale Fluid/Structures Problems

NASA Technical Reports Server (NTRS)

Guruswamy, Guru P.; Byun, Chansup; Kwak, Dochan (Technical Monitor)

2001-01-01

A modular process that can efficiently solve large scale multidisciplinary problems using massively parallel super computers is presented. The process integrates disciplines with diverse physical characteristics by retaining the efficiency of individual disciplines. Computational domain independence of individual disciplines is maintained using a meta programming approach. The process integrates disciplines without affecting the combined performance. Results are demonstrated for large scale aerospace problems on several supercomputers. The super scalability and portability of the approach is demonstrated on several parallel computers.

Implementation of Shifted Periodic Boundary Conditions in the Large-Scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) Software

DTIC Science & Technology

2015-08-01

Atomic/Molecular Massively Parallel Simulator ( LAMMPS ) Software by N Scott Weingarten and James P Larentzos Approved for...Massively Parallel Simulator ( LAMMPS ) Software by N Scott Weingarten Weapons and Materials Research Directorate, ARL James P Larentzos Engility...Shifted Periodic Boundary Conditions in the Large-Scale Atomic/Molecular Massively Parallel Simulator ( LAMMPS ) Software 5a. CONTRACT NUMBER 5b

Resource Management for Distributed Parallel Systems

NASA Technical Reports Server (NTRS)

Neuman, B. Clifford; Rao, Santosh

1993-01-01

Multiprocessor systems should exist in the the larger context of distributed systems, allowing multiprocessor resources to be shared by those that need them. Unfortunately, typical multiprocessor resource management techniques do not scale to large networks. The Prospero Resource Manager (PRM) is a scalable resource allocation system that supports the allocation of processing resources in large networks and multiprocessor systems. To manage resources in such distributed parallel systems, PRM employs three types of managers: system managers, job managers, and node managers. There exist multiple independent instances of each type of manager, reducing bottlenecks. The complexity of each manager is further reduced because each is designed to utilize information at an appropriate level of abstraction.

Large-scale three-dimensional phase-field simulations for phase coarsening at ultrahigh volume fraction on high-performance architectures

NASA Astrophysics Data System (ADS)

Yan, Hui; Wang, K. G.; Jones, Jim E.

2016-06-01

A parallel algorithm for large-scale three-dimensional phase-field simulations of phase coarsening is developed and implemented on high-performance architectures. From the large-scale simulations, a new kinetics in phase coarsening in the region of ultrahigh volume fraction is found. The parallel implementation is capable of harnessing the greater computer power available from high-performance architectures. The parallelized code enables increase in three-dimensional simulation system size up to a 5123 grid cube. Through the parallelized code, practical runtime can be achieved for three-dimensional large-scale simulations, and the statistical significance of the results from these high resolution parallel simulations are greatly improved over those obtainable from serial simulations. A detailed performance analysis on speed-up and scalability is presented, showing good scalability which improves with increasing problem size. In addition, a model for prediction of runtime is developed, which shows a good agreement with actual run time from numerical tests.

Demonstration of Hadoop-GIS: A Spatial Data Warehousing System Over MapReduce.

PubMed

Aji, Ablimit; Sun, Xiling; Vo, Hoang; Liu, Qioaling; Lee, Rubao; Zhang, Xiaodong; Saltz, Joel; Wang, Fusheng

2013-11-01

The proliferation of GPS-enabled devices, and the rapid improvement of scientific instruments have resulted in massive amounts of spatial data in the last decade. Support of high performance spatial queries on large volumes data has become increasingly important in numerous fields, which requires a scalable and efficient spatial data warehousing solution as existing approaches exhibit scalability limitations and efficiency bottlenecks for large scale spatial applications. In this demonstration, we present Hadoop-GIS - a scalable and high performance spatial query system over MapReduce. Hadoop-GIS provides an efficient spatial query engine to process spatial queries, data and space based partitioning, and query pipelines that parallelize queries implicitly on MapReduce. Hadoop-GIS also provides an expressive, SQL-like spatial query language for workload specification. We will demonstrate how spatial queries are expressed in spatially extended SQL queries, and submitted through a command line/web interface for execution. Parallel to our system demonstration, we explain the system architecture and details on how queries are translated to MapReduce operators, optimized, and executed on Hadoop. In addition, we will showcase how the system can be used to support two representative real world use cases: large scale pathology analytical imaging, and geo-spatial data warehousing.

A parallel orbital-updating based plane-wave basis method for electronic structure calculations

NASA Astrophysics Data System (ADS)

Pan, Yan; Dai, Xiaoying; de Gironcoli, Stefano; Gong, Xin-Gao; Rignanese, Gian-Marco; Zhou, Aihui

2017-11-01

Motivated by the recently proposed parallel orbital-updating approach in real space method [1], we propose a parallel orbital-updating based plane-wave basis method for electronic structure calculations, for solving the corresponding eigenvalue problems. In addition, we propose two new modified parallel orbital-updating methods. Compared to the traditional plane-wave methods, our methods allow for two-level parallelization, which is particularly interesting for large scale parallelization. Numerical experiments show that these new methods are more reliable and efficient for large scale calculations on modern supercomputers.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rubel, Oliver; Loring, Burlen; Vay, Jean -Luc

The generation of short pulses of ion beams through the interaction of an intense laser with a plasma sheath offers the possibility of compact and cheaper ion sources for many applications--from fast ignition and radiography of dense targets to hadron therapy and injection into conventional accelerators. To enable the efficient analysis of large-scale, high-fidelity particle accelerator simulations using the Warp simulation suite, the authors introduce the Warp In situ Visualization Toolkit (WarpIV). WarpIV integrates state-of-the-art in situ visualization and analysis using VisIt with Warp, supports management and control of complex in situ visualization and analysis workflows, and implements integrated analyticsmore » to facilitate query- and feature-based data analytics and efficient large-scale data analysis. WarpIV enables for the first time distributed parallel, in situ visualization of the full simulation data using high-performance compute resources as the data is being generated by Warp. The authors describe the application of WarpIV to study and compare large 2D and 3D ion accelerator simulations, demonstrating significant differences in the acceleration process in 2D and 3D simulations. WarpIV is available to the public via https://bitbucket.org/berkeleylab/warpiv. The Warp In situ Visualization Toolkit (WarpIV) supports large-scale, parallel, in situ visualization and analysis and facilitates query- and feature-based analytics, enabling for the first time high-performance analysis of large-scale, high-fidelity particle accelerator simulations while the data is being generated by the Warp simulation suite. Furthermore, this supplemental material https://extras.computer.org/extra/mcg2016030022s1.pdf provides more details regarding the memory profiling and optimization and the Yee grid recentering optimization results discussed in the main article.« less

WarpIV: In situ visualization and analysis of ion accelerator simulations

DOE PAGES

Rubel, Oliver; Loring, Burlen; Vay, Jean -Luc; ...

2016-05-09

The generation of short pulses of ion beams through the interaction of an intense laser with a plasma sheath offers the possibility of compact and cheaper ion sources for many applications--from fast ignition and radiography of dense targets to hadron therapy and injection into conventional accelerators. To enable the efficient analysis of large-scale, high-fidelity particle accelerator simulations using the Warp simulation suite, the authors introduce the Warp In situ Visualization Toolkit (WarpIV). WarpIV integrates state-of-the-art in situ visualization and analysis using VisIt with Warp, supports management and control of complex in situ visualization and analysis workflows, and implements integrated analyticsmore » to facilitate query- and feature-based data analytics and efficient large-scale data analysis. WarpIV enables for the first time distributed parallel, in situ visualization of the full simulation data using high-performance compute resources as the data is being generated by Warp. The authors describe the application of WarpIV to study and compare large 2D and 3D ion accelerator simulations, demonstrating significant differences in the acceleration process in 2D and 3D simulations. WarpIV is available to the public via https://bitbucket.org/berkeleylab/warpiv. The Warp In situ Visualization Toolkit (WarpIV) supports large-scale, parallel, in situ visualization and analysis and facilitates query- and feature-based analytics, enabling for the first time high-performance analysis of large-scale, high-fidelity particle accelerator simulations while the data is being generated by the Warp simulation suite. Furthermore, this supplemental material https://extras.computer.org/extra/mcg2016030022s1.pdf provides more details regarding the memory profiling and optimization and the Yee grid recentering optimization results discussed in the main article.« less

Parallel computing for probabilistic fatigue analysis

NASA Technical Reports Server (NTRS)

Sues, Robert H.; Lua, Yuan J.; Smith, Mark D.

1993-01-01

This paper presents the results of Phase I research to investigate the most effective parallel processing software strategies and hardware configurations for probabilistic structural analysis. We investigate the efficiency of both shared and distributed-memory architectures via a probabilistic fatigue life analysis problem. We also present a parallel programming approach, the virtual shared-memory paradigm, that is applicable across both types of hardware. Using this approach, problems can be solved on a variety of parallel configurations, including networks of single or multiprocessor workstations. We conclude that it is possible to effectively parallelize probabilistic fatigue analysis codes; however, special strategies will be needed to achieve large-scale parallelism to keep large number of processors busy and to treat problems with the large memory requirements encountered in practice. We also conclude that distributed-memory architecture is preferable to shared-memory for achieving large scale parallelism; however, in the future, the currently emerging hybrid-memory architectures will likely be optimal.

Computer Science Techniques Applied to Parallel Atomistic Simulation

NASA Astrophysics Data System (ADS)

Nakano, Aiichiro

1998-03-01

Recent developments in parallel processing technology and multiresolution numerical algorithms have established large-scale molecular dynamics (MD) simulations as a new research mode for studying materials phenomena such as fracture. However, this requires large system sizes and long simulated times. We have developed: i) Space-time multiresolution schemes; ii) fuzzy-clustering approach to hierarchical dynamics; iii) wavelet-based adaptive curvilinear-coordinate load balancing; iv) multilevel preconditioned conjugate gradient method; and v) spacefilling-curve-based data compression for parallel I/O. Using these techniques, million-atom parallel MD simulations are performed for the oxidation dynamics of nanocrystalline Al. The simulations take into account the effect of dynamic charge transfer between Al and O using the electronegativity equalization scheme. The resulting long-range Coulomb interaction is calculated efficiently with the fast multipole method. Results for temperature and charge distributions, residual stresses, bond lengths and bond angles, and diffusivities of Al and O will be presented. The oxidation of nanocrystalline Al is elucidated through immersive visualization in virtual environments. A unique dual-degree education program at Louisiana State University will also be discussed in which students can obtain a Ph.D. in Physics & Astronomy and a M.S. from the Department of Computer Science in five years. This program fosters interdisciplinary research activities for interfacing High Performance Computing and Communications with large-scale atomistic simulations of advanced materials. This work was supported by NSF (CAREER Program), ARO, PRF, and Louisiana LEQSF.

Xyce parallel electronic simulator : users' guide.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mei, Ting; Rankin, Eric Lamont; Thornquist, Heidi K.

2011-05-01

This manual describes the use of the Xyce Parallel Electronic Simulator. Xyce has been designed as a SPICE-compatible, high-performance analog circuit simulator, and has been written to support the simulation needs of the Sandia National Laboratories electrical designers. This development has focused on improving capability over the current state-of-the-art in the following areas: (1) Capability to solve extremely large circuit problems by supporting large-scale parallel computing platforms (up to thousands of processors). Note that this includes support for most popular parallel and serial computers; (2) Improved performance for all numerical kernels (e.g., time integrator, nonlinear and linear solvers) through state-of-the-artmore » algorithms and novel techniques. (3) Device models which are specifically tailored to meet Sandia's needs, including some radiation-aware devices (for Sandia users only); and (4) Object-oriented code design and implementation using modern coding practices that ensure that the Xyce Parallel Electronic Simulator will be maintainable and extensible far into the future. Xyce is a parallel code in the most general sense of the phrase - a message passing parallel implementation - which allows it to run efficiently on the widest possible number of computing platforms. These include serial, shared-memory and distributed-memory parallel as well as heterogeneous platforms. Careful attention has been paid to the specific nature of circuit-simulation problems to ensure that optimal parallel efficiency is achieved as the number of processors grows. The development of Xyce provides a platform for computational research and development aimed specifically at the needs of the Laboratory. With Xyce, Sandia has an 'in-house' capability with which both new electrical (e.g., device model development) and algorithmic (e.g., faster time-integration methods, parallel solver algorithms) research and development can be performed. As a result, Xyce is a unique electrical simulation capability, designed to meet the unique needs of the laboratory.« less

Symposium on Parallel Computational Methods for Large-scale Structural Analysis and Design, 2nd, Norfolk, VA, US

NASA Technical Reports Server (NTRS)

Storaasli, Olaf O. (Editor); Housner, Jerrold M. (Editor)

1993-01-01

Computing speed is leaping forward by several orders of magnitude each decade. Engineers and scientists gathered at a NASA Langley symposium to discuss these exciting trends as they apply to parallel computational methods for large-scale structural analysis and design. Among the topics discussed were: large-scale static analysis; dynamic, transient, and thermal analysis; domain decomposition (substructuring); and nonlinear and numerical methods.

Composing Data Parallel Code for a SPARQL Graph Engine

DOE Office of Scientific and Technical Information (OSTI.GOV)

Castellana, Vito G.; Tumeo, Antonino; Villa, Oreste

Big data analytics process large amount of data to extract knowledge from them. Semantic databases are big data applications that adopt the Resource Description Framework (RDF) to structure metadata through a graph-based representation. The graph based representation provides several benefits, such as the possibility to perform in memory processing with large amounts of parallelism. SPARQL is a language used to perform queries on RDF-structured data through graph matching. In this paper we present a tool that automatically translates SPARQL queries to parallel graph crawling and graph matching operations. The tool also supports complex SPARQL constructs, which requires more than basicmore » graph matching for their implementation. The tool generates parallel code annotated with OpenMP pragmas for x86 Shared-memory Multiprocessors (SMPs). With respect to commercial database systems such as Virtuoso, our approach reduces memory occupation due to join operations and provides higher performance. We show the scaling of the automatically generated graph-matching code on a 48-core SMP.« less

Large Scale GW Calculations on the Cori System

NASA Astrophysics Data System (ADS)

Deslippe, Jack; Del Ben, Mauro; da Jornada, Felipe; Canning, Andrew; Louie, Steven

The NERSC Cori system, powered by 9000+ Intel Xeon-Phi processors, represents one of the largest HPC systems for open-science in the United States and the world. We discuss the optimization of the GW methodology for this system, including both node level and system-scale optimizations. We highlight multiple large scale (thousands of atoms) case studies and discuss both absolute application performance and comparison to calculations on more traditional HPC architectures. We find that the GW method is particularly well suited for many-core architectures due to the ability to exploit a large amount of parallelism across many layers of the system. This work was supported by the U.S. Department of Energy, Office of Science, Basic Energy Sciences, Materials Sciences and Engineering Division, as part of the Computational Materials Sciences Program.

Demonstration of Hadoop-GIS: A Spatial Data Warehousing System Over MapReduce

PubMed Central

Aji, Ablimit; Sun, Xiling; Vo, Hoang; Liu, Qioaling; Lee, Rubao; Zhang, Xiaodong; Saltz, Joel; Wang, Fusheng

2016-01-01

The proliferation of GPS-enabled devices, and the rapid improvement of scientific instruments have resulted in massive amounts of spatial data in the last decade. Support of high performance spatial queries on large volumes data has become increasingly important in numerous fields, which requires a scalable and efficient spatial data warehousing solution as existing approaches exhibit scalability limitations and efficiency bottlenecks for large scale spatial applications. In this demonstration, we present Hadoop-GIS – a scalable and high performance spatial query system over MapReduce. Hadoop-GIS provides an efficient spatial query engine to process spatial queries, data and space based partitioning, and query pipelines that parallelize queries implicitly on MapReduce. Hadoop-GIS also provides an expressive, SQL-like spatial query language for workload specification. We will demonstrate how spatial queries are expressed in spatially extended SQL queries, and submitted through a command line/web interface for execution. Parallel to our system demonstration, we explain the system architecture and details on how queries are translated to MapReduce operators, optimized, and executed on Hadoop. In addition, we will showcase how the system can be used to support two representative real world use cases: large scale pathology analytical imaging, and geo-spatial data warehousing. PMID:27617325

MLP: A Parallel Programming Alternative to MPI for New Shared Memory Parallel Systems

NASA Technical Reports Server (NTRS)

Taft, James R.

1999-01-01

Recent developments at the NASA AMES Research Center's NAS Division have demonstrated that the new generation of NUMA based Symmetric Multi-Processing systems (SMPs), such as the Silicon Graphics Origin 2000, can successfully execute legacy vector oriented CFD production codes at sustained rates far exceeding processing rates possible on dedicated 16 CPU Cray C90 systems. This high level of performance is achieved via shared memory based Multi-Level Parallelism (MLP). This programming approach, developed at NAS and outlined below, is distinct from the message passing paradigm of MPI. It offers parallelism at both the fine and coarse grained level, with communication latencies that are approximately 50-100 times lower than typical MPI implementations on the same platform. Such latency reductions offer the promise of performance scaling to very large CPU counts. The method draws on, but is also distinct from, the newly defined OpenMP specification, which uses compiler directives to support a limited subset of multi-level parallel operations. The NAS MLP method is general, and applicable to a large class of NASA CFD codes.

OpenMP parallelization of a gridded SWAT (SWATG)

NASA Astrophysics Data System (ADS)

Zhang, Ying; Hou, Jinliang; Cao, Yongpan; Gu, Juan; Huang, Chunlin

2017-12-01

Large-scale, long-term and high spatial resolution simulation is a common issue in environmental modeling. A Gridded Hydrologic Response Unit (HRU)-based Soil and Water Assessment Tool (SWATG) that integrates grid modeling scheme with different spatial representations also presents such problems. The time-consuming problem affects applications of very high resolution large-scale watershed modeling. The OpenMP (Open Multi-Processing) parallel application interface is integrated with SWATG (called SWATGP) to accelerate grid modeling based on the HRU level. Such parallel implementation takes better advantage of the computational power of a shared memory computer system. We conducted two experiments at multiple temporal and spatial scales of hydrological modeling using SWATG and SWATGP on a high-end server. At 500-m resolution, SWATGP was found to be up to nine times faster than SWATG in modeling over a roughly 2000 km2 watershed with 1 CPU and a 15 thread configuration. The study results demonstrate that parallel models save considerable time relative to traditional sequential simulation runs. Parallel computations of environmental models are beneficial for model applications, especially at large spatial and temporal scales and at high resolutions. The proposed SWATGP model is thus a promising tool for large-scale and high-resolution water resources research and management in addition to offering data fusion and model coupling ability.

The force on the flex: Global parallelism and portability

NASA Technical Reports Server (NTRS)

Jordan, H. F.

1986-01-01

A parallel programming methodology, called the force, supports the construction of programs to be executed in parallel by an unspecified, but potentially large, number of processes. The methodology was originally developed on a pipelined, shared memory multiprocessor, the Denelcor HEP, and embodies the primitive operations of the force in a set of macros which expand into multiprocessor Fortran code. A small set of primitives is sufficient to write large parallel programs, and the system has been used to produce 10,000 line programs in computational fluid dynamics. The level of complexity of the force primitives is intermediate. It is high enough to mask detailed architectural differences between multiprocessors but low enough to give the user control over performance. The system is being ported to a medium scale multiprocessor, the Flex/32, which is a 20 processor system with a mixture of shared and local memory. Memory organization and the type of processor synchronization supported by the hardware on the two machines lead to some differences in efficient implementations of the force primitives, but the user interface remains the same. An initial implementation was done by retargeting the macros to Flexible Computer Corporation's ConCurrent C language. Subsequently, the macros were caused to directly produce the system calls which form the basis for ConCurrent C. The implementation of the Fortran based system is in step with Flexible Computer Corporations's implementation of a Fortran system in the parallel environment.

SOLAR WIND TURBULENCE FROM MHD TO SUB-ION SCALES: HIGH-RESOLUTION HYBRID SIMULATIONS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Franci, Luca; Verdini, Andrea; Landi, Simone

2015-05-10

We present results from a high-resolution and large-scale hybrid (fluid electrons and particle-in-cell protons) two-dimensional numerical simulation of decaying turbulence. Two distinct spectral regions (separated by a smooth break at proton scales) develop with clear power-law scaling, each one occupying about a decade in wavenumbers. The simulation results simultaneously exhibit several properties of the observed solar wind fluctuations: spectral indices of the magnetic, kinetic, and residual energy spectra in the magnetohydrodynamic (MHD) inertial range along with a flattening of the electric field spectrum, an increase in magnetic compressibility, and a strong coupling of the cascade with the density and themore » parallel component of the magnetic fluctuations at sub-proton scales. Our findings support the interpretation that in the solar wind, large-scale MHD fluctuations naturally evolve beyond proton scales into a turbulent regime that is governed by the generalized Ohm’s law.« less

Solar Wind Turbulence from MHD to Sub-ion Scales: High-resolution Hybrid Simulations

NASA Astrophysics Data System (ADS)

Franci, Luca; Verdini, Andrea; Matteini, Lorenzo; Landi, Simone; Hellinger, Petr

2015-05-01

We present results from a high-resolution and large-scale hybrid (fluid electrons and particle-in-cell protons) two-dimensional numerical simulation of decaying turbulence. Two distinct spectral regions (separated by a smooth break at proton scales) develop with clear power-law scaling, each one occupying about a decade in wavenumbers. The simulation results simultaneously exhibit several properties of the observed solar wind fluctuations: spectral indices of the magnetic, kinetic, and residual energy spectra in the magnetohydrodynamic (MHD) inertial range along with a flattening of the electric field spectrum, an increase in magnetic compressibility, and a strong coupling of the cascade with the density and the parallel component of the magnetic fluctuations at sub-proton scales. Our findings support the interpretation that in the solar wind, large-scale MHD fluctuations naturally evolve beyond proton scales into a turbulent regime that is governed by the generalized Ohm’s law.

Hadoop-GIS: A High Performance Spatial Data Warehousing System over MapReduce.

PubMed

Aji, Ablimit; Wang, Fusheng; Vo, Hoang; Lee, Rubao; Liu, Qiaoling; Zhang, Xiaodong; Saltz, Joel

2013-08-01

Support of high performance queries on large volumes of spatial data becomes increasingly important in many application domains, including geospatial problems in numerous fields, location based services, and emerging scientific applications that are increasingly data- and compute-intensive. The emergence of massive scale spatial data is due to the proliferation of cost effective and ubiquitous positioning technologies, development of high resolution imaging technologies, and contribution from a large number of community users. There are two major challenges for managing and querying massive spatial data to support spatial queries: the explosion of spatial data, and the high computational complexity of spatial queries. In this paper, we present Hadoop-GIS - a scalable and high performance spatial data warehousing system for running large scale spatial queries on Hadoop. Hadoop-GIS supports multiple types of spatial queries on MapReduce through spatial partitioning, customizable spatial query engine RESQUE, implicit parallel spatial query execution on MapReduce, and effective methods for amending query results through handling boundary objects. Hadoop-GIS utilizes global partition indexing and customizable on demand local spatial indexing to achieve efficient query processing. Hadoop-GIS is integrated into Hive to support declarative spatial queries with an integrated architecture. Our experiments have demonstrated the high efficiency of Hadoop-GIS on query response and high scalability to run on commodity clusters. Our comparative experiments have showed that performance of Hadoop-GIS is on par with parallel SDBMS and outperforms SDBMS for compute-intensive queries. Hadoop-GIS is available as a set of library for processing spatial queries, and as an integrated software package in Hive.

Hadoop-GIS: A High Performance Spatial Data Warehousing System over MapReduce

PubMed Central

Aji, Ablimit; Wang, Fusheng; Vo, Hoang; Lee, Rubao; Liu, Qiaoling; Zhang, Xiaodong; Saltz, Joel

2013-01-01

Support of high performance queries on large volumes of spatial data becomes increasingly important in many application domains, including geospatial problems in numerous fields, location based services, and emerging scientific applications that are increasingly data- and compute-intensive. The emergence of massive scale spatial data is due to the proliferation of cost effective and ubiquitous positioning technologies, development of high resolution imaging technologies, and contribution from a large number of community users. There are two major challenges for managing and querying massive spatial data to support spatial queries: the explosion of spatial data, and the high computational complexity of spatial queries. In this paper, we present Hadoop-GIS – a scalable and high performance spatial data warehousing system for running large scale spatial queries on Hadoop. Hadoop-GIS supports multiple types of spatial queries on MapReduce through spatial partitioning, customizable spatial query engine RESQUE, implicit parallel spatial query execution on MapReduce, and effective methods for amending query results through handling boundary objects. Hadoop-GIS utilizes global partition indexing and customizable on demand local spatial indexing to achieve efficient query processing. Hadoop-GIS is integrated into Hive to support declarative spatial queries with an integrated architecture. Our experiments have demonstrated the high efficiency of Hadoop-GIS on query response and high scalability to run on commodity clusters. Our comparative experiments have showed that performance of Hadoop-GIS is on par with parallel SDBMS and outperforms SDBMS for compute-intensive queries. Hadoop-GIS is available as a set of library for processing spatial queries, and as an integrated software package in Hive. PMID:24187650

Toward server-side, high performance climate change data analytics in the Earth System Grid Federation (ESGF) eco-system

NASA Astrophysics Data System (ADS)

Fiore, Sandro; Williams, Dean; Aloisio, Giovanni

2016-04-01

In many scientific domains such as climate, data is often n-dimensional and requires tools that support specialized data types and primitives to be properly stored, accessed, analysed and visualized. Moreover, new challenges arise in large-scale scenarios and eco-systems where petabytes (PB) of data can be available and data can be distributed and/or replicated (e.g., the Earth System Grid Federation (ESGF) serving the Coupled Model Intercomparison Project, Phase 5 (CMIP5) experiment, providing access to 2.5PB of data for the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5). Most of the tools currently available for scientific data analysis in the climate domain fail at large scale since they: (1) are desktop based and need the data locally; (2) are sequential, so do not benefit from available multicore/parallel machines; (3) do not provide declarative languages to express scientific data analysis tasks; (4) are domain-specific, which ties their adoption to a specific domain; and (5) do not provide a workflow support, to enable the definition of complex "experiments". The Ophidia project aims at facing most of the challenges highlighted above by providing a big data analytics framework for eScience. Ophidia provides declarative, server-side, and parallel data analysis, jointly with an internal storage model able to efficiently deal with multidimensional data and a hierarchical data organization to manage large data volumes ("datacubes"). The project relies on a strong background of high performance database management and OLAP systems to manage large scientific data sets. It also provides a native workflow management support, to define processing chains and workflows with tens to hundreds of data analytics operators to build real scientific use cases. With regard to interoperability aspects, the talk will present the contribution provided both to the RDA Working Group on Array Databases, and the Earth System Grid Federation (ESGF) Compute Working Team. Also highlighted will be the results of large scale climate model intercomparison data analysis experiments, for example: (1) defined in the context of the EU H2020 INDIGO-DataCloud project; (2) implemented in a real geographically distributed environment involving CMCC (Italy) and LLNL (US) sites; (3) exploiting Ophidia as server-side, parallel analytics engine; and (4) applied on real CMIP5 data sets available through ESGF.

Scaling up digital circuit computation with DNA strand displacement cascades.

PubMed

Qian, Lulu; Winfree, Erik

2011-06-03

To construct sophisticated biochemical circuits from scratch, one needs to understand how simple the building blocks can be and how robustly such circuits can scale up. Using a simple DNA reaction mechanism based on a reversible strand displacement process, we experimentally demonstrated several digital logic circuits, culminating in a four-bit square-root circuit that comprises 130 DNA strands. These multilayer circuits include thresholding and catalysis within every logical operation to perform digital signal restoration, which enables fast and reliable function in large circuits with roughly constant switching time and linear signal propagation delays. The design naturally incorporates other crucial elements for large-scale circuitry, such as general debugging tools, parallel circuit preparation, and an abstraction hierarchy supported by an automated circuit compiler.

Creating a Parallel Version of VisIt for Microsoft Windows

DOE Office of Scientific and Technical Information (OSTI.GOV)

Whitlock, B J; Biagas, K S; Rawson, P L

2011-12-07

VisIt is a popular, free interactive parallel visualization and analysis tool for scientific data. Users can quickly generate visualizations from their data, animate them through time, manipulate them, and save the resulting images or movies for presentations. VisIt was designed from the ground up to work on many scales of computers from modest desktops up to massively parallel clusters. VisIt is comprised of a set of cooperating programs. All programs can be run locally or in client/server mode in which some run locally and some run remotely on compute clusters. The VisIt program most able to harness today's computing powermore » is the VisIt compute engine. The compute engine is responsible for reading simulation data from disk, processing it, and sending results or images back to the VisIt viewer program. In a parallel environment, the compute engine runs several processes, coordinating using the Message Passing Interface (MPI) library. Each MPI process reads some subset of the scientific data and filters the data in various ways to create useful visualizations. By using MPI, VisIt has been able to scale well into the thousands of processors on large computers such as dawn and graph at LLNL. The advent of multicore CPU's has made parallelism the 'new' way to achieve increasing performance. With today's computers having at least 2 cores and in many cases up to 8 and beyond, it is more important than ever to deploy parallel software that can use that computing power not only on clusters but also on the desktop. We have created a parallel version of VisIt for Windows that uses Microsoft's MPI implementation (MSMPI) to process data in parallel on the Windows desktop as well as on a Windows HPC cluster running Microsoft Windows Server 2008. Initial desktop parallel support for Windows was deployed in VisIt 2.4.0. Windows HPC cluster support has been completed and will appear in the VisIt 2.5.0 release. We plan to continue supporting parallel VisIt on Windows so our users will be able to take full advantage of their multicore resources.« less

Software Engineering Support of the Third Round of Scientific Grand Challenge Investigations: Earth System Modeling Software Framework Survey

NASA Technical Reports Server (NTRS)

Talbot, Bryan; Zhou, Shu-Jia; Higgins, Glenn; Zukor, Dorothy (Technical Monitor)

2002-01-01

One of the most significant challenges in large-scale climate modeling, as well as in high-performance computing in other scientific fields, is that of effectively integrating many software models from multiple contributors. A software framework facilitates the integration task, both in the development and runtime stages of the simulation. Effective software frameworks reduce the programming burden for the investigators, freeing them to focus more on the science and less on the parallel communication implementation. while maintaining high performance across numerous supercomputer and workstation architectures. This document surveys numerous software frameworks for potential use in Earth science modeling. Several frameworks are evaluated in depth, including Parallel Object-Oriented Methods and Applications (POOMA), Cactus (from (he relativistic physics community), Overture, Goddard Earth Modeling System (GEMS), the National Center for Atmospheric Research Flux Coupler, and UCLA/UCB Distributed Data Broker (DDB). Frameworks evaluated in less detail include ROOT, Parallel Application Workspace (PAWS), and Advanced Large-Scale Integrated Computational Environment (ALICE). A host of other frameworks and related tools are referenced in this context. The frameworks are evaluated individually and also compared with each other.

Parallel Quantum Circuit in a Tunnel Junction

NASA Astrophysics Data System (ADS)

Faizy Namarvar, Omid; Dridi, Ghassen; Joachim, Christian; GNS theory Group Team

In between 2 metallic nanopads, adding identical and independent electron transfer paths in parallel increases the electronic effective coupling between the 2 nanopads through the quantum circuit defined by those paths. Measuring this increase of effective coupling using the tunnelling current intensity can lead for example for 2 paths in parallel to the now standard G =G1 +G2 + 2√{G1 .G2 } conductance superposition law (1). This is only valid for the tunnelling regime (2). For large electronic coupling to the nanopads (or at resonance), G can saturate and even decay as a function of the number of parallel paths added in the quantum circuit (3). We provide here the explanation of this phenomenon: the measurement of the effective Rabi oscillation frequency using the current intensity is constrained by the normalization principle of quantum mechanics. This limits the quantum conductance G for example to go when there is only one channel per metallic nanopads. This ef fect has important consequences for the design of Boolean logic gates at the atomic scale using atomic scale or intramolecular circuits. References: This has the financial support by European PAMS project.

Cloud Computing Boosts Business Intelligence of Telecommunication Industry

NASA Astrophysics Data System (ADS)

Xu, Meng; Gao, Dan; Deng, Chao; Luo, Zhiguo; Sun, Shaoling

Business Intelligence becomes an attracting topic in today's data intensive applications, especially in telecommunication industry. Meanwhile, Cloud Computing providing IT supporting Infrastructure with excellent scalability, large scale storage, and high performance becomes an effective way to implement parallel data processing and data mining algorithms. BC-PDM (Big Cloud based Parallel Data Miner) is a new MapReduce based parallel data mining platform developed by CMRI (China Mobile Research Institute) to fit the urgent requirements of business intelligence in telecommunication industry. In this paper, the architecture, functionality and performance of BC-PDM are presented, together with the experimental evaluation and case studies of its applications. The evaluation result demonstrates both the usability and the cost-effectiveness of Cloud Computing based Business Intelligence system in applications of telecommunication industry.

Petascale Simulation Initiative Tech Base: FY2007 Final Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

May, J; Chen, R; Jefferson, D

The Petascale Simulation Initiative began as an LDRD project in the middle of Fiscal Year 2004. The goal of the project was to develop techniques to allow large-scale scientific simulation applications to better exploit the massive parallelism that will come with computers running at petaflops per second. One of the major products of this work was the design and prototype implementation of a programming model and a runtime system that lets applications extend data-parallel applications to use task parallelism. By adopting task parallelism, applications can use processing resources more flexibly, exploit multiple forms of parallelism, and support more sophisticated multiscalemore » and multiphysics models. Our programming model was originally called the Symponents Architecture but is now known as Cooperative Parallelism, and the runtime software that supports it is called Coop. (However, we sometimes refer to the programming model as Coop for brevity.) We have documented the programming model and runtime system in a submitted conference paper [1]. This report focuses on the specific accomplishments of the Cooperative Parallelism project (as we now call it) under Tech Base funding in FY2007. Development and implementation of the model under LDRD funding alone proceeded to the point of demonstrating a large-scale materials modeling application using Coop on more than 1300 processors by the end of FY2006. Beginning in FY2007, the project received funding from both LDRD and the Computation Directorate Tech Base program. Later in the year, after the three-year term of the LDRD funding ended, the ASC program supported the project with additional funds. The goal of the Tech Base effort was to bring Coop from a prototype to a production-ready system that a variety of LLNL users could work with. Specifically, the major tasks that we planned for the project were: (1) Port SARS [former name of the Coop runtime system] to another LLNL platform, probably Thunder or Peloton (depending on when Peloton becomes available); (2) Improve SARS's robustness and ease-of-use, and develop user documentation; and (3) Work with LLNL code teams to help them determine how Symponents could benefit their applications. The original funding request was $296,000 for the year, and we eventually received $252,000. The remainder of this report describes our efforts and accomplishments for each of the goals listed above.« less

High Performance Geostatistical Modeling of Biospheric Resources

NASA Astrophysics Data System (ADS)

Pedelty, J. A.; Morisette, J. T.; Smith, J. A.; Schnase, J. L.; Crosier, C. S.; Stohlgren, T. J.

2004-12-01

We are using parallel geostatistical codes to study spatial relationships among biospheric resources in several study areas. For example, spatial statistical models based on large- and small-scale variability have been used to predict species richness of both native and exotic plants (hot spots of diversity) and patterns of exotic plant invasion. However, broader use of geostastics in natural resource modeling, especially at regional and national scales, has been limited due to the large computing requirements of these applications. To address this problem, we implemented parallel versions of the kriging spatial interpolation algorithm. The first uses the Message Passing Interface (MPI) in a master/slave paradigm on an open source Linux Beowulf cluster, while the second is implemented with the new proprietary Xgrid distributed processing system on an Xserve G5 cluster from Apple Computer, Inc. These techniques are proving effective and provide the basis for a national decision support capability for invasive species management that is being jointly developed by NASA and the US Geological Survey.

Decomposition method for fast computation of gigapixel-sized Fresnel holograms on a graphics processing unit cluster.

PubMed

Jackin, Boaz Jessie; Watanabe, Shinpei; Ootsu, Kanemitsu; Ohkawa, Takeshi; Yokota, Takashi; Hayasaki, Yoshio; Yatagai, Toyohiko; Baba, Takanobu

2018-04-20

A parallel computation method for large-size Fresnel computer-generated hologram (CGH) is reported. The method was introduced by us in an earlier report as a technique for calculating Fourier CGH from 2D object data. In this paper we extend the method to compute Fresnel CGH from 3D object data. The scale of the computation problem is also expanded to 2 gigapixels, making it closer to real application requirements. The significant feature of the reported method is its ability to avoid communication overhead and thereby fully utilize the computing power of parallel devices. The method exhibits three layers of parallelism that favor small to large scale parallel computing machines. Simulation and optical experiments were conducted to demonstrate the workability and to evaluate the efficiency of the proposed technique. A two-times improvement in computation speed has been achieved compared to the conventional method, on a 16-node cluster (one GPU per node) utilizing only one layer of parallelism. A 20-times improvement in computation speed has been estimated utilizing two layers of parallelism on a very large-scale parallel machine with 16 nodes, where each node has 16 GPUs.

Parallel Clustering Algorithm for Large-Scale Biological Data Sets

PubMed Central

Wang, Minchao; Zhang, Wu; Ding, Wang; Dai, Dongbo; Zhang, Huiran; Xie, Hao; Chen, Luonan; Guo, Yike; Xie, Jiang

2014-01-01

Backgrounds Recent explosion of biological data brings a great challenge for the traditional clustering algorithms. With increasing scale of data sets, much larger memory and longer runtime are required for the cluster identification problems. The affinity propagation algorithm outperforms many other classical clustering algorithms and is widely applied into the biological researches. However, the time and space complexity become a great bottleneck when handling the large-scale data sets. Moreover, the similarity matrix, whose constructing procedure takes long runtime, is required before running the affinity propagation algorithm, since the algorithm clusters data sets based on the similarities between data pairs. Methods Two types of parallel architectures are proposed in this paper to accelerate the similarity matrix constructing procedure and the affinity propagation algorithm. The memory-shared architecture is used to construct the similarity matrix, and the distributed system is taken for the affinity propagation algorithm, because of its large memory size and great computing capacity. An appropriate way of data partition and reduction is designed in our method, in order to minimize the global communication cost among processes. Result A speedup of 100 is gained with 128 cores. The runtime is reduced from serval hours to a few seconds, which indicates that parallel algorithm is capable of handling large-scale data sets effectively. The parallel affinity propagation also achieves a good performance when clustering large-scale gene data (microarray) and detecting families in large protein superfamilies. PMID:24705246

Handling Big Data in Medical Imaging: Iterative Reconstruction with Large-Scale Automated Parallel Computation

PubMed Central

Lee, Jae H.; Yao, Yushu; Shrestha, Uttam; Gullberg, Grant T.; Seo, Youngho

2014-01-01

The primary goal of this project is to implement the iterative statistical image reconstruction algorithm, in this case maximum likelihood expectation maximum (MLEM) used for dynamic cardiac single photon emission computed tomography, on Spark/GraphX. This involves porting the algorithm to run on large-scale parallel computing systems. Spark is an easy-to- program software platform that can handle large amounts of data in parallel. GraphX is a graph analytic system running on top of Spark to handle graph and sparse linear algebra operations in parallel. The main advantage of implementing MLEM algorithm in Spark/GraphX is that it allows users to parallelize such computation without any expertise in parallel computing or prior knowledge in computer science. In this paper we demonstrate a successful implementation of MLEM in Spark/GraphX and present the performance gains with the goal to eventually make it useable in clinical setting. PMID:27081299

Handling Big Data in Medical Imaging: Iterative Reconstruction with Large-Scale Automated Parallel Computation.

PubMed

Lee, Jae H; Yao, Yushu; Shrestha, Uttam; Gullberg, Grant T; Seo, Youngho

2014-11-01

The primary goal of this project is to implement the iterative statistical image reconstruction algorithm, in this case maximum likelihood expectation maximum (MLEM) used for dynamic cardiac single photon emission computed tomography, on Spark/GraphX. This involves porting the algorithm to run on large-scale parallel computing systems. Spark is an easy-to- program software platform that can handle large amounts of data in parallel. GraphX is a graph analytic system running on top of Spark to handle graph and sparse linear algebra operations in parallel. The main advantage of implementing MLEM algorithm in Spark/GraphX is that it allows users to parallelize such computation without any expertise in parallel computing or prior knowledge in computer science. In this paper we demonstrate a successful implementation of MLEM in Spark/GraphX and present the performance gains with the goal to eventually make it useable in clinical setting.

Geocomputation over Hybrid Computer Architecture and Systems: Prior Works and On-going Initiatives at UARK

NASA Astrophysics Data System (ADS)

Shi, X.

2015-12-01

As NSF indicated - "Theory and experimentation have for centuries been regarded as two fundamental pillars of science. It is now widely recognized that computational and data-enabled science forms a critical third pillar." Geocomputation is the third pillar of GIScience and geosciences. With the exponential growth of geodata, the challenge of scalable and high performance computing for big data analytics become urgent because many research activities are constrained by the inability of software or tool that even could not complete the computation process. Heterogeneous geodata integration and analytics obviously magnify the complexity and operational time frame. Many large-scale geospatial problems may be not processable at all if the computer system does not have sufficient memory or computational power. Emerging computer architectures, such as Intel's Many Integrated Core (MIC) Architecture and Graphics Processing Unit (GPU), and advanced computing technologies provide promising solutions to employ massive parallelism and hardware resources to achieve scalability and high performance for data intensive computing over large spatiotemporal and social media data. Exploring novel algorithms and deploying the solutions in massively parallel computing environment to achieve the capability for scalable data processing and analytics over large-scale, complex, and heterogeneous geodata with consistent quality and high-performance has been the central theme of our research team in the Department of Geosciences at the University of Arkansas (UARK). New multi-core architectures combined with application accelerators hold the promise to achieve scalability and high performance by exploiting task and data levels of parallelism that are not supported by the conventional computing systems. Such a parallel or distributed computing environment is particularly suitable for large-scale geocomputation over big data as proved by our prior works, while the potential of such advanced infrastructure remains unexplored in this domain. Within this presentation, our prior and on-going initiatives will be summarized to exemplify how we exploit multicore CPUs, GPUs, and MICs, and clusters of CPUs, GPUs and MICs, to accelerate geocomputation in different applications.

Applications of Parallel Process HiMAP for Large Scale Multidisciplinary Problems

NASA Technical Reports Server (NTRS)

Guruswamy, Guru P.; Potsdam, Mark; Rodriguez, David; Kwak, Dochay (Technical Monitor)

2000-01-01

HiMAP is a three level parallel middleware that can be interfaced to a large scale global design environment for code independent, multidisciplinary analysis using high fidelity equations. Aerospace technology needs are rapidly changing. Computational tools compatible with the requirements of national programs such as space transportation are needed. Conventional computation tools are inadequate for modern aerospace design needs. Advanced, modular computational tools are needed, such as those that incorporate the technology of massively parallel processors (MPP).

Parallel heuristics for scalable community detection

DOE PAGES

Lu, Hao; Halappanavar, Mahantesh; Kalyanaraman, Ananth

2015-08-14

Community detection has become a fundamental operation in numerous graph-theoretic applications. Despite its potential for application, there is only limited support for community detection on large-scale parallel computers, largely owing to the irregular and inherently sequential nature of the underlying heuristics. In this paper, we present parallelization heuristics for fast community detection using the Louvain method as the serial template. The Louvain method is an iterative heuristic for modularity optimization. Originally developed in 2008, the method has become increasingly popular owing to its ability to detect high modularity community partitions in a fast and memory-efficient manner. However, the method ismore » also inherently sequential, thereby limiting its scalability. Here, we observe certain key properties of this method that present challenges for its parallelization, and consequently propose heuristics that are designed to break the sequential barrier. For evaluation purposes, we implemented our heuristics using OpenMP multithreading, and tested them over real world graphs derived from multiple application domains. Compared to the serial Louvain implementation, our parallel implementation is able to produce community outputs with a higher modularity for most of the inputs tested, in comparable number or fewer iterations, while providing real speedups of up to 16x using 32 threads.« less

Improving parallel I/O autotuning with performance modeling

DOE PAGES

Behzad, Babak; Byna, Surendra; Wild, Stefan M.; ...

2014-01-01

Various layers of the parallel I/O subsystem offer tunable parameters for improving I/O performance on large-scale computers. However, searching through a large parameter space is challenging. We are working towards an autotuning framework for determining the parallel I/O parameters that can achieve good I/O performance for different data write patterns. In this paper, we characterize parallel I/O and discuss the development of predictive models for use in effectively reducing the parameter space. Furthermore, applying our technique on tuning an I/O kernel derived from a large-scale simulation code shows that the search time can be reduced from 12 hours to 2more » hours, while achieving 54X I/O performance speedup.« less

CERN data services for LHC computing

NASA Astrophysics Data System (ADS)

Espinal, X.; Bocchi, E.; Chan, B.; Fiorot, A.; Iven, J.; Lo Presti, G.; Lopez, J.; Gonzalez, H.; Lamanna, M.; Mascetti, L.; Moscicki, J.; Pace, A.; Peters, A.; Ponce, S.; Rousseau, H.; van der Ster, D.

2017-10-01

Dependability, resilience, adaptability and efficiency. Growing requirements require tailoring storage services and novel solutions. Unprecedented volumes of data coming from the broad number of experiments at CERN need to be quickly available in a highly scalable way for large-scale processing and data distribution while in parallel they are routed to tape for long-term archival. These activities are critical for the success of HEP experiments. Nowadays we operate at high incoming throughput (14GB/s during 2015 LHC Pb-Pb run and 11PB in July 2016) and with concurrent complex production work-loads. In parallel our systems provide the platform for the continuous user and experiment driven work-loads for large-scale data analysis, including end-user access and sharing. The storage services at CERN cover the needs of our community: EOS and CASTOR as a large-scale storage; CERNBox for end-user access and sharing; Ceph as data back-end for the CERN OpenStack infrastructure, NFS services and S3 functionality; AFS for legacy distributed-file-system services. In this paper we will summarise the experience in supporting LHC experiments and the transition of our infrastructure from static monolithic systems to flexible components providing a more coherent environment with pluggable protocols, tuneable QoS, sharing capabilities and fine grained ACLs management while continuing to guarantee dependable and robust services.

A Metascalable Computing Framework for Large Spatiotemporal-Scale Atomistic Simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nomura, K; Seymour, R; Wang, W

2009-02-17

A metascalable (or 'design once, scale on new architectures') parallel computing framework has been developed for large spatiotemporal-scale atomistic simulations of materials based on spatiotemporal data locality principles, which is expected to scale on emerging multipetaflops architectures. The framework consists of: (1) an embedded divide-and-conquer (EDC) algorithmic framework based on spatial locality to design linear-scaling algorithms for high complexity problems; (2) a space-time-ensemble parallel (STEP) approach based on temporal locality to predict long-time dynamics, while introducing multiple parallelization axes; and (3) a tunable hierarchical cellular decomposition (HCD) parallelization framework to map these O(N) algorithms onto a multicore cluster based onmore » hybrid implementation combining message passing and critical section-free multithreading. The EDC-STEP-HCD framework exposes maximal concurrency and data locality, thereby achieving: (1) inter-node parallel efficiency well over 0.95 for 218 billion-atom molecular-dynamics and 1.68 trillion electronic-degrees-of-freedom quantum-mechanical simulations on 212,992 IBM BlueGene/L processors (superscalability); (2) high intra-node, multithreading parallel efficiency (nanoscalability); and (3) nearly perfect time/ensemble parallel efficiency (eon-scalability). The spatiotemporal scale covered by MD simulation on a sustained petaflops computer per day (i.e. petaflops {center_dot} day of computing) is estimated as NT = 2.14 (e.g. N = 2.14 million atoms for T = 1 microseconds).« less

An efficient implementation of 3D high-resolution imaging for large-scale seismic data with GPU/CPU heterogeneous parallel computing

NASA Astrophysics Data System (ADS)

Xu, Jincheng; Liu, Wei; Wang, Jin; Liu, Linong; Zhang, Jianfeng

2018-02-01

De-absorption pre-stack time migration (QPSTM) compensates for the absorption and dispersion of seismic waves by introducing an effective Q parameter, thereby making it an effective tool for 3D, high-resolution imaging of seismic data. Although the optimal aperture obtained via stationary-phase migration reduces the computational cost of 3D QPSTM and yields 3D stationary-phase QPSTM, the associated computational efficiency is still the main problem in the processing of 3D, high-resolution images for real large-scale seismic data. In the current paper, we proposed a division method for large-scale, 3D seismic data to optimize the performance of stationary-phase QPSTM on clusters of graphics processing units (GPU). Then, we designed an imaging point parallel strategy to achieve an optimal parallel computing performance. Afterward, we adopted an asynchronous double buffering scheme for multi-stream to perform the GPU/CPU parallel computing. Moreover, several key optimization strategies of computation and storage based on the compute unified device architecture (CUDA) were adopted to accelerate the 3D stationary-phase QPSTM algorithm. Compared with the initial GPU code, the implementation of the key optimization steps, including thread optimization, shared memory optimization, register optimization and special function units (SFU), greatly improved the efficiency. A numerical example employing real large-scale, 3D seismic data showed that our scheme is nearly 80 times faster than the CPU-QPSTM algorithm. Our GPU/CPU heterogeneous parallel computing framework significant reduces the computational cost and facilitates 3D high-resolution imaging for large-scale seismic data.

Large-Scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) Simulations of the Molecular Crystal alphaRDX

DTIC Science & Technology

2013-08-01

potential for HMX / RDX (3, 9). ...................................................................................8 1 1. Purpose This work...6 dispersion and electrostatic interactions. Constants for the SB potential are given in table 1. 8 Table 1. SB potential for HMX / RDX (3, 9...modeling dislocations in the energetic molecular crystal RDX using the Large-Scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) molecular

Grid-Enabled Quantitative Analysis of Breast Cancer

DTIC Science & Technology

2010-10-01

large-scale, multi-modality computerized image analysis . The central hypothesis of this research is that large-scale image analysis for breast cancer...research, we designed a pilot study utilizing large scale parallel Grid computing harnessing nationwide infrastructure for medical image analysis . Also

Parallelization of Nullspace Algorithm for the computation of metabolic pathways

PubMed Central

Jevremović, Dimitrije; Trinh, Cong T.; Srienc, Friedrich; Sosa, Carlos P.; Boley, Daniel

2011-01-01

Elementary mode analysis is a useful metabolic pathway analysis tool in understanding and analyzing cellular metabolism, since elementary modes can represent metabolic pathways with unique and minimal sets of enzyme-catalyzed reactions of a metabolic network under steady state conditions. However, computation of the elementary modes of a genome- scale metabolic network with 100–1000 reactions is very expensive and sometimes not feasible with the commonly used serial Nullspace Algorithm. In this work, we develop a distributed memory parallelization of the Nullspace Algorithm to handle efficiently the computation of the elementary modes of a large metabolic network. We give an implementation in C++ language with the support of MPI library functions for the parallel communication. Our proposed algorithm is accompanied with an analysis of the complexity and identification of major bottlenecks during computation of all possible pathways of a large metabolic network. The algorithm includes methods to achieve load balancing among the compute-nodes and specific communication patterns to reduce the communication overhead and improve efficiency. PMID:22058581

NASA Exhibits

NASA Technical Reports Server (NTRS)

Deardorff, Glenn; Djomehri, M. Jahed; Freeman, Ken; Gambrel, Dave; Green, Bryan; Henze, Chris; Hinke, Thomas; Hood, Robert; Kiris, Cetin; Moran, Patrick;

Solutions of large-scale electromagnetics problems involving dielectric objects with the parallel multilevel fast multipole algorithm.

PubMed

Ergül, Özgür

2011-11-01

Fast and accurate solutions of large-scale electromagnetics problems involving homogeneous dielectric objects are considered. Problems are formulated with the electric and magnetic current combined-field integral equation and discretized with the Rao-Wilton-Glisson functions. Solutions are performed iteratively by using the multilevel fast multipole algorithm (MLFMA). For the solution of large-scale problems discretized with millions of unknowns, MLFMA is parallelized on distributed-memory architectures using a rigorous technique, namely, the hierarchical partitioning strategy. Efficiency and accuracy of the developed implementation are demonstrated on very large problems involving as many as 100 million unknowns.

Random number generators for large-scale parallel Monte Carlo simulations on FPGA

NASA Astrophysics Data System (ADS)

Lin, Y.; Wang, F.; Liu, B.

2018-05-01

Through parallelization, field programmable gate array (FPGA) can achieve unprecedented speeds in large-scale parallel Monte Carlo (LPMC) simulations. FPGA presents both new constraints and new opportunities for the implementations of random number generators (RNGs), which are key elements of any Monte Carlo (MC) simulation system. Using empirical and application based tests, this study evaluates all of the four RNGs used in previous FPGA based MC studies and newly proposed FPGA implementations for two well-known high-quality RNGs that are suitable for LPMC studies on FPGA. One of the newly proposed FPGA implementations: a parallel version of additive lagged Fibonacci generator (Parallel ALFG) is found to be the best among the evaluated RNGs in fulfilling the needs of LPMC simulations on FPGA.

Parallel Simulation of Unsteady Turbulent Flames

NASA Technical Reports Server (NTRS)

Menon, Suresh

1996-01-01

Time-accurate simulation of turbulent flames in high Reynolds number flows is a challenging task since both fluid dynamics and combustion must be modeled accurately. To numerically simulate this phenomenon, very large computer resources (both time and memory) are required. Although current vector supercomputers are capable of providing adequate resources for simulations of this nature, the high cost and their limited availability, makes practical use of such machines less than satisfactory. At the same time, the explicit time integration algorithms used in unsteady flow simulations often possess a very high degree of parallelism, making them very amenable to efficient implementation on large-scale parallel computers. Under these circumstances, distributed memory parallel computers offer an excellent near-term solution for greatly increased computational speed and memory, at a cost that may render the unsteady simulations of the type discussed above more feasible and affordable.This paper discusses the study of unsteady turbulent flames using a simulation algorithm that is capable of retaining high parallel efficiency on distributed memory parallel architectures. Numerical studies are carried out using large-eddy simulation (LES). In LES, the scales larger than the grid are computed using a time- and space-accurate scheme, while the unresolved small scales are modeled using eddy viscosity based subgrid models. This is acceptable for the moment/energy closure since the small scales primarily provide a dissipative mechanism for the energy transferred from the large scales. However, for combustion to occur, the species must first undergo mixing at the small scales and then come into molecular contact. Therefore, global models cannot be used. Recently, a new model for turbulent combustion was developed, in which the combustion is modeled, within the subgrid (small-scales) using a methodology that simulates the mixing and the molecular transport and the chemical kinetics within each LES grid cell. Finite-rate kinetics can be included without any closure and this approach actually provides a means to predict the turbulent rates and the turbulent flame speed. The subgrid combustion model requires resolution of the local time scales associated with small-scale mixing, molecular diffusion and chemical kinetics and, therefore, within each grid cell, a significant amount of computations must be carried out before the large-scale (LES resolved) effects are incorporated. Therefore, this approach is uniquely suited for parallel processing and has been implemented on various systems such as: Intel Paragon, IBM SP-2, Cray T3D and SGI Power Challenge (PC) using the system independent Message Passing Interface (MPI) compiler. In this paper, timing data on these machines is reported along with some characteristic results.

Parallel VLSI architecture emulation and the organization of APSA/MPP

NASA Technical Reports Server (NTRS)

Odonnell, John T.

1987-01-01

The Applicative Programming System Architecture (APSA) combines an applicative language interpreter with a novel parallel computer architecture that is well suited for Very Large Scale Integration (VLSI) implementation. The Massively Parallel Processor (MPP) can simulate VLSI circuits by allocating one processing element in its square array to an area on a square VLSI chip. As long as there are not too many long data paths, the MPP can simulate a VLSI clock cycle very rapidly. The APSA circuit contains a binary tree with a few long paths and many short ones. A skewed H-tree layout allows every processing element to simulate a leaf cell and up to four tree nodes, with no loss in parallelism. Emulation of a key APSA algorithm on the MPP resulted in performance 16,000 times faster than a Vax. This speed will make it possible for the APSA language interpreter to run fast enough to support research in parallel list processing algorithms.

Xyce parallel electronic simulator : reference guide.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mei, Ting; Rankin, Eric Lamont; Thornquist, Heidi K.

2011-05-01

This document is a reference guide to the Xyce Parallel Electronic Simulator, and is a companion document to the Xyce Users Guide. The focus of this document is (to the extent possible) exhaustively list device parameters, solver options, parser options, and other usage details of Xyce. This document is not intended to be a tutorial. Users who are new to circuit simulation are better served by the Xyce Users Guide. The Xyce Parallel Electronic Simulator has been written to support, in a rigorous manner, the simulation needs of the Sandia National Laboratories electrical designers. It is targeted specifically to runmore » on large-scale parallel computing platforms but also runs well on a variety of architectures including single processor workstations. It also aims to support a variety of devices and models specific to Sandia needs. This document is intended to complement the Xyce Users Guide. It contains comprehensive, detailed information about a number of topics pertinent to the usage of Xyce. Included in this document is a netlist reference for the input-file commands and elements supported within Xyce; a command line reference, which describes the available command line arguments for Xyce; and quick-references for users of other circuit codes, such as Orcad's PSpice and Sandia's ChileSPICE.« less

The Parallel System for Integrating Impact Models and Sectors (pSIMS)

NASA Technical Reports Server (NTRS)

Elliott, Joshua; Kelly, David; Chryssanthacopoulos, James; Glotter, Michael; Jhunjhnuwala, Kanika; Best, Neil; Wilde, Michael; Foster, Ian

2014-01-01

We present a framework for massively parallel climate impact simulations: the parallel System for Integrating Impact Models and Sectors (pSIMS). This framework comprises a) tools for ingesting and converting large amounts of data to a versatile datatype based on a common geospatial grid; b) tools for translating this datatype into custom formats for site-based models; c) a scalable parallel framework for performing large ensemble simulations, using any one of a number of different impacts models, on clusters, supercomputers, distributed grids, or clouds; d) tools and data standards for reformatting outputs to common datatypes for analysis and visualization; and e) methodologies for aggregating these datatypes to arbitrary spatial scales such as administrative and environmental demarcations. By automating many time-consuming and error-prone aspects of large-scale climate impacts studies, pSIMS accelerates computational research, encourages model intercomparison, and enhances reproducibility of simulation results. We present the pSIMS design and use example assessments to demonstrate its multi-model, multi-scale, and multi-sector versatility.

Design Sketches For Optical Crossbar Switches Intended For Large-Scale Parallel Processing Applications

NASA Astrophysics Data System (ADS)

Hartmann, Alfred; Redfield, Steve

1989-04-01

This paper discusses design of large-scale (1000x 1000) optical crossbar switching networks for use in parallel processing supercom-puters. Alternative design sketches for an optical crossbar switching network are presented using free-space optical transmission with either a beam spreading/masking model or a beam steering model for internodal communications. The performances of alternative multiple access channel communications protocol-unslotted and slotted ALOHA and carrier sense multiple access (CSMA)-are compared with the performance of the classic arbitrated bus crossbar of conventional electronic parallel computing. These comparisons indicate an almost inverse relationship between ease of implementation and speed of operation. Practical issues of optical system design are addressed, and an optically addressed, composite spatial light modulator design is presented for fabrication to arbitrarily large scale. The wide range of switch architecture, communications protocol, optical systems design, device fabrication, and system performance problems presented by these design sketches poses a serious challenge to practical exploitation of highly parallel optical interconnects in advanced computer designs.

Efficient parallelization of analytic bond-order potentials for large-scale atomistic simulations

NASA Astrophysics Data System (ADS)

Teijeiro, C.; Hammerschmidt, T.; Drautz, R.; Sutmann, G.

2016-07-01

Analytic bond-order potentials (BOPs) provide a way to compute atomistic properties with controllable accuracy. For large-scale computations of heterogeneous compounds at the atomistic level, both the computational efficiency and memory demand of BOP implementations have to be optimized. Since the evaluation of BOPs is a local operation within a finite environment, the parallelization concepts known from short-range interacting particle simulations can be applied to improve the performance of these simulations. In this work, several efficient parallelization methods for BOPs that use three-dimensional domain decomposition schemes are described. The schemes are implemented into the bond-order potential code BOPfox, and their performance is measured in a series of benchmarks. Systems of up to several millions of atoms are simulated on a high performance computing system, and parallel scaling is demonstrated for up to thousands of processors.

Xyce Parallel Electronic Simulator Users' Guide Version 6.7.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Keiter, Eric R.; Aadithya, Karthik Venkatraman; Mei, Ting

This manual describes the use of the Xyce Parallel Electronic Simulator. Xyce has been designed as a SPICE-compatible, high-performance analog circuit simulator, and has been written to support the simulation needs of the Sandia National Laboratories electrical designers. This development has focused on improving capability over the current state-of-the-art in the following areas: Capability to solve extremely large circuit problems by supporting large-scale parallel com- puting platforms (up to thousands of processors). This includes support for most popular parallel and serial computers. A differential-algebraic-equation (DAE) formulation, which better isolates the device model package from solver algorithms. This allows one tomore » develop new types of analysis without requiring the implementation of analysis-specific device models. Device models that are specifically tailored to meet Sandia's needs, including some radiation- aware devices (for Sandia users only). Object-oriented code design and implementation using modern coding practices. Xyce is a parallel code in the most general sense of the phrase -- a message passing parallel implementation -- which allows it to run efficiently a wide range of computing platforms. These include serial, shared-memory and distributed-memory parallel platforms. Attention has been paid to the specific nature of circuit-simulation problems to ensure that optimal parallel efficiency is achieved as the number of processors grows. The information herein is subject to change without notice. Copyright c 2002-2017 Sandia Corporation. All rights reserved. Trademarks Xyce TM Electronic Simulator and Xyce TM are trademarks of Sandia Corporation. Orcad, Orcad Capture, PSpice and Probe are registered trademarks of Cadence Design Systems, Inc. Microsoft, Windows and Windows 7 are registered trademarks of Microsoft Corporation. Medici, DaVinci and Taurus are registered trademarks of Synopsys Corporation. Amtec and TecPlot are trademarks of Amtec Engineering, Inc. All other trademarks are property of their respective owners. Contacts World Wide Web http://xyce.sandia.gov https://info.sandia.gov/xyce (Sandia only) Email xyce@sandia.gov (outside Sandia) xyce-sandia@sandia.gov (Sandia only) Bug Reports (Sandia only) http://joseki-vm.sandia.gov/bugzilla http://morannon.sandia.gov/bugzilla« less

Application of high-performance computing to numerical simulation of human movement

NASA Technical Reports Server (NTRS)

Anderson, F. C.; Ziegler, J. M.; Pandy, M. G.; Whalen, R. T.

1995-01-01

We have examined the feasibility of using massively-parallel and vector-processing supercomputers to solve large-scale optimization problems for human movement. Specifically, we compared the computational expense of determining the optimal controls for the single support phase of gait using a conventional serial machine (SGI Iris 4D25), a MIMD parallel machine (Intel iPSC/860), and a parallel-vector-processing machine (Cray Y-MP 8/864). With the human body modeled as a 14 degree-of-freedom linkage actuated by 46 musculotendinous units, computation of the optimal controls for gait could take up to 3 months of CPU time on the Iris. Both the Cray and the Intel are able to reduce this time to practical levels. The optimal solution for gait can be found with about 77 hours of CPU on the Cray and with about 88 hours of CPU on the Intel. Although the overall speeds of the Cray and the Intel were found to be similar, the unique capabilities of each machine are better suited to different portions of the computational algorithm used. The Intel was best suited to computing the derivatives of the performance criterion and the constraints whereas the Cray was best suited to parameter optimization of the controls. These results suggest that the ideal computer architecture for solving very large-scale optimal control problems is a hybrid system in which a vector-processing machine is integrated into the communication network of a MIMD parallel machine.

Parallel and serial computing tools for testing single-locus and epistatic SNP effects of quantitative traits in genome-wide association studies

PubMed Central

Ma, Li; Runesha, H Birali; Dvorkin, Daniel; Garbe, John R; Da, Yang

2008-01-01

Background Genome-wide association studies (GWAS) using single nucleotide polymorphism (SNP) markers provide opportunities to detect epistatic SNPs associated with quantitative traits and to detect the exact mode of an epistasis effect. Computational difficulty is the main bottleneck for epistasis testing in large scale GWAS. Results The EPISNPmpi and EPISNP computer programs were developed for testing single-locus and epistatic SNP effects on quantitative traits in GWAS, including tests of three single-locus effects for each SNP (SNP genotypic effect, additive and dominance effects) and five epistasis effects for each pair of SNPs (two-locus interaction, additive × additive, additive × dominance, dominance × additive, and dominance × dominance) based on the extended Kempthorne model. EPISNPmpi is the parallel computing program for epistasis testing in large scale GWAS and achieved excellent scalability for large scale analysis and portability for various parallel computing platforms. EPISNP is the serial computing program based on the EPISNPmpi code for epistasis testing in small scale GWAS using commonly available operating systems and computer hardware. Three serial computing utility programs were developed for graphical viewing of test results and epistasis networks, and for estimating CPU time and disk space requirements. Conclusion The EPISNPmpi parallel computing program provides an effective computing tool for epistasis testing in large scale GWAS, and the epiSNP serial computing programs are convenient tools for epistasis analysis in small scale GWAS using commonly available computer hardware. PMID:18644146

Exploring the Ability of a Coarse-grained Potential to Describe the Stress-strain Response of Glassy Polystyrene

DTIC Science & Technology

2012-10-01

using the open-source code Large-scale Atomic/Molecular Massively Parallel Simulator ( LAMMPS ) (http://lammps.sandia.gov) (23). The commercial...parameters are proprietary and cannot be ported to the LAMMPS 4 simulation code. In our molecular dynamics simulations at the atomistic resolution, we...IBI iterative Boltzmann inversion LAMMPS Large-scale Atomic/Molecular Massively Parallel Simulator MAPS Materials Processes and Simulations MS

Sirocco Storage Server v. pre-alpha 0.1

DOE Office of Scientific and Technical Information (OSTI.GOV)

Curry, Matthew L.; Danielson, Geoffrey; Ward, H. Lee

Sirocco is a parallel storage system under development, designed for write-intensive workloads on large-scale HPC platforms. It implements a keyvalue object store on top of a set of loosely federated storage servers that cooperate to ensure data integrity and performance. It includes support for a range of different types of storage transactions. This software release constitutes a conformant storage server, along with the client-side libraries to access the storage over a network.

Visual analysis of inter-process communication for large-scale parallel computing.

PubMed

Muelder, Chris; Gygi, Francois; Ma, Kwan-Liu

2009-01-01

In serial computation, program profiling is often helpful for optimization of key sections of code. When moving to parallel computation, not only does the code execution need to be considered but also communication between the different processes which can induce delays that are detrimental to performance. As the number of processes increases, so does the impact of the communication delays on performance. For large-scale parallel applications, it is critical to understand how the communication impacts performance in order to make the code more efficient. There are several tools available for visualizing program execution and communications on parallel systems. These tools generally provide either views which statistically summarize the entire program execution or process-centric views. However, process-centric visualizations do not scale well as the number of processes gets very large. In particular, the most common representation of parallel processes is a Gantt char t with a row for each process. As the number of processes increases, these charts can become difficult to work with and can even exceed screen resolution. We propose a new visualization approach that affords more scalability and then demonstrate it on systems running with up to 16,384 processes.

Xyce Parallel Electronic Simulator : users' guide, version 2.0.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hoekstra, Robert John; Waters, Lon J.; Rankin, Eric Lamont

2004-06-01

This manual describes the use of the Xyce Parallel Electronic Simulator. Xyce has been designed as a SPICE-compatible, high-performance analog circuit simulator capable of simulating electrical circuits at a variety of abstraction levels. Primarily, Xyce has been written to support the simulation needs of the Sandia National Laboratories electrical designers. This development has focused on improving capability the current state-of-the-art in the following areas: {sm_bullet} Capability to solve extremely large circuit problems by supporting large-scale parallel computing platforms (up to thousands of processors). Note that this includes support for most popular parallel and serial computers. {sm_bullet} Improved performance for allmore » numerical kernels (e.g., time integrator, nonlinear and linear solvers) through state-of-the-art algorithms and novel techniques. {sm_bullet} Device models which are specifically tailored to meet Sandia's needs, including many radiation-aware devices. {sm_bullet} A client-server or multi-tiered operating model wherein the numerical kernel can operate independently of the graphical user interface (GUI). {sm_bullet} Object-oriented code design and implementation using modern coding practices that ensure that the Xyce Parallel Electronic Simulator will be maintainable and extensible far into the future. Xyce is a parallel code in the most general sense of the phrase - a message passing of computing platforms. These include serial, shared-memory and distributed-memory parallel implementation - which allows it to run efficiently on the widest possible number parallel as well as heterogeneous platforms. Careful attention has been paid to the specific nature of circuit-simulation problems to ensure that optimal parallel efficiency is achieved as the number of processors grows. One feature required by designers is the ability to add device models, many specific to the needs of Sandia, to the code. To this end, the device package in the Xyce These input formats include standard analytical models, behavioral models look-up Parallel Electronic Simulator is designed to support a variety of device model inputs. tables, and mesh-level PDE device models. Combined with this flexible interface is an architectural design that greatly simplifies the addition of circuit models. One of the most important feature of Xyce is in providing a platform for computational research and development aimed specifically at the needs of the Laboratory. With Xyce, Sandia now has an 'in-house' capability with which both new electrical (e.g., device model development) and algorithmic (e.g., faster time-integration methods) research and development can be performed. Ultimately, these capabilities are migrated to end users.« less

Kinetic Simulations of the Interruption of Large-Amplitude Shear-Alfvén Waves in a High- β Plasma

DOE PAGES

Squire, J.; Kunz, M. W.; Quataert, E.; ...

2017-10-12

Using two-dimensional hybrid-kinetic simulations, we explore the nonlinear “interruption” of standing and traveling shear-Alfvén waves in collisionless plasmas. Interruption involves a self-generated pressure anisotropy removing the restoring force of a linearly polarized Alfvénic perturbation, and occurs for wave amplitudes δB ⊥/B 0≳β –1/2 (where β is the ratio of thermal to magnetic pressure). We use highly elongated domains to obtain maximal scale separation between the wave and the ion gyroscale. For standing waves above the amplitude limit, we find that the large-scale magnetic field of the wave decays rapidly. The dynamics are strongly affected by the excitation of oblique firehosemore » modes, which transition into long-lived parallel fluctuations at the ion gyroscale and cause significant particle scattering. Traveling waves are damped more slowly, but are also influenced by small-scale parallel fluctuations created by the decay of firehose modes. Our results demonstrate that collisionless plasmas cannot support linearly polarized Alfvén waves above δB ⊥/B 0~β –1/2. Here, they also provide a vivid illustration of two key aspects of low-collisionality plasma dynamics: (i) the importance of velocity-space instabilities in regulating plasma dynamics at high β, and (ii) how nonlinear collisionless processes can transfer mechanical energy directly from the largest scales into thermal energy and microscale fluctuations, without the need for a scale-by-scale turbulent cascade.« less

Kinetic Simulations of the Interruption of Large-Amplitude Shear-Alfvén Waves in a High- β Plasma

DOE Office of Scientific and Technical Information (OSTI.GOV)

Squire, J.; Kunz, M. W.; Quataert, E.

Using two-dimensional hybrid-kinetic simulations, we explore the nonlinear “interruption” of standing and traveling shear-Alfvén waves in collisionless plasmas. Interruption involves a self-generated pressure anisotropy removing the restoring force of a linearly polarized Alfvénic perturbation, and occurs for wave amplitudes δB ⊥/B 0≳β –1/2 (where β is the ratio of thermal to magnetic pressure). We use highly elongated domains to obtain maximal scale separation between the wave and the ion gyroscale. For standing waves above the amplitude limit, we find that the large-scale magnetic field of the wave decays rapidly. The dynamics are strongly affected by the excitation of oblique firehosemore » modes, which transition into long-lived parallel fluctuations at the ion gyroscale and cause significant particle scattering. Traveling waves are damped more slowly, but are also influenced by small-scale parallel fluctuations created by the decay of firehose modes. Our results demonstrate that collisionless plasmas cannot support linearly polarized Alfvén waves above δB ⊥/B 0~β –1/2. Here, they also provide a vivid illustration of two key aspects of low-collisionality plasma dynamics: (i) the importance of velocity-space instabilities in regulating plasma dynamics at high β, and (ii) how nonlinear collisionless processes can transfer mechanical energy directly from the largest scales into thermal energy and microscale fluctuations, without the need for a scale-by-scale turbulent cascade.« less

Leveraging human oversight and intervention in large-scale parallel processing of open-source data

NASA Astrophysics Data System (ADS)

Casini, Enrico; Suri, Niranjan; Bradshaw, Jeffrey M.

2015-05-01

The popularity of cloud computing along with the increased availability of cheap storage have led to the necessity of elaboration and transformation of large volumes of open-source data, all in parallel. One way to handle such extensive volumes of information properly is to take advantage of distributed computing frameworks like Map-Reduce. Unfortunately, an entirely automated approach that excludes human intervention is often unpredictable and error prone. Highly accurate data processing and decision-making can be achieved by supporting an automatic process through human collaboration, in a variety of environments such as warfare, cyber security and threat monitoring. Although this mutual participation seems easily exploitable, human-machine collaboration in the field of data analysis presents several challenges. First, due to the asynchronous nature of human intervention, it is necessary to verify that once a correction is made, all the necessary reprocessing is done in chain. Second, it is often needed to minimize the amount of reprocessing in order to optimize the usage of resources due to limited availability. In order to improve on these strict requirements, this paper introduces improvements to an innovative approach for human-machine collaboration in the processing of large amounts of open-source data in parallel.

Parameter estimation in large-scale systems biology models: a parallel and self-adaptive cooperative strategy.

PubMed

Penas, David R; González, Patricia; Egea, Jose A; Doallo, Ramón; Banga, Julio R

2017-01-21

The development of large-scale kinetic models is one of the current key issues in computational systems biology and bioinformatics. Here we consider the problem of parameter estimation in nonlinear dynamic models. Global optimization methods can be used to solve this type of problems but the associated computational cost is very large. Moreover, many of these methods need the tuning of a number of adjustable search parameters, requiring a number of initial exploratory runs and therefore further increasing the computation times. Here we present a novel parallel method, self-adaptive cooperative enhanced scatter search (saCeSS), to accelerate the solution of this class of problems. The method is based on the scatter search optimization metaheuristic and incorporates several key new mechanisms: (i) asynchronous cooperation between parallel processes, (ii) coarse and fine-grained parallelism, and (iii) self-tuning strategies. The performance and robustness of saCeSS is illustrated by solving a set of challenging parameter estimation problems, including medium and large-scale kinetic models of the bacterium E. coli, bakerés yeast S. cerevisiae, the vinegar fly D. melanogaster, Chinese Hamster Ovary cells, and a generic signal transduction network. The results consistently show that saCeSS is a robust and efficient method, allowing very significant reduction of computation times with respect to several previous state of the art methods (from days to minutes, in several cases) even when only a small number of processors is used. The new parallel cooperative method presented here allows the solution of medium and large scale parameter estimation problems in reasonable computation times and with small hardware requirements. Further, the method includes self-tuning mechanisms which facilitate its use by non-experts. We believe that this new method can play a key role in the development of large-scale and even whole-cell dynamic models.

SQDFT: Spectral Quadrature method for large-scale parallel O(N) Kohn-Sham calculations at high temperature

NASA Astrophysics Data System (ADS)

Suryanarayana, Phanish; Pratapa, Phanisri P.; Sharma, Abhiraj; Pask, John E.

2018-03-01

We present SQDFT: a large-scale parallel implementation of the Spectral Quadrature (SQ) method for O(N) Kohn-Sham Density Functional Theory (DFT) calculations at high temperature. Specifically, we develop an efficient and scalable finite-difference implementation of the infinite-cell Clenshaw-Curtis SQ approach, in which results for the infinite crystal are obtained by expressing quantities of interest as bilinear forms or sums of bilinear forms, that are then approximated by spatially localized Clenshaw-Curtis quadrature rules. We demonstrate the accuracy of SQDFT by showing systematic convergence of energies and atomic forces with respect to SQ parameters to reference diagonalization results, and convergence with discretization to established planewave results, for both metallic and insulating systems. We further demonstrate that SQDFT achieves excellent strong and weak parallel scaling on computer systems consisting of tens of thousands of processors, with near perfect O(N) scaling with system size and wall times as low as a few seconds per self-consistent field iteration. Finally, we verify the accuracy of SQDFT in large-scale quantum molecular dynamics simulations of aluminum at high temperature.

Implementing Parquet equations using HPX

NASA Astrophysics Data System (ADS)

Kellar, Samuel; Wagle, Bibek; Yang, Shuxiang; Tam, Ka-Ming; Kaiser, Hartmut; Moreno, Juana; Jarrell, Mark

A new C++ runtime system (HPX) enables simulations of complex systems to run more efficiently on parallel and heterogeneous systems. This increased efficiency allows for solutions to larger simulations of the parquet approximation for a system with impurities. The relevancy of the parquet equations depends upon the ability to solve systems which require long runs and large amounts of memory. These limitations, in addition to numerical complications arising from stability of the solutions, necessitate running on large distributed systems. As the computational resources trend towards the exascale and the limitations arising from computational resources vanish efficiency of large scale simulations becomes a focus. HPX facilitates efficient simulations through intelligent overlapping of computation and communication. Simulations such as the parquet equations which require the transfer of large amounts of data should benefit from HPX implementations. Supported by the the NSF EPSCoR Cooperative Agreement No. EPS-1003897 with additional support from the Louisiana Board of Regents.

Camphor-Enabled Transfer and Mechanical Testing of Centimeter-Scale Ultrathin Films.

PubMed

Wang, Bin; Luo, Da; Li, Zhancheng; Kwon, Youngwoo; Wang, Meihui; Goo, Min; Jin, Sunghwan; Huang, Ming; Shen, Yongtao; Shi, Haofei; Ding, Feng; Ruoff, Rodney S

2018-05-21

Camphor is used to transfer centimeter-scale ultrathin films onto custom-designed substrates for mechanical (tensile) testing. Compared to traditional transfer methods using dissolving/peeling to remove the support-layers, camphor is sublimed away in air at low temperature, thereby avoiding additional stress on the as-transferred films. Large-area ultrathin films can be transferred onto hollow substrates without damage by this method. Tensile measurements are made on centimeter-scale 300 nm-thick graphene oxide film specimens, much thinner than the ≈2 μm minimum thickness of macroscale graphene-oxide films previously reported. Tensile tests were also done on two different types of large-area samples of adlayer free CVD-grown single-layer graphene supported by a ≈100 nm thick polycarbonate film; graphene stiffens this sample significantly, thus the intrinsic mechanical response of the graphene can be extracted. This is the first tensile measurement of centimeter-scale monolayer graphene films. The Young's modulus of polycrystalline graphene ranges from 637 to 793 GPa, while for near single-crystal graphene, it ranges from 728 to 908 GPa (folds parallel to the tensile loading direction) and from 683 to 775 GPa (folds orthogonal to the tensile loading direction), demonstrating the mechanical performance of large-area graphene in a size scale relevant to many applications. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Lessons Learned in Deploying the World s Largest Scale Lustre File System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dillow, David A; Fuller, Douglas; Wang, Feiyi

2010-01-01

The Spider system at the Oak Ridge National Laboratory's Leadership Computing Facility (OLCF) is the world's largest scale Lustre parallel file system. Envisioned as a shared parallel file system capable of delivering both the bandwidth and capacity requirements of the OLCF's diverse computational environment, the project had a number of ambitious goals. To support the workloads of the OLCF's diverse computational platforms, the aggregate performance and storage capacity of Spider exceed that of our previously deployed systems by a factor of 6x - 240 GB/sec, and 17x - 10 Petabytes, respectively. Furthermore, Spider supports over 26,000 clients concurrently accessing themore » file system, which exceeds our previously deployed systems by nearly 4x. In addition to these scalability challenges, moving to a center-wide shared file system required dramatically improved resiliency and fault-tolerance mechanisms. This paper details our efforts in designing, deploying, and operating Spider. Through a phased approach of research and development, prototyping, deployment, and transition to operations, this work has resulted in a number of insights into large-scale parallel file system architectures, from both the design and the operational perspectives. We present in this paper our solutions to issues such as network congestion, performance baselining and evaluation, file system journaling overheads, and high availability in a system with tens of thousands of components. We also discuss areas of continued challenges, such as stressed metadata performance and the need for file system quality of service alongside with our efforts to address them. Finally, operational aspects of managing a system of this scale are discussed along with real-world data and observations.« less

Portable parallel stochastic optimization for the design of aeropropulsion components

NASA Technical Reports Server (NTRS)

Sues, Robert H.; Rhodes, G. S.

1994-01-01

This report presents the results of Phase 1 research to develop a methodology for performing large-scale Multi-disciplinary Stochastic Optimization (MSO) for the design of aerospace systems ranging from aeropropulsion components to complete aircraft configurations. The current research recognizes that such design optimization problems are computationally expensive, and require the use of either massively parallel or multiple-processor computers. The methodology also recognizes that many operational and performance parameters are uncertain, and that uncertainty must be considered explicitly to achieve optimum performance and cost. The objective of this Phase 1 research was to initialize the development of an MSO methodology that is portable to a wide variety of hardware platforms, while achieving efficient, large-scale parallelism when multiple processors are available. The first effort in the project was a literature review of available computer hardware, as well as review of portable, parallel programming environments. The first effort was to implement the MSO methodology for a problem using the portable parallel programming language, Parallel Virtual Machine (PVM). The third and final effort was to demonstrate the example on a variety of computers, including a distributed-memory multiprocessor, a distributed-memory network of workstations, and a single-processor workstation. Results indicate the MSO methodology can be well-applied towards large-scale aerospace design problems. Nearly perfect linear speedup was demonstrated for computation of optimization sensitivity coefficients on both a 128-node distributed-memory multiprocessor (the Intel iPSC/860) and a network of workstations (speedups of almost 19 times achieved for 20 workstations). Very high parallel efficiencies (75 percent for 31 processors and 60 percent for 50 processors) were also achieved for computation of aerodynamic influence coefficients on the Intel. Finally, the multi-level parallelization strategy that will be needed for large-scale MSO problems was demonstrated to be highly efficient. The same parallel code instructions were used on both platforms, demonstrating portability. There are many applications for which MSO can be applied, including NASA's High-Speed-Civil Transport, and advanced propulsion systems. The use of MSO will reduce design and development time and testing costs dramatically.

Performance Characterization of Global Address Space Applications: A Case Study with NWChem

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hammond, Jeffrey R.; Krishnamoorthy, Sriram; Shende, Sameer

The use of global address space languages and one-sided communication for complex applications is gaining attention in the parallel computing community. However, lack of good evaluative methods to observe multiple levels of performance makes it difficult to isolate the cause of performance deficiencies and to understand the fundamental limitations of system and application design for future improvement. NWChem is a popular computational chemistry package which depends on the Global Arrays/ ARMCI suite for partitioned global address space functionality to deliver high-end molecular modeling capabilities. A workload characterization methodology was developed to support NWChem performance engineering on large-scale parallel platforms. Themore » research involved both the integration of performance instrumentation and measurement in the NWChem software, as well as the analysis of one-sided communication performance in the context of NWChem workloads. Scaling studies were conducted for NWChem on Blue Gene/P and on two large-scale clusters using different generation Infiniband interconnects and x86 processors. The performance analysis and results show how subtle changes in the runtime parameters related to the communication subsystem could have significant impact on performance behavior. The tool has successfully identified several algorithmic bottlenecks which are already being tackled by computational chemists to improve NWChem performance.« less

Solving Partial Differential Equations in a data-driven multiprocessor environment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gaudiot, J.L.; Lin, C.M.; Hosseiniyar, M.

1988-12-31

Partial differential equations can be found in a host of engineering and scientific problems. The emergence of new parallel architectures has spurred research in the definition of parallel PDE solvers. Concurrently, highly programmable systems such as data-how architectures have been proposed for the exploitation of large scale parallelism. The implementation of some Partial Differential Equation solvers (such as the Jacobi method) on a tagged token data-flow graph is demonstrated here. Asynchronous methods (chaotic relaxation) are studied and new scheduling approaches (the Token No-Labeling scheme) are introduced in order to support the implementation of the asychronous methods in a data-driven environment.more » New high-level data-flow language program constructs are introduced in order to handle chaotic operations. Finally, the performance of the program graphs is demonstrated by a deterministic simulation of a message passing data-flow multiprocessor. An analysis of the overhead in the data-flow graphs is undertaken to demonstrate the limits of parallel operations in dataflow PDE program graphs.« less

Simulation framework for intelligent transportation systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ewing, T.; Doss, E.; Hanebutte, U.

1996-10-01

A simulation framework has been developed for a large-scale, comprehensive, scaleable simulation of an Intelligent Transportation System (ITS). The simulator is designed for running on parallel computers and distributed (networked) computer systems, but can run on standalone workstations for smaller simulations. The simulator currently models instrumented smart vehicles with in-vehicle navigation units capable of optimal route planning and Traffic Management Centers (TMC). The TMC has probe vehicle tracking capabilities (display position and attributes of instrumented vehicles), and can provide two-way interaction with traffic to provide advisories and link times. Both the in-vehicle navigation module and the TMC feature detailed graphicalmore » user interfaces to support human-factors studies. Realistic modeling of variations of the posted driving speed are based on human factors studies that take into consideration weather, road conditions, driver personality and behavior, and vehicle type. The prototype has been developed on a distributed system of networked UNIX computers but is designed to run on parallel computers, such as ANL`s IBM SP-2, for large-scale problems. A novel feature of the approach is that vehicles are represented by autonomous computer processes which exchange messages with other processes. The vehicles have a behavior model which governs route selection and driving behavior, and can react to external traffic events much like real vehicles. With this approach, the simulation is scaleable to take advantage of emerging massively parallel processor (MPP) systems.« less

High performance computing and communications: Advancing the frontiers of information technology

DOE Office of Scientific and Technical Information (OSTI.GOV)

NONE

1997-12-31

This report, which supplements the President`s Fiscal Year 1997 Budget, describes the interagency High Performance Computing and Communications (HPCC) Program. The HPCC Program will celebrate its fifth anniversary in October 1996 with an impressive array of accomplishments to its credit. Over its five-year history, the HPCC Program has focused on developing high performance computing and communications technologies that can be applied to computation-intensive applications. Major highlights for FY 1996: (1) High performance computing systems enable practical solutions to complex problems with accuracies not possible five years ago; (2) HPCC-funded research in very large scale networking techniques has been instrumental inmore » the evolution of the Internet, which continues exponential growth in size, speed, and availability of information; (3) The combination of hardware capability measured in gigaflop/s, networking technology measured in gigabit/s, and new computational science techniques for modeling phenomena has demonstrated that very large scale accurate scientific calculations can be executed across heterogeneous parallel processing systems located thousands of miles apart; (4) Federal investments in HPCC software R and D support researchers who pioneered the development of parallel languages and compilers, high performance mathematical, engineering, and scientific libraries, and software tools--technologies that allow scientists to use powerful parallel systems to focus on Federal agency mission applications; and (5) HPCC support for virtual environments has enabled the development of immersive technologies, where researchers can explore and manipulate multi-dimensional scientific and engineering problems. Educational programs fostered by the HPCC Program have brought into classrooms new science and engineering curricula designed to teach computational science. This document contains a small sample of the significant HPCC Program accomplishments in FY 1996.« less

Linear static structural and vibration analysis on high-performance computers

NASA Technical Reports Server (NTRS)

Baddourah, M. A.; Storaasli, O. O.; Bostic, S. W.

1993-01-01

Parallel computers offer the oppurtunity to significantly reduce the computation time necessary to analyze large-scale aerospace structures. This paper presents algorithms developed for and implemented on massively-parallel computers hereafter referred to as Scalable High-Performance Computers (SHPC), for the most computationally intensive tasks involved in structural analysis, namely, generation and assembly of system matrices, solution of systems of equations and calculation of the eigenvalues and eigenvectors. Results on SHPC are presented for large-scale structural problems (i.e. models for High-Speed Civil Transport). The goal of this research is to develop a new, efficient technique which extends structural analysis to SHPC and makes large-scale structural analyses tractable.

Displacement and deformation measurement for large structures by camera network

NASA Astrophysics Data System (ADS)

Shang, Yang; Yu, Qifeng; Yang, Zhen; Xu, Zhiqiang; Zhang, Xiaohu

2014-03-01

A displacement and deformation measurement method for large structures by a series-parallel connection camera network is presented. By taking the dynamic monitoring of a large-scale crane in lifting operation as an example, a series-parallel connection camera network is designed, and the displacement and deformation measurement method by using this series-parallel connection camera network is studied. The movement range of the crane body is small, and that of the crane arm is large. The displacement of the crane body, the displacement of the crane arm relative to the body and the deformation of the arm are measured. Compared with a pure series or parallel connection camera network, the designed series-parallel connection camera network can be used to measure not only the movement and displacement of a large structure but also the relative movement and deformation of some interesting parts of the large structure by a relatively simple optical measurement system.

Parallel Domain Decomposition Formulation and Software for Large-Scale Sparse Symmetrical/Unsymmetrical Aeroacoustic Applications

NASA Technical Reports Server (NTRS)

Nguyen, D. T.; Watson, Willie R. (Technical Monitor)

2005-01-01

The overall objectives of this research work are to formulate and validate efficient parallel algorithms, and to efficiently design/implement computer software for solving large-scale acoustic problems, arised from the unified frameworks of the finite element procedures. The adopted parallel Finite Element (FE) Domain Decomposition (DD) procedures should fully take advantages of multiple processing capabilities offered by most modern high performance computing platforms for efficient parallel computation. To achieve this objective. the formulation needs to integrate efficient sparse (and dense) assembly techniques, hybrid (or mixed) direct and iterative equation solvers, proper pre-conditioned strategies, unrolling strategies, and effective processors' communicating schemes. Finally, the numerical performance of the developed parallel finite element procedures will be evaluated by solving series of structural, and acoustic (symmetrical and un-symmetrical) problems (in different computing platforms). Comparisons with existing "commercialized" and/or "public domain" software are also included, whenever possible.

Paradigms and strategies for scientific computing on distributed memory concurrent computers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Foster, I.T.; Walker, D.W.

1994-06-01

In this work we examine recent advances in parallel languages and abstractions that have the potential for improving the programmability and maintainability of large-scale, parallel, scientific applications running on high performance architectures and networks. This paper focuses on Fortran M, a set of extensions to Fortran 77 that supports the modular design of message-passing programs. We describe the Fortran M implementation of a particle-in-cell (PIC) plasma simulation application, and discuss issues in the optimization of the code. The use of two other methodologies for parallelizing the PIC application are considered. The first is based on the shared object abstraction asmore » embodied in the Orca language. The second approach is the Split-C language. In Fortran M, Orca, and Split-C the ability of the programmer to control the granularity of communication is important is designing an efficient implementation.« less

Accelerating large-scale protein structure alignments with graphics processing units

PubMed Central

2012-01-01

Background Large-scale protein structure alignment, an indispensable tool to structural bioinformatics, poses a tremendous challenge on computational resources. To ensure structure alignment accuracy and efficiency, efforts have been made to parallelize traditional alignment algorithms in grid environments. However, these solutions are costly and of limited accessibility. Others trade alignment quality for speedup by using high-level characteristics of structure fragments for structure comparisons. Findings We present ppsAlign, a parallel protein structure Alignment framework designed and optimized to exploit the parallelism of Graphics Processing Units (GPUs). As a general-purpose GPU platform, ppsAlign could take many concurrent methods, such as TM-align and Fr-TM-align, into the parallelized algorithm design. We evaluated ppsAlign on an NVIDIA Tesla C2050 GPU card, and compared it with existing software solutions running on an AMD dual-core CPU. We observed a 36-fold speedup over TM-align, a 65-fold speedup over Fr-TM-align, and a 40-fold speedup over MAMMOTH. Conclusions ppsAlign is a high-performance protein structure alignment tool designed to tackle the computational complexity issues from protein structural data. The solution presented in this paper allows large-scale structure comparisons to be performed using massive parallel computing power of GPU. PMID:22357132

Design Aspects of the Rayleigh Convection Code

NASA Astrophysics Data System (ADS)

Featherstone, N. A.

2017-12-01

Understanding the long-term generation of planetary or stellar magnetic field requires complementary knowledge of the large-scale fluid dynamics pervading large fractions of the object's interior. Such large-scale motions are sensitive to the system's geometry which, in planets and stars, is spherical to a good approximation. As a result, computational models designed to study such systems often solve the MHD equations in spherical geometry, frequently employing a spectral approach involving spherical harmonics. We present computational and user-interface design aspects of one such modeling tool, the Rayleigh convection code, which is suitable for deployment on desktop and petascale-hpc architectures alike. In this poster, we will present an overview of this code's parallel design and its built-in diagnostics-output package. Rayleigh has been developed with NSF support through the Computational Infrastructure for Geodynamics and is expected to be released as open-source software in winter 2017/2018.

Multi-thread parallel algorithm for reconstructing 3D large-scale porous structures

NASA Astrophysics Data System (ADS)

Ju, Yang; Huang, Yaohui; Zheng, Jiangtao; Qian, Xu; Xie, Heping; Zhao, Xi

2017-04-01

Geomaterials inherently contain many discontinuous, multi-scale, geometrically irregular pores, forming a complex porous structure that governs their mechanical and transport properties. The development of an efficient reconstruction method for representing porous structures can significantly contribute toward providing a better understanding of the governing effects of porous structures on the properties of porous materials. In order to improve the efficiency of reconstructing large-scale porous structures, a multi-thread parallel scheme was incorporated into the simulated annealing reconstruction method. In the method, four correlation functions, which include the two-point probability function, the linear-path functions for the pore phase and the solid phase, and the fractal system function for the solid phase, were employed for better reproduction of the complex well-connected porous structures. In addition, a random sphere packing method and a self-developed pre-conditioning method were incorporated to cast the initial reconstructed model and select independent interchanging pairs for parallel multi-thread calculation, respectively. The accuracy of the proposed algorithm was evaluated by examining the similarity between the reconstructed structure and a prototype in terms of their geometrical, topological, and mechanical properties. Comparisons of the reconstruction efficiency of porous models with various scales indicated that the parallel multi-thread scheme significantly shortened the execution time for reconstruction of a large-scale well-connected porous model compared to a sequential single-thread procedure.

GROMACS 4.5: a high-throughput and highly parallel open source molecular simulation toolkit

PubMed Central

Pronk, Sander; Páll, Szilárd; Schulz, Roland; Larsson, Per; Bjelkmar, Pär; Apostolov, Rossen; Shirts, Michael R.; Smith, Jeremy C.; Kasson, Peter M.; van der Spoel, David; Hess, Berk; Lindahl, Erik

2013-01-01

Motivation: Molecular simulation has historically been a low-throughput technique, but faster computers and increasing amounts of genomic and structural data are changing this by enabling large-scale automated simulation of, for instance, many conformers or mutants of biomolecules with or without a range of ligands. At the same time, advances in performance and scaling now make it possible to model complex biomolecular interaction and function in a manner directly testable by experiment. These applications share a need for fast and efficient software that can be deployed on massive scale in clusters, web servers, distributed computing or cloud resources. Results: Here, we present a range of new simulation algorithms and features developed during the past 4 years, leading up to the GROMACS 4.5 software package. The software now automatically handles wide classes of biomolecules, such as proteins, nucleic acids and lipids, and comes with all commonly used force fields for these molecules built-in. GROMACS supports several implicit solvent models, as well as new free-energy algorithms, and the software now uses multithreading for efficient parallelization even on low-end systems, including windows-based workstations. Together with hand-tuned assembly kernels and state-of-the-art parallelization, this provides extremely high performance and cost efficiency for high-throughput as well as massively parallel simulations. Availability: GROMACS is an open source and free software available from http://www.gromacs.org. Contact: erik.lindahl@scilifelab.se Supplementary information: Supplementary data are available at Bioinformatics online. PMID:23407358

Streaming parallel GPU acceleration of large-scale filter-based spiking neural networks.

PubMed

Slażyński, Leszek; Bohte, Sander

2012-01-01

The arrival of graphics processing (GPU) cards suitable for massively parallel computing promises affordable large-scale neural network simulation previously only available at supercomputing facilities. While the raw numbers suggest that GPUs may outperform CPUs by at least an order of magnitude, the challenge is to develop fine-grained parallel algorithms to fully exploit the particulars of GPUs. Computation in a neural network is inherently parallel and thus a natural match for GPU architectures: given inputs, the internal state for each neuron can be updated in parallel. We show that for filter-based spiking neurons, like the Spike Response Model, the additive nature of membrane potential dynamics enables additional update parallelism. This also reduces the accumulation of numerical errors when using single precision computation, the native precision of GPUs. We further show that optimizing simulation algorithms and data structures to the GPU's architecture has a large pay-off: for example, matching iterative neural updating to the memory architecture of the GPU speeds up this simulation step by a factor of three to five. With such optimizations, we can simulate in better-than-realtime plausible spiking neural networks of up to 50 000 neurons, processing over 35 million spiking events per second.

Implementation of highly parallel and large scale GW calculations within the OpenAtom software

NASA Astrophysics Data System (ADS)

Ismail-Beigi, Sohrab

The need to describe electronic excitations with better accuracy than provided by band structures produced by Density Functional Theory (DFT) has been a long-term enterprise for the computational condensed matter and materials theory communities. In some cases, appropriate theoretical frameworks have existed for some time but have been difficult to apply widely due to computational cost. For example, the GW approximation incorporates a great deal of important non-local and dynamical electronic interaction effects but has been too computationally expensive for routine use in large materials simulations. OpenAtom is an open source massively parallel ab initiodensity functional software package based on plane waves and pseudopotentials (http://charm.cs.uiuc.edu/OpenAtom/) that takes advantage of the Charm + + parallel framework. At present, it is developed via a three-way collaboration, funded by an NSF SI2-SSI grant (ACI-1339804), between Yale (Ismail-Beigi), IBM T. J. Watson (Glenn Martyna) and the University of Illinois at Urbana Champaign (Laxmikant Kale). We will describe the project and our current approach towards implementing large scale GW calculations with OpenAtom. Potential applications of large scale parallel GW software for problems involving electronic excitations in semiconductor and/or metal oxide systems will be also be pointed out.

SQDFT: Spectral Quadrature method for large-scale parallel O ( N ) Kohn–Sham calculations at high temperature

DOE Office of Scientific and Technical Information (OSTI.GOV)

Suryanarayana, Phanish; Pratapa, Phanisri P.; Sharma, Abhiraj

We present SQDFT: a large-scale parallel implementation of the Spectral Quadrature (SQ) method formore » $$\\mathscr{O}(N)$$ Kohn–Sham Density Functional Theory (DFT) calculations at high temperature. Specifically, we develop an efficient and scalable finite-difference implementation of the infinite-cell Clenshaw–Curtis SQ approach, in which results for the infinite crystal are obtained by expressing quantities of interest as bilinear forms or sums of bilinear forms, that are then approximated by spatially localized Clenshaw–Curtis quadrature rules. We demonstrate the accuracy of SQDFT by showing systematic convergence of energies and atomic forces with respect to SQ parameters to reference diagonalization results, and convergence with discretization to established planewave results, for both metallic and insulating systems. Here, we further demonstrate that SQDFT achieves excellent strong and weak parallel scaling on computer systems consisting of tens of thousands of processors, with near perfect $$\\mathscr{O}(N)$$ scaling with system size and wall times as low as a few seconds per self-consistent field iteration. Finally, we verify the accuracy of SQDFT in large-scale quantum molecular dynamics simulations of aluminum at high temperature.« less

SQDFT: Spectral Quadrature method for large-scale parallel O ( N ) Kohn–Sham calculations at high temperature

DOE PAGES

Suryanarayana, Phanish; Pratapa, Phanisri P.; Sharma, Abhiraj; ...

2017-12-07

We present SQDFT: a large-scale parallel implementation of the Spectral Quadrature (SQ) method formore » $$\\mathscr{O}(N)$$ Kohn–Sham Density Functional Theory (DFT) calculations at high temperature. Specifically, we develop an efficient and scalable finite-difference implementation of the infinite-cell Clenshaw–Curtis SQ approach, in which results for the infinite crystal are obtained by expressing quantities of interest as bilinear forms or sums of bilinear forms, that are then approximated by spatially localized Clenshaw–Curtis quadrature rules. We demonstrate the accuracy of SQDFT by showing systematic convergence of energies and atomic forces with respect to SQ parameters to reference diagonalization results, and convergence with discretization to established planewave results, for both metallic and insulating systems. Here, we further demonstrate that SQDFT achieves excellent strong and weak parallel scaling on computer systems consisting of tens of thousands of processors, with near perfect $$\\mathscr{O}(N)$$ scaling with system size and wall times as low as a few seconds per self-consistent field iteration. Finally, we verify the accuracy of SQDFT in large-scale quantum molecular dynamics simulations of aluminum at high temperature.« less

Reaction Force of Micro-scale Liquid Droplets Constrained Between Parallel Plates through CFD

NASA Astrophysics Data System (ADS)

Free, Robert; Hekiri, Haider; Hawa, Takumi

2012-02-01

Micro-scale liquid droplets responding to depression between parallel plates are investigated analytically and numerically. The functional dependence of the reaction force accrued in such droplets on droplet size, surface tension, depression amount, and contact angle is explored. For both the 2D and 3D case, an analytical model is developed based on first principles. Computational fluid dynamics is then utilized to evaluate the validity of these models. The reaction force is highly nonlinear, initially increasing very slowly with increasing depression of the droplet, but eventually moving asymptotically to infinity. The force scales linearly with both the droplet free radius and surface tension of the liquid, but has a much more complicated dependence on the contact angle and depression. Explicit expressions for the reaction force have been determined, showing these dependencies. The 3D model has been largely supported by the CFD results. It very accurately predicts the reaction force on the upper plate as the droplet is crushed, accounting for the effect of contact angle, surface tension, and droplet size.

Grid-Enabled Quantitative Analysis of Breast Cancer

DTIC Science & Technology

2009-10-01

large-scale, multi-modality computerized image analysis . The central hypothesis of this research is that large-scale image analysis for breast cancer...pilot study to utilize large scale parallel Grid computing to harness the nationwide cluster infrastructure for optimization of medical image ... analysis parameters. Additionally, we investigated the use of cutting edge dataanalysis/ mining techniques as applied to Ultrasound, FFDM, and DCE-MRI Breast

Developing eThread pipeline using SAGA-pilot abstraction for large-scale structural bioinformatics.

PubMed

Ragothaman, Anjani; Boddu, Sairam Chowdary; Kim, Nayong; Feinstein, Wei; Brylinski, Michal; Jha, Shantenu; Kim, Joohyun

2014-01-01

While most of computational annotation approaches are sequence-based, threading methods are becoming increasingly attractive because of predicted structural information that could uncover the underlying function. However, threading tools are generally compute-intensive and the number of protein sequences from even small genomes such as prokaryotes is large typically containing many thousands, prohibiting their application as a genome-wide structural systems biology tool. To leverage its utility, we have developed a pipeline for eThread--a meta-threading protein structure modeling tool, that can use computational resources efficiently and effectively. We employ a pilot-based approach that supports seamless data and task-level parallelism and manages large variation in workload and computational requirements. Our scalable pipeline is deployed on Amazon EC2 and can efficiently select resources based upon task requirements. We present runtime analysis to characterize computational complexity of eThread and EC2 infrastructure. Based on results, we suggest a pathway to an optimized solution with respect to metrics such as time-to-solution or cost-to-solution. Our eThread pipeline can scale to support a large number of sequences and is expected to be a viable solution for genome-scale structural bioinformatics and structure-based annotation, particularly, amenable for small genomes such as prokaryotes. The developed pipeline is easily extensible to other types of distributed cyberinfrastructure.

Developing eThread Pipeline Using SAGA-Pilot Abstraction for Large-Scale Structural Bioinformatics

PubMed Central

Ragothaman, Anjani; Feinstein, Wei; Jha, Shantenu; Kim, Joohyun

2014-01-01

While most of computational annotation approaches are sequence-based, threading methods are becoming increasingly attractive because of predicted structural information that could uncover the underlying function. However, threading tools are generally compute-intensive and the number of protein sequences from even small genomes such as prokaryotes is large typically containing many thousands, prohibiting their application as a genome-wide structural systems biology tool. To leverage its utility, we have developed a pipeline for eThread—a meta-threading protein structure modeling tool, that can use computational resources efficiently and effectively. We employ a pilot-based approach that supports seamless data and task-level parallelism and manages large variation in workload and computational requirements. Our scalable pipeline is deployed on Amazon EC2 and can efficiently select resources based upon task requirements. We present runtime analysis to characterize computational complexity of eThread and EC2 infrastructure. Based on results, we suggest a pathway to an optimized solution with respect to metrics such as time-to-solution or cost-to-solution. Our eThread pipeline can scale to support a large number of sequences and is expected to be a viable solution for genome-scale structural bioinformatics and structure-based annotation, particularly, amenable for small genomes such as prokaryotes. The developed pipeline is easily extensible to other types of distributed cyberinfrastructure. PMID:24995285

Characterizing parallel file-access patterns on a large-scale multiprocessor

NASA Technical Reports Server (NTRS)

Purakayastha, Apratim; Ellis, Carla Schlatter; Kotz, David; Nieuwejaar, Nils; Best, Michael

1994-01-01

Rapid increases in the computational speeds of multiprocessors have not been matched by corresponding performance enhancements in the I/O subsystem. To satisfy the large and growing I/O requirements of some parallel scientific applications, we need parallel file systems that can provide high-bandwidth and high-volume data transfer between the I/O subsystem and thousands of processors. Design of such high-performance parallel file systems depends on a thorough grasp of the expected workload. So far there have been no comprehensive usage studies of multiprocessor file systems. Our CHARISMA project intends to fill this void. The first results from our study involve an iPSC/860 at NASA Ames. This paper presents results from a different platform, the CM-5 at the National Center for Supercomputing Applications. The CHARISMA studies are unique because we collect information about every individual read and write request and about the entire mix of applications running on the machines. The results of our trace analysis lead to recommendations for parallel file system design. First the file system should support efficient concurrent access to many files, and I/O requests from many jobs under varying load conditions. Second, it must efficiently manage large files kept open for long periods. Third, it should expect to see small requests predominantly sequential access patterns, application-wide synchronous access, no concurrent file-sharing between jobs appreciable byte and block sharing between processes within jobs, and strong interprocess locality. Finally, the trace data suggest that node-level write caches and collective I/O request interfaces may be useful in certain environments.

Measurement of large parallel and perpendicular electric fields on electron spatial scales in the terrestrial bow shock.

PubMed

Bale, S D; Mozer, F S

2007-05-18

Large parallel (

A parallel form of the Gudjonsson Suggestibility Scale.

PubMed

Gudjonsson, G H

1987-09-01

The purpose of this study is twofold: (1) to present a parallel form of the Gudjonsson Suggestibility Scale (GSS, Form 1); (2) to study test-retest reliabilities of interrogative suggestibility. Three groups of subjects were administered the two suggestibility scales in a counterbalanced order. Group 1 (28 normal subjects) and Group 2 (32 'forensic' patients) completed both scales within the same testing session, whereas Group 3 (30 'forensic' patients) completed the two scales between one week and eight months apart. All the correlations were highly significant, giving support for high 'temporal consistency' of interrogative suggestibility.

OWL: A scalable Monte Carlo simulation suite for finite-temperature study of materials

NASA Astrophysics Data System (ADS)

Li, Ying Wai; Yuk, Simuck F.; Cooper, Valentino R.; Eisenbach, Markus; Odbadrakh, Khorgolkhuu

The OWL suite is a simulation package for performing large-scale Monte Carlo simulations. Its object-oriented, modular design enables it to interface with various external packages for energy evaluations. It is therefore applicable to study the finite-temperature properties for a wide range of systems: from simple classical spin models to materials where the energy is evaluated by ab initio methods. This scheme not only allows for the study of thermodynamic properties based on first-principles statistical mechanics, it also provides a means for massive, multi-level parallelism to fully exploit the capacity of modern heterogeneous computer architectures. We will demonstrate how improved strong and weak scaling is achieved by employing novel, parallel and scalable Monte Carlo algorithms, as well as the applications of OWL to a few selected frontier materials research problems. This research was supported by the Office of Science of the Department of Energy under contract DE-AC05-00OR22725.

Spectral enstrophy budget in a shear-less flow with turbulent/non-turbulent interface

NASA Astrophysics Data System (ADS)

Cimarelli, Andrea; Cocconi, Giacomo; Frohnapfel, Bettina; De Angelis, Elisabetta

2015-12-01

A numerical analysis of the interaction between decaying shear free turbulence and quiescent fluid is performed by means of global statistical budgets of enstrophy, both, at the single-point and two point levels. The single-point enstrophy budget allows us to recognize three physically relevant layers: a bulk turbulent region, an inhomogeneous turbulent layer, and an interfacial layer. Within these layers, enstrophy is produced, transferred, and finally destroyed while leading to a propagation of the turbulent front. These processes do not only depend on the position in the flow field but are also strongly scale dependent. In order to tackle this multi-dimensional behaviour of enstrophy in the space of scales and in physical space, we analyse the spectral enstrophy budget equation. The picture consists of an inviscid spatial cascade of enstrophy from large to small scales parallel to the interface moving towards the interface. At the interface, this phenomenon breaks, leaving place to an anisotropic cascade where large scale structures exhibit only a cascade process normal to the interface thus reducing their thickness while retaining their lengths parallel to the interface. The observed behaviour could be relevant for both the theoretical and the modelling approaches to flow with interacting turbulent/nonturbulent regions. The scale properties of the turbulent propagation mechanisms highlight that the inviscid turbulent transport is a large-scale phenomenon. On the contrary, the viscous diffusion, commonly associated with small scale mechanisms, highlights a much richer physics involving small lengths, normal to the interface, but at the same time large scales, parallel to the interface.

Traffic Simulations on Parallel Computers Using Domain Decomposition Techniques

DOT National Transportation Integrated Search

1995-01-01

Large scale simulations of Intelligent Transportation Systems (ITS) can only be acheived by using the computing resources offered by parallel computing architectures. Domain decomposition techniques are proposed which allow the performance of traffic...

Approximate kernel competitive learning.

PubMed

Wu, Jian-Sheng; Zheng, Wei-Shi; Lai, Jian-Huang

2015-03-01

Kernel competitive learning has been successfully used to achieve robust clustering. However, kernel competitive learning (KCL) is not scalable for large scale data processing, because (1) it has to calculate and store the full kernel matrix that is too large to be calculated and kept in the memory and (2) it cannot be computed in parallel. In this paper we develop a framework of approximate kernel competitive learning for processing large scale dataset. The proposed framework consists of two parts. First, it derives an approximate kernel competitive learning (AKCL), which learns kernel competitive learning in a subspace via sampling. We provide solid theoretical analysis on why the proposed approximation modelling would work for kernel competitive learning, and furthermore, we show that the computational complexity of AKCL is largely reduced. Second, we propose a pseudo-parallelled approximate kernel competitive learning (PAKCL) based on a set-based kernel competitive learning strategy, which overcomes the obstacle of using parallel programming in kernel competitive learning and significantly accelerates the approximate kernel competitive learning for large scale clustering. The empirical evaluation on publicly available datasets shows that the proposed AKCL and PAKCL can perform comparably as KCL, with a large reduction on computational cost. Also, the proposed methods achieve more effective clustering performance in terms of clustering precision against related approximate clustering approaches. Copyright © 2014 Elsevier Ltd. All rights reserved.

Parallel Visualization of Large-Scale Aerodynamics Calculations: A Case Study on the Cray T3E

NASA Technical Reports Server (NTRS)

Ma, Kwan-Liu; Crockett, Thomas W.

1999-01-01

This paper reports the performance of a parallel volume rendering algorithm for visualizing a large-scale, unstructured-grid dataset produced by a three-dimensional aerodynamics simulation. This dataset, containing over 18 million tetrahedra, allows us to extend our performance results to a problem which is more than 30 times larger than the one we examined previously. This high resolution dataset also allows us to see fine, three-dimensional features in the flow field. All our tests were performed on the Silicon Graphics Inc. (SGI)/Cray T3E operated by NASA's Goddard Space Flight Center. Using 511 processors, a rendering rate of almost 9 million tetrahedra/second was achieved with a parallel overhead of 26%.

The JASMIN Analysis Platform - bridging the gap between traditional climate data practicies and data-centric analysis paradigms

NASA Astrophysics Data System (ADS)

Pascoe, Stephen; Iwi, Alan; kershaw, philip; Stephens, Ag; Lawrence, Bryan

2014-05-01

The advent of large-scale data and the consequential analysis problems have led to two new challenges for the research community: how to share such data to get the maximum value and how to carry out efficient analysis. Solving both challenges require a form of parallelisation: the first is social parallelisation (involving trust and information sharing), the second data parallelisation (involving new algorithms and tools). The JASMIN infrastructure supports both kinds of parallelism by providing a multi-tennent environment with petabyte-scale storage, VM provisioning and batch cluster facilities. The JASMIN Analysis Platform (JAP) is an analysis software layer for JASMIN which emphasises ease of transition from a researcher's local environment to JASMIN. JAP brings together tools traditionally used by multiple communities and configures them to work together, enabling users to move analysis from their local environment to JASMIN without rewriting code. JAP also provides facilities to exploit JASMIN's parallel capabilities whilst maintaining their familiar analysis environment where ever possible. Modern opensource analysis tools typically have multiple dependent packages, increasing the installation burden on system administrators. When you consider a suite of tools, often with both common and conflicting dependencies, analysis pipelines can become locked to a particular installation simply because of the effort required to reconstruct the dependency tree. JAP addresses this problem by providing a consistent suite of RPMs compatible with RedHat Enterprise Linux and CentOS 6.4. Researchers can install JAP locally, either as RPMs or through a pre-built VM image, giving them the confidence to know moving analysis to JASMIN will not disrupt their environment. Analysis parallelisation is in it's infancy in climate sciences, with few tools capable of exploiting any parallel environment beyond manual scripting of the use of multiple processors. JAP begins to bridge this gap through a veriety of higher-level tools for parallelisation and job scheduling such as IPython-parallel and MPI support for interactive analysis languages. We find that enabling even simple parallelisation of workflows, together with the state of the art I/O performance of JASMIN storage, provides many users with the large increases in efficiency they need to scale their analyses to conteporary data volumes and tackly new, previously inaccessible, problems.

A hybrid parallel framework for the cellular Potts model simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jiang, Yi; He, Kejing; Dong, Shoubin

2009-01-01

The Cellular Potts Model (CPM) has been widely used for biological simulations. However, most current implementations are either sequential or approximated, which can't be used for large scale complex 3D simulation. In this paper we present a hybrid parallel framework for CPM simulations. The time-consuming POE solving, cell division, and cell reaction operation are distributed to clusters using the Message Passing Interface (MPI). The Monte Carlo lattice update is parallelized on shared-memory SMP system using OpenMP. Because the Monte Carlo lattice update is much faster than the POE solving and SMP systems are more and more common, this hybrid approachmore » achieves good performance and high accuracy at the same time. Based on the parallel Cellular Potts Model, we studied the avascular tumor growth using a multiscale model. The application and performance analysis show that the hybrid parallel framework is quite efficient. The hybrid parallel CPM can be used for the large scale simulation ({approx}10{sup 8} sites) of complex collective behavior of numerous cells ({approx}10{sup 6}).« less

The EMCC / DARPA Massively Parallel Electromagnetic Scattering Project

NASA Technical Reports Server (NTRS)

Woo, Alex C.; Hill, Kueichien C.

1996-01-01

The Electromagnetic Code Consortium (EMCC) was sponsored by the Advanced Research Program Agency (ARPA) to demonstrate the effectiveness of massively parallel computing in large scale radar signature predictions. The EMCC/ARPA project consisted of three parts.

PLASMA TURBULENCE AND KINETIC INSTABILITIES AT ION SCALES IN THE EXPANDING SOLAR WIND

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hellinger, Petr; Trávnícek, Pavel M.; Matteini, Lorenzo

The relationship between a decaying strong turbulence and kinetic instabilities in a slowly expanding plasma is investigated using two-dimensional (2D) hybrid expanding box simulations. We impose an initial ambient magnetic field perpendicular to the simulation box, and we start with a spectrum of large-scale, linearly polarized, random-phase Alfvénic fluctuations that have energy equipartition between kinetic and magnetic fluctuations and vanishing correlation between the two fields. A turbulent cascade rapidly develops; magnetic field fluctuations exhibit a power-law spectrum at large scales and a steeper spectrum at ion scales. The turbulent cascade leads to an overall anisotropic proton heating, protons are heatedmore » in the perpendicular direction, and, initially, also in the parallel direction. The imposed expansion leads to generation of a large parallel proton temperature anisotropy which is at later stages partly reduced by turbulence. The turbulent heating is not sufficient to overcome the expansion-driven perpendicular cooling and the system eventually drives the oblique firehose instability in a form of localized nonlinear wave packets which efficiently reduce the parallel temperature anisotropy. This work demonstrates that kinetic instabilities may coexist with strong plasma turbulence even in a constrained 2D regime.« less

WImpiBLAST: web interface for mpiBLAST to help biologists perform large-scale annotation using high performance computing.

PubMed

Sharma, Parichit; Mantri, Shrikant S

2014-01-01

The function of a newly sequenced gene can be discovered by determining its sequence homology with known proteins. BLAST is the most extensively used sequence analysis program for sequence similarity search in large databases of sequences. With the advent of next generation sequencing technologies it has now become possible to study genes and their expression at a genome-wide scale through RNA-seq and metagenome sequencing experiments. Functional annotation of all the genes is done by sequence similarity search against multiple protein databases. This annotation task is computationally very intensive and can take days to obtain complete results. The program mpiBLAST, an open-source parallelization of BLAST that achieves superlinear speedup, can be used to accelerate large-scale annotation by using supercomputers and high performance computing (HPC) clusters. Although many parallel bioinformatics applications using the Message Passing Interface (MPI) are available in the public domain, researchers are reluctant to use them due to lack of expertise in the Linux command line and relevant programming experience. With these limitations, it becomes difficult for biologists to use mpiBLAST for accelerating annotation. No web interface is available in the open-source domain for mpiBLAST. We have developed WImpiBLAST, a user-friendly open-source web interface for parallel BLAST searches. It is implemented in Struts 1.3 using a Java backbone and runs atop the open-source Apache Tomcat Server. WImpiBLAST supports script creation and job submission features and also provides a robust job management interface for system administrators. It combines script creation and modification features with job monitoring and management through the Torque resource manager on a Linux-based HPC cluster. Use case information highlights the acceleration of annotation analysis achieved by using WImpiBLAST. Here, we describe the WImpiBLAST web interface features and architecture, explain design decisions, describe workflows and provide a detailed analysis.

WImpiBLAST: Web Interface for mpiBLAST to Help Biologists Perform Large-Scale Annotation Using High Performance Computing

PubMed Central

Sharma, Parichit; Mantri, Shrikant S.

2014-01-01

The function of a newly sequenced gene can be discovered by determining its sequence homology with known proteins. BLAST is the most extensively used sequence analysis program for sequence similarity search in large databases of sequences. With the advent of next generation sequencing technologies it has now become possible to study genes and their expression at a genome-wide scale through RNA-seq and metagenome sequencing experiments. Functional annotation of all the genes is done by sequence similarity search against multiple protein databases. This annotation task is computationally very intensive and can take days to obtain complete results. The program mpiBLAST, an open-source parallelization of BLAST that achieves superlinear speedup, can be used to accelerate large-scale annotation by using supercomputers and high performance computing (HPC) clusters. Although many parallel bioinformatics applications using the Message Passing Interface (MPI) are available in the public domain, researchers are reluctant to use them due to lack of expertise in the Linux command line and relevant programming experience. With these limitations, it becomes difficult for biologists to use mpiBLAST for accelerating annotation. No web interface is available in the open-source domain for mpiBLAST. We have developed WImpiBLAST, a user-friendly open-source web interface for parallel BLAST searches. It is implemented in Struts 1.3 using a Java backbone and runs atop the open-source Apache Tomcat Server. WImpiBLAST supports script creation and job submission features and also provides a robust job management interface for system administrators. It combines script creation and modification features with job monitoring and management through the Torque resource manager on a Linux-based HPC cluster. Use case information highlights the acceleration of annotation analysis achieved by using WImpiBLAST. Here, we describe the WImpiBLAST web interface features and architecture, explain design decisions, describe workflows and provide a detailed analysis. PMID:24979410

Improved treatment of exact exchange in Quantum ESPRESSO

DOE PAGES

Barnes, Taylor A.; Kurth, Thorsten; Carrier, Pierre; ...

2017-01-18

Here, we present an algorithm and implementation for the parallel computation of exact exchange in Quantum ESPRESSO (QE) that exhibits greatly improved strong scaling. QE is an open-source software package for electronic structure calculations using plane wave density functional theory, and supports the use of local, semi-local, and hybrid DFT functionals. Wider application of hybrid functionals is desirable for the improved simulation of electronic band energy alignments and thermodynamic properties, but the computational complexity of evaluating the exact exchange potential limits the practical application of hybrid functionals to large systems and requires efficient implementations. We demonstrate that existing implementations ofmore » hybrid DFT that utilize a single data structure for both the local and exact exchange regions of the code are significantly limited in the degree of parallelization achievable. We present a band-pair parallelization approach, in which the calculation of exact exchange is parallelized and evaluated independently from the parallelization of the remainder of the calculation, with the wavefunction data being efficiently transformed on-the-fly into a form that is optimal for each part of the calculation. For a 64 water molecule supercell, our new algorithm reduces the overall time to solution by nearly an order of magnitude.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barnes, Taylor A.; Kurth, Thorsten; Carrier, Pierre

Here, we present an algorithm and implementation for the parallel computation of exact exchange in Quantum ESPRESSO (QE) that exhibits greatly improved strong scaling. QE is an open-source software package for electronic structure calculations using plane wave density functional theory, and supports the use of local, semi-local, and hybrid DFT functionals. Wider application of hybrid functionals is desirable for the improved simulation of electronic band energy alignments and thermodynamic properties, but the computational complexity of evaluating the exact exchange potential limits the practical application of hybrid functionals to large systems and requires efficient implementations. We demonstrate that existing implementations ofmore » hybrid DFT that utilize a single data structure for both the local and exact exchange regions of the code are significantly limited in the degree of parallelization achievable. We present a band-pair parallelization approach, in which the calculation of exact exchange is parallelized and evaluated independently from the parallelization of the remainder of the calculation, with the wavefunction data being efficiently transformed on-the-fly into a form that is optimal for each part of the calculation. For a 64 water molecule supercell, our new algorithm reduces the overall time to solution by nearly an order of magnitude.« less

Hybrid Parallelism for Volume Rendering on Large-, Multi-, and Many-Core Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Howison, Mark; Bethel, E. Wes; Childs, Hank

2012-01-01

With the computing industry trending towards multi- and many-core processors, we study how a standard visualization algorithm, ray-casting volume rendering, can benefit from a hybrid parallelism approach. Hybrid parallelism provides the best of both worlds: using distributed-memory parallelism across a large numbers of nodes increases available FLOPs and memory, while exploiting shared-memory parallelism among the cores within each node ensures that each node performs its portion of the larger calculation as efficiently as possible. We demonstrate results from weak and strong scaling studies, at levels of concurrency ranging up to 216,000, and with datasets as large as 12.2 trillion cells.more » The greatest benefit from hybrid parallelism lies in the communication portion of the algorithm, the dominant cost at higher levels of concurrency. We show that reducing the number of participants with a hybrid approach significantly improves performance.« less

Constructing Neuronal Network Models in Massively Parallel Environments.

PubMed

Ippen, Tammo; Eppler, Jochen M; Plesser, Hans E; Diesmann, Markus

2017-01-01

Recent advances in the development of data structures to represent spiking neuron network models enable us to exploit the complete memory of petascale computers for a single brain-scale network simulation. In this work, we investigate how well we can exploit the computing power of such supercomputers for the creation of neuronal networks. Using an established benchmark, we divide the runtime of simulation code into the phase of network construction and the phase during which the dynamical state is advanced in time. We find that on multi-core compute nodes network creation scales well with process-parallel code but exhibits a prohibitively large memory consumption. Thread-parallel network creation, in contrast, exhibits speedup only up to a small number of threads but has little overhead in terms of memory. We further observe that the algorithms creating instances of model neurons and their connections scale well for networks of ten thousand neurons, but do not show the same speedup for networks of millions of neurons. Our work uncovers that the lack of scaling of thread-parallel network creation is due to inadequate memory allocation strategies and demonstrates that thread-optimized memory allocators recover excellent scaling. An analysis of the loop order used for network construction reveals that more complex tests on the locality of operations significantly improve scaling and reduce runtime by allowing construction algorithms to step through large networks more efficiently than in existing code. The combination of these techniques increases performance by an order of magnitude and harnesses the increasingly parallel compute power of the compute nodes in high-performance clusters and supercomputers.

Constructing Neuronal Network Models in Massively Parallel Environments

PubMed Central

Ippen, Tammo; Eppler, Jochen M.; Plesser, Hans E.; Diesmann, Markus

2017-01-01

Recent advances in the development of data structures to represent spiking neuron network models enable us to exploit the complete memory of petascale computers for a single brain-scale network simulation. In this work, we investigate how well we can exploit the computing power of such supercomputers for the creation of neuronal networks. Using an established benchmark, we divide the runtime of simulation code into the phase of network construction and the phase during which the dynamical state is advanced in time. We find that on multi-core compute nodes network creation scales well with process-parallel code but exhibits a prohibitively large memory consumption. Thread-parallel network creation, in contrast, exhibits speedup only up to a small number of threads but has little overhead in terms of memory. We further observe that the algorithms creating instances of model neurons and their connections scale well for networks of ten thousand neurons, but do not show the same speedup for networks of millions of neurons. Our work uncovers that the lack of scaling of thread-parallel network creation is due to inadequate memory allocation strategies and demonstrates that thread-optimized memory allocators recover excellent scaling. An analysis of the loop order used for network construction reveals that more complex tests on the locality of operations significantly improve scaling and reduce runtime by allowing construction algorithms to step through large networks more efficiently than in existing code. The combination of these techniques increases performance by an order of magnitude and harnesses the increasingly parallel compute power of the compute nodes in high-performance clusters and supercomputers. PMID:28559808

Parallel Mutual Information Based Construction of Genome-Scale Networks on the Intel® Xeon Phi™ Coprocessor.

PubMed

Misra, Sanchit; Pamnany, Kiran; Aluru, Srinivas

2015-01-01

Construction of whole-genome networks from large-scale gene expression data is an important problem in systems biology. While several techniques have been developed, most cannot handle network reconstruction at the whole-genome scale, and the few that can, require large clusters. In this paper, we present a solution on the Intel Xeon Phi coprocessor, taking advantage of its multi-level parallelism including many x86-based cores, multiple threads per core, and vector processing units. We also present a solution on the Intel® Xeon® processor. Our solution is based on TINGe, a fast parallel network reconstruction technique that uses mutual information and permutation testing for assessing statistical significance. We demonstrate the first ever inference of a plant whole genome regulatory network on a single chip by constructing a 15,575 gene network of the plant Arabidopsis thaliana from 3,137 microarray experiments in only 22 minutes. In addition, our optimization for parallelizing mutual information computation on the Intel Xeon Phi coprocessor holds out lessons that are applicable to other domains.

MMS Observations of Parallel Electric Fields During a Quasi-Perpendicular Bow Shock Crossing

NASA Astrophysics Data System (ADS)

Goodrich, K.; Schwartz, S. J.; Ergun, R.; Wilder, F. D.; Holmes, J.; Burch, J. L.; Gershman, D. J.; Giles, B. L.; Khotyaintsev, Y. V.; Le Contel, O.; Lindqvist, P. A.; Strangeway, R. J.; Russell, C.; Torbert, R. B.

2016-12-01

Previous observations of the terrestrial bow shock have frequently shown large-amplitude fluctuations in the parallel electric field. These parallel electric fields are seen as both nonlinear solitary structures, such as double layers and electron phase-space holes, and short-wavelength waves, which can reach amplitudes greater than 100 mV/m. The Magnetospheric Multi-Scale (MMS) Mission has crossed the Earth's bow shock more than 200 times. The parallel electric field signatures observed in these crossings are seen in very discrete packets and evolve over time scales of less than a second, indicating the presence of a wealth of kinetic-scale activity. The high time resolution of the Fast Particle Instrument (FPI) available on MMS offers greater detail of the kinetic-scale physics that occur at bow shocks than ever before, allowing greater insight into the overall effect of these observed electric fields. We present a characterization of these parallel electric fields found in a single bow shock event and how it reflects the kinetic-scale activity that can occur at the terrestrial bow shock.

A transient FETI methodology for large-scale parallel implicit computations in structural mechanics

NASA Technical Reports Server (NTRS)

Farhat, Charbel; Crivelli, Luis; Roux, Francois-Xavier

1992-01-01

Explicit codes are often used to simulate the nonlinear dynamics of large-scale structural systems, even for low frequency response, because the storage and CPU requirements entailed by the repeated factorizations traditionally found in implicit codes rapidly overwhelm the available computing resources. With the advent of parallel processing, this trend is accelerating because explicit schemes are also easier to parallelize than implicit ones. However, the time step restriction imposed by the Courant stability condition on all explicit schemes cannot yet -- and perhaps will never -- be offset by the speed of parallel hardware. Therefore, it is essential to develop efficient and robust alternatives to direct methods that are also amenable to massively parallel processing because implicit codes using unconditionally stable time-integration algorithms are computationally more efficient when simulating low-frequency dynamics. Here we present a domain decomposition method for implicit schemes that requires significantly less storage than factorization algorithms, that is several times faster than other popular direct and iterative methods, that can be easily implemented on both shared and local memory parallel processors, and that is both computationally and communication-wise efficient. The proposed transient domain decomposition method is an extension of the method of Finite Element Tearing and Interconnecting (FETI) developed by Farhat and Roux for the solution of static problems. Serial and parallel performance results on the CRAY Y-MP/8 and the iPSC-860/128 systems are reported and analyzed for realistic structural dynamics problems. These results establish the superiority of the FETI method over both the serial/parallel conjugate gradient algorithm with diagonal scaling and the serial/parallel direct method, and contrast the computational power of the iPSC-860/128 parallel processor with that of the CRAY Y-MP/8 system.

Sight Application Analysis Tool

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bronevetsky, G.

2014-09-17

The scale and complexity of scientific applications makes it very difficult to optimize, debug and extend them to support new capabilities. We have developed a tool that supports developers’ efforts to understand the logical flow of their applications and interactions between application components and hardware in a way that scales with application complexity and parallelism.

Performance of parallel computation using CUDA for solving the one-dimensional elasticity equations

NASA Astrophysics Data System (ADS)

Darmawan, J. B. B.; Mungkasi, S.

2017-01-01

In this paper, we investigate the performance of parallel computation in solving the one-dimensional elasticity equations. Elasticity equations are usually implemented in engineering science. Solving these equations fast and efficiently is desired. Therefore, we propose the use of parallel computation. Our parallel computation uses CUDA of the NVIDIA. Our research results show that parallel computation using CUDA has a great advantage and is powerful when the computation is of large scale.

Porting LAMMPS to GPUs.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brown, William Michael; Plimpton, Steven James; Wang, Peng

2010-03-01

LAMMPS is a classical molecular dynamics code, and an acronym for Large-scale Atomic/Molecular Massively Parallel Simulator. LAMMPS has potentials for soft materials (biomolecules, polymers) and solid-state materials (metals, semiconductors) and coarse-grained or mesoscopic systems. It can be used to model atoms or, more generically, as a parallel particle simulator at the atomic, meso, or continuum scale. LAMMPS runs on single processors or in parallel using message-passing techniques and a spatial-decomposition of the simulation domain. The code is designed to be easy to modify or extend with new functionality.

Traffic Flow Management and Optimization

NASA Technical Reports Server (NTRS)

Rios, Joseph Lucio

2014-01-01

This talk will present an overview of Traffic Flow Management (TFM) research at NASA Ames Research Center. Dr. Rios will focus on his work developing a large-scale, parallel approach to solving traffic flow management problems in the national airspace. In support of this talk, Dr. Rios will provide some background on operational aspects of TFM as well a discussion of some of the tools needed to perform such work including a high-fidelity airspace simulator. Current, on-going research related to TFM data services in the national airspace system and general aviation will also be presented.

Parallel-vector solution of large-scale structural analysis problems on supercomputers

NASA Technical Reports Server (NTRS)

Storaasli, Olaf O.; Nguyen, Duc T.; Agarwal, Tarun K.

1989-01-01

A direct linear equation solution method based on the Choleski factorization procedure is presented which exploits both parallel and vector features of supercomputers. The new equation solver is described, and its performance is evaluated by solving structural analysis problems on three high-performance computers. The method has been implemented using Force, a generic parallel FORTRAN language.

Correlation of generation interval and scale of large-scale submarine landslides using 3D seismic data off Shimokita Peninsula, Northeast Japan

NASA Astrophysics Data System (ADS)

Nakamura, Yuki; Ashi, Juichiro; Morita, Sumito

2016-04-01

To clarify timing and scale of past submarine landslides is important to understand formation processes of the landslides. The study area is in a part of continental slope of the Japan Trench, where a number of large-scale submarine landslide (slump) deposits have been identified in Pliocene and Quaternary formations by analysing METI's 3D seismic data "Sanrikuoki 3D" off Shimokita Peninsula (Morita et al., 2011). As structural features, swarm of parallel dikes which are likely dewatering paths formed accompanying the slumping deformation, and slip directions are basically perpendicular to the parallel dikes. Therefore, parallel dikes are good indicator for estimation of slip directions. Slip direction of each slide was determined one kilometre grid in the survey area of 40 km x 20 km. The remarkable slip direction varies from Pliocene to Quaternary in the survey area. Parallel dike structure is also available for the distinguishment of the slump deposit and normal deposit on time slice images. By tracing outline of slump deposits at each depth, we identified general morphology of the overall slump deposits, and calculated the volume of the extracted slump deposits so as to estimate the scale of each event. We investigated temporal and spatial variation of depositional pattern of the slump deposits. Calculating the generation interval of the slumps, some periodicity is likely recognized, especially large slump do not occur in succession. Additionally, examining the relationship of the cumulative volume and the generation interval, certain correlation is observed in Pliocene and Quaternary. Key words: submarine landslides, 3D seismic data, Shimokita Peninsula

A Screen Space GPGPU Surface LIC Algorithm for Distributed Memory Data Parallel Sort Last Rendering Infrastructures

NASA Astrophysics Data System (ADS)

Loring, B.; Karimabadi, H.; Rortershteyn, V.

2015-10-01

The surface line integral convolution(LIC) visualization technique produces dense visualization of vector fields on arbitrary surfaces. We present a screen space surface LIC algorithm for use in distributed memory data parallel sort last rendering infrastructures. The motivations for our work are to support analysis of datasets that are too large to fit in the main memory of a single computer and compatibility with prevalent parallel scientific visualization tools such as ParaView and VisIt. By working in screen space using OpenGL we can leverage the computational power of GPUs when they are available and run without them when they are not. We address efficiency and performance issues that arise from the transformation of data from physical to screen space by selecting an alternate screen space domain decomposition. We analyze the algorithm's scaling behavior with and without GPUs on two high performance computing systems using data from turbulent plasma simulations.

A Screen Space GPGPU Surface LIC Algorithm for Distributed Memory Data Parallel Sort Last Rendering Infrastructures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Loring, Burlen; Karimabadi, Homa; Rortershteyn, Vadim

2014-07-01

The surface line integral convolution(LIC) visualization technique produces dense visualization of vector fields on arbitrary surfaces. We present a screen space surface LIC algorithm for use in distributed memory data parallel sort last rendering infrastructures. The motivations for our work are to support analysis of datasets that are too large to fit in the main memory of a single computer and compatibility with prevalent parallel scientific visualization tools such as ParaView and VisIt. By working in screen space using OpenGL we can leverage the computational power of GPUs when they are available and run without them when they are not.more » We address efficiency and performance issues that arise from the transformation of data from physical to screen space by selecting an alternate screen space domain decomposition. We analyze the algorithm's scaling behavior with and without GPUs on two high performance computing systems using data from turbulent plasma simulations.« less

Brief Self-Efficacy Scales for use in Weight-Loss Trials: Preliminary Evidence of Validity

PubMed Central

Wilson, Kathryn E.; Harden, Samantha M.; Almeida, Fabio A.; You, Wen; Hill, Jennie L.; Goessl, Cody; Estabrooks, Paul A.

2015-01-01

Self-efficacy is a commonly included cognitive variable in weight-loss trials, but there is little uniformity in its measurement. Weight-loss trials frequently focus on physical activity (PA) and eating behavior, as well as weight loss, but no survey is available that offers reliable measurement of self-efficacy as it relates to each of these targeted outcomes. The purpose of this study was to test the psychometric properties of brief, pragmatic self-efficacy scales specific to PA, healthful eating and weight-loss (4 items each). An adult sample (n=1790) from 28 worksites enrolled in a worksite weight-loss program completed the self-efficacy scale, as well as measures of PA, dietary fat intake, and weight, at baseline, 6-, and 12-months. The hypothesized factor structure was tested through confirmatory factor analysis, which supported the expected factor structure for three latent self-efficacy factors, specific to PA, healthful eating, and weight-loss. Measurement equivalence/invariance between relevant demographic groups, and over time was also supported. Parallel growth processes in self-efficacy factors and outcomes (PA, fat intake, and weight) support the predictive validity of score interpretations. Overall, this initial series of psychometric analyses supports the interpretation that scores on these scales reflect self-efficacy for PA, healthful eating, and weight-loss. The use of this instrument in large-scale weight-loss trials is encouraged. PMID:26619093

Large-Scale Linear Optimization through Machine Learning: From Theory to Practical System Design and Implementation

DTIC Science & Technology

2016-08-10

AFRL-AFOSR-JP-TR-2016-0073 Large-scale Linear Optimization through Machine Learning: From Theory to Practical System Design and Implementation ...2016 4.  TITLE AND SUBTITLE Large-scale Linear Optimization through Machine Learning: From Theory to Practical System Design and Implementation 5a...performances on various machine learning tasks and it naturally lends itself to fast parallel implementations . Despite this, very little work has been

Parallel digital forensics infrastructure.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liebrock, Lorie M.; Duggan, David Patrick

2009-10-01

This report documents the architecture and implementation of a Parallel Digital Forensics infrastructure. This infrastructure is necessary for supporting the design, implementation, and testing of new classes of parallel digital forensics tools. Digital Forensics has become extremely difficult with data sets of one terabyte and larger. The only way to overcome the processing time of these large sets is to identify and develop new parallel algorithms for performing the analysis. To support algorithm research, a flexible base infrastructure is required. A candidate architecture for this base infrastructure was designed, instantiated, and tested by this project, in collaboration with New Mexicomore » Tech. Previous infrastructures were not designed and built specifically for the development and testing of parallel algorithms. With the size of forensics data sets only expected to increase significantly, this type of infrastructure support is necessary for continued research in parallel digital forensics. This report documents the implementation of the parallel digital forensics (PDF) infrastructure architecture and implementation.« less

Highly Efficient Parallel Multigrid Solver For Large-Scale Simulation of Grain Growth Using the Structural Phase Field Crystal Model

NASA Astrophysics Data System (ADS)

Guan, Zhen; Pekurovsky, Dmitry; Luce, Jason; Thornton, Katsuyo; Lowengrub, John

The structural phase field crystal (XPFC) model can be used to model grain growth in polycrystalline materials at diffusive time-scales while maintaining atomic scale resolution. However, the governing equation of the XPFC model is an integral-partial-differential-equation (IPDE), which poses challenges in implementation onto high performance computing (HPC) platforms. In collaboration with the XSEDE Extended Collaborative Support Service, we developed a distributed memory HPC solver for the XPFC model, which combines parallel multigrid and P3DFFT. The performance benchmarking on the Stampede supercomputer indicates near linear strong and weak scaling for both multigrid and transfer time between multigrid and FFT modules up to 1024 cores. Scalability of the FFT module begins to decline at 128 cores, but it is sufficient for the type of problem we will be examining. We have demonstrated simulations using 1024 cores, and we expect to achieve 4096 cores and beyond. Ongoing work involves optimization of MPI/OpenMP-based codes for the Intel KNL Many-Core Architecture. This optimizes the code for coming pre-exascale systems, in particular many-core systems such as Stampede 2.0 and Cori 2 at NERSC, without sacrificing efficiency on other general HPC systems.

Experiences with hypercube operating system instrumentation

NASA Technical Reports Server (NTRS)

Reed, Daniel A.; Rudolph, David C.

1989-01-01

The difficulties in conceptualizing the interactions among a large number of processors make it difficult both to identify the sources of inefficiencies and to determine how a parallel program could be made more efficient. This paper describes an instrumentation system that can trace the execution of distributed memory parallel programs by recording the occurrence of parallel program events. The resulting event traces can be used to compile summary statistics that provide a global view of program performance. In addition, visualization tools permit the graphic display of event traces. Visual presentation of performance data is particularly useful, indeed, necessary for large-scale parallel computers; the enormous volume of performance data mandates visual display.

Liter-scale production of uniform gas bubbles via parallelization of flow-focusing generators.

PubMed

Jeong, Heon-Ho; Yadavali, Sagar; Issadore, David; Lee, Daeyeon

2017-07-25

Microscale gas bubbles have demonstrated enormous utility as versatile templates for the synthesis of functional materials in medicine, ultra-lightweight materials and acoustic metamaterials. In many of these applications, high uniformity of the size of the gas bubbles is critical to achieve the desired properties and functionality. While microfluidics have been used with success to create gas bubbles that have a uniformity not achievable using conventional methods, the inherently low volumetric flow rate of microfluidics has limited its use in most applications. Parallelization of liquid droplet generators, in which many droplet generators are incorporated onto a single chip, has shown great promise for the large scale production of monodisperse liquid emulsion droplets. However, the scale-up of monodisperse gas bubbles using such an approach has remained a challenge because of possible coupling between parallel bubbles generators and feedback effects from the downstream channels. In this report, we systematically investigate the effect of factors such as viscosity of the continuous phase, capillary number, and gas pressure as well as the channel uniformity on the size distribution of gas bubbles in a parallelized microfluidic device. We show that, by optimizing the flow conditions, a device with 400 parallel flow focusing generators on a footprint of 5 × 5 cm 2 can be used to generate gas bubbles with a coefficient of variation of less than 5% at a production rate of approximately 1 L h -1 . Our results suggest that the optimization of flow conditions using a device with a small number (e.g., 8) of parallel FFGs can facilitate large-scale bubble production.

Myria: Scalable Analytics as a Service

NASA Astrophysics Data System (ADS)

Howe, B.; Halperin, D.; Whitaker, A.

2014-12-01

At the UW eScience Institute, we're working to empower non-experts, especially in the sciences, to write and use data-parallel algorithms. To this end, we are building Myria, a web-based platform for scalable analytics and data-parallel programming. Myria's internal model of computation is the relational algebra extended with iteration, such that every program is inherently data-parallel, just as every query in a database is inherently data-parallel. But unlike databases, iteration is a first class concept, allowing us to express machine learning tasks, graph traversal tasks, and more. Programs can be expressed in a number of languages and can be executed on a number of execution environments, but we emphasize a particular language called MyriaL that supports both imperative and declarative styles and a particular execution engine called MyriaX that uses an in-memory column-oriented representation and asynchronous iteration. We deliver Myria over the web as a service, providing an editor, performance analysis tools, and catalog browsing features in a single environment. We find that this web-based "delivery vector" is critical in reaching non-experts: they are insulated from irrelevant effort technical work associated with installation, configuration, and resource management. The MyriaX backend, one of several execution runtimes we support, is a main-memory, column-oriented, RDBMS-on-the-worker system that supports cyclic data flows as a first-class citizen and has been shown to outperform competitive systems on 100-machine cluster sizes. I will describe the Myria system, give a demo, and present some new results in large-scale oceanographic microbiology.

Parallel Large-Scale Molecular Dynamics Simulation Opens New Perspective to Clarify the Effect of a Porous Structure on the Sintering Process of Ni/YSZ Multiparticles.

PubMed

Xu, Jingxiang; Higuchi, Yuji; Ozawa, Nobuki; Sato, Kazuhisa; Hashida, Toshiyuki; Kubo, Momoji

2017-09-20

Ni sintering in the Ni/YSZ porous anode of a solid oxide fuel cell changes the porous structure, leading to degradation. Preventing sintering and degradation during operation is a great challenge. Usually, a sintering molecular dynamics (MD) simulation model consisting of two particles on a substrate is used; however, the model cannot reflect the porous structure effect on sintering. In our previous study, a multi-nanoparticle sintering modeling method with tens of thousands of atoms revealed the effect of the particle framework and porosity on sintering. However, the method cannot reveal the effect of the particle size on sintering and the effect of sintering on the change in the porous structure. In the present study, we report a strategy to reveal them in the porous structure by using our multi-nanoparticle modeling method and a parallel large-scale multimillion-atom MD simulator. We used this method to investigate the effect of YSZ particle size and tortuosity on sintering and degradation in the Ni/YSZ anodes. Our parallel large-scale MD simulation showed that the sintering degree decreased as the YSZ particle size decreased. The gas fuel diffusion path, which reflects the overpotential, was blocked by pore coalescence during sintering. The degradation of gas diffusion performance increased as the YSZ particle size increased. Furthermore, the gas diffusion performance was quantified by a tortuosity parameter and an optimal YSZ particle size, which is equal to that of Ni, was found for good diffusion after sintering. These findings cannot be obtained by previous MD sintering studies with tens of thousands of atoms. The present parallel large-scale multimillion-atom MD simulation makes it possible to clarify the effects of the particle size and tortuosity on sintering and degradation.

Trace: a high-throughput tomographic reconstruction engine for large-scale datasets

DOE PAGES

Bicer, Tekin; Gursoy, Doga; Andrade, Vincent De; ...

2017-01-28

Here, synchrotron light source and detector technologies enable scientists to perform advanced experiments. These scientific instruments and experiments produce data at such scale and complexity that large-scale computation is required to unleash their full power. One of the widely used data acquisition technique at light sources is Computed Tomography, which can generate tens of GB/s depending on x-ray range. A large-scale tomographic dataset, such as mouse brain, may require hours of computation time with a medium size workstation. In this paper, we present Trace, a data-intensive computing middleware we developed for implementation and parallelization of iterative tomographic reconstruction algorithms. Tracemore » provides fine-grained reconstruction of tomography datasets using both (thread level) shared memory and (process level) distributed memory parallelization. Trace utilizes a special data structure called replicated reconstruction object to maximize application performance. We also present the optimizations we have done on the replicated reconstruction objects and evaluate them using a shale and a mouse brain sinogram. Our experimental evaluations show that the applied optimizations and parallelization techniques can provide 158x speedup (using 32 compute nodes) over single core configuration, which decreases the reconstruction time of a sinogram (with 4501 projections and 22400 detector resolution) from 12.5 hours to less than 5 minutes per iteration.« less

Trace: a high-throughput tomographic reconstruction engine for large-scale datasets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bicer, Tekin; Gursoy, Doga; Andrade, Vincent De

Here, synchrotron light source and detector technologies enable scientists to perform advanced experiments. These scientific instruments and experiments produce data at such scale and complexity that large-scale computation is required to unleash their full power. One of the widely used data acquisition technique at light sources is Computed Tomography, which can generate tens of GB/s depending on x-ray range. A large-scale tomographic dataset, such as mouse brain, may require hours of computation time with a medium size workstation. In this paper, we present Trace, a data-intensive computing middleware we developed for implementation and parallelization of iterative tomographic reconstruction algorithms. Tracemore » provides fine-grained reconstruction of tomography datasets using both (thread level) shared memory and (process level) distributed memory parallelization. Trace utilizes a special data structure called replicated reconstruction object to maximize application performance. We also present the optimizations we have done on the replicated reconstruction objects and evaluate them using a shale and a mouse brain sinogram. Our experimental evaluations show that the applied optimizations and parallelization techniques can provide 158x speedup (using 32 compute nodes) over single core configuration, which decreases the reconstruction time of a sinogram (with 4501 projections and 22400 detector resolution) from 12.5 hours to less than 5 minutes per iteration.« less

Space Technology 5 Multi-point Observations of Field-aligned Currents: Temporal Variability of Meso-Scale Structures

NASA Technical Reports Server (NTRS)

Le, Guan; Wang, Yongli; Slavin, James A.; Strangeway, Robert J.

2007-01-01

Space Technology 5 (ST5) is a three micro-satellite constellation deployed into a 300 x 4500 km, dawn-dusk, sun-synchronous polar orbit from March 22 to June 21, 2006, for technology validations. In this paper, we present a study of the temporal variability of field-aligned currents using multi-point magnetic field measurements from ST5. The data demonstrate that meso-scale current structures are commonly embedded within large-scale field-aligned current sheets. The meso-scale current structures are very dynamic with highly variable current density and/or polarity in time scales of - 10 min. They exhibit large temporal variations during both quiet and disturbed times in such time scales. On the other hand, the data also shown that the time scales for the currents to be relatively stable are approx. 1 min for meso-scale currents and approx. 10 min for large scale current sheets. These temporal features are obviously associated with dynamic variations of their particle carriers (mainly electrons) as they respond to the variations of the parallel electric field in auroral acceleration region. The characteristic time scales for the temporal variability of meso-scale field-aligned currents are found to be consistent with those of auroral parallel electric field.

PARAMO: A Parallel Predictive Modeling Platform for Healthcare Analytic Research using Electronic Health Records

PubMed Central

Ng, Kenney; Ghoting, Amol; Steinhubl, Steven R.; Stewart, Walter F.; Malin, Bradley; Sun, Jimeng

2014-01-01

Objective Healthcare analytics research increasingly involves the construction of predictive models for disease targets across varying patient cohorts using electronic health records (EHRs). To facilitate this process, it is critical to support a pipeline of tasks: 1) cohort construction, 2) feature construction, 3) cross-validation, 4) feature selection, and 5) classification. To develop an appropriate model, it is necessary to compare and refine models derived from a diversity of cohorts, patient-specific features, and statistical frameworks. The goal of this work is to develop and evaluate a predictive modeling platform that can be used to simplify and expedite this process for health data. Methods To support this goal, we developed a PARAllel predictive MOdeling (PARAMO) platform which 1) constructs a dependency graph of tasks from specifications of predictive modeling pipelines, 2) schedules the tasks in a topological ordering of the graph, and 3) executes those tasks in parallel. We implemented this platform using Map-Reduce to enable independent tasks to run in parallel in a cluster computing environment. Different task scheduling preferences are also supported. Results We assess the performance of PARAMO on various workloads using three datasets derived from the EHR systems in place at Geisinger Health System and Vanderbilt University Medical Center and an anonymous longitudinal claims database. We demonstrate significant gains in computational efficiency against a standard approach. In particular, PARAMO can build 800 different models on a 300,000 patient data set in 3 hours in parallel compared to 9 days if running sequentially. Conclusion This work demonstrates that an efficient parallel predictive modeling platform can be developed for EHR data. This platform can facilitate large-scale modeling endeavors and speed-up the research workflow and reuse of health information. This platform is only a first step and provides the foundation for our ultimate goal of building analytic pipelines that are specialized for health data researchers. PMID:24370496

PARAMO: a PARAllel predictive MOdeling platform for healthcare analytic research using electronic health records.

PubMed

Ng, Kenney; Ghoting, Amol; Steinhubl, Steven R; Stewart, Walter F; Malin, Bradley; Sun, Jimeng

2014-04-01

Healthcare analytics research increasingly involves the construction of predictive models for disease targets across varying patient cohorts using electronic health records (EHRs). To facilitate this process, it is critical to support a pipeline of tasks: (1) cohort construction, (2) feature construction, (3) cross-validation, (4) feature selection, and (5) classification. To develop an appropriate model, it is necessary to compare and refine models derived from a diversity of cohorts, patient-specific features, and statistical frameworks. The goal of this work is to develop and evaluate a predictive modeling platform that can be used to simplify and expedite this process for health data. To support this goal, we developed a PARAllel predictive MOdeling (PARAMO) platform which (1) constructs a dependency graph of tasks from specifications of predictive modeling pipelines, (2) schedules the tasks in a topological ordering of the graph, and (3) executes those tasks in parallel. We implemented this platform using Map-Reduce to enable independent tasks to run in parallel in a cluster computing environment. Different task scheduling preferences are also supported. We assess the performance of PARAMO on various workloads using three datasets derived from the EHR systems in place at Geisinger Health System and Vanderbilt University Medical Center and an anonymous longitudinal claims database. We demonstrate significant gains in computational efficiency against a standard approach. In particular, PARAMO can build 800 different models on a 300,000 patient data set in 3h in parallel compared to 9days if running sequentially. This work demonstrates that an efficient parallel predictive modeling platform can be developed for EHR data. This platform can facilitate large-scale modeling endeavors and speed-up the research workflow and reuse of health information. This platform is only a first step and provides the foundation for our ultimate goal of building analytic pipelines that are specialized for health data researchers. Copyright © 2013 Elsevier Inc. All rights reserved.

Stability of Large Parallel Tunnels Excavated in Weak Rocks: A Case Study

NASA Astrophysics Data System (ADS)

Ding, Xiuli; Weng, Yonghong; Zhang, Yuting; Xu, Tangjin; Wang, Tuanle; Rao, Zhiwen; Qi, Zufang

2017-09-01

Diversion tunnels are important structures for hydropower projects but are always placed in locations with less favorable geological conditions than those in which other structures are placed. Because diversion tunnels are usually large and closely spaced, the rock pillar between adjacent tunnels in weak rocks is affected on both sides, and conventional support measures may not be adequate to achieve the required stability. Thus, appropriate reinforcement support measures are needed, and the design philosophy regarding large parallel tunnels in weak rocks should be updated. This paper reports a recent case in which two large parallel diversion tunnels are excavated. The rock masses are thin- to ultra-thin-layered strata coated with phyllitic films, which significantly decrease the soundness and strength of the strata and weaken the rocks. The behaviors of the surrounding rock masses under original (and conventional) support measures are detailed in terms of rock mass deformation, anchor bolt stress, and the extent of the excavation disturbed zone (EDZ), as obtained from safety monitoring and field testing. In situ observed phenomena and their interpretation are also included. The sidewall deformations exhibit significant time-dependent characteristics, and large magnitudes are recorded. The stresses in the anchor bolts are small, but the extents of the EDZs are large. The stability condition under the original support measures is evaluated as poor. To enhance rock mass stability, attempts are made to reinforce support design and improve safety monitoring programs. The main feature of these attempts is the use of prestressed cables that run through the rock pillar between the parallel tunnels. The efficacy of reinforcement support measures is verified by further safety monitoring data and field test results. Numerical analysis is constantly performed during the construction process to provide a useful reference for decision making. The calculated deformations are in good agreement with the measured data, and the calculated forces of newly added cables show that the designed reinforcement is necessary and ensures sufficient stability. Finally, the role of safety monitoring in the evaluation of rock mass stability and the consideration of tunnel group effect are discussed. The work described in this paper aims to deepen the understanding of rock mass behaviors of large parallel tunnels in weak rocks and to improve the design philosophy.

Portability and Cross-Platform Performance of an MPI-Based Parallel Polygon Renderer

NASA Technical Reports Server (NTRS)

Crockett, Thomas W.

1999-01-01

Visualizing the results of computations performed on large-scale parallel computers is a challenging problem, due to the size of the datasets involved. One approach is to perform the visualization and graphics operations in place, exploiting the available parallelism to obtain the necessary rendering performance. Over the past several years, we have been developing algorithms and software to support visualization applications on NASA's parallel supercomputers. Our results have been incorporated into a parallel polygon rendering system called PGL. PGL was initially developed on tightly-coupled distributed-memory message-passing systems, including Intel's iPSC/860 and Paragon, and IBM's SP2. Over the past year, we have ported it to a variety of additional platforms, including the HP Exemplar, SGI Origin2OOO, Cray T3E, and clusters of Sun workstations. In implementing PGL, we have had two primary goals: cross-platform portability and high performance. Portability is important because (1) our manpower resources are limited, making it difficult to develop and maintain multiple versions of the code, and (2) NASA's complement of parallel computing platforms is diverse and subject to frequent change. Performance is important in delivering adequate rendering rates for complex scenes and ensuring that parallel computing resources are used effectively. Unfortunately, these two goals are often at odds. In this paper we report on our experiences with portability and performance of the PGL polygon renderer across a range of parallel computing platforms.

A Parallel Sliding Region Algorithm to Make Agent-Based Modeling Possible for a Large-Scale Simulation: Modeling Hepatitis C Epidemics in Canada.

PubMed

Wong, William W L; Feng, Zeny Z; Thein, Hla-Hla

2016-11-01

Agent-based models (ABMs) are computer simulation models that define interactions among agents and simulate emergent behaviors that arise from the ensemble of local decisions. ABMs have been increasingly used to examine trends in infectious disease epidemiology. However, the main limitation of ABMs is the high computational cost for a large-scale simulation. To improve the computational efficiency for large-scale ABM simulations, we built a parallelizable sliding region algorithm (SRA) for ABM and compared it to a nonparallelizable ABM. We developed a complex agent network and performed two simulations to model hepatitis C epidemics based on the real demographic data from Saskatchewan, Canada. The first simulation used the SRA that processed on each postal code subregion subsequently. The second simulation processed the entire population simultaneously. It was concluded that the parallelizable SRA showed computational time saving with comparable results in a province-wide simulation. Using the same method, SRA can be generalized for performing a country-wide simulation. Thus, this parallel algorithm enables the possibility of using ABM for large-scale simulation with limited computational resources.

GPU-Accelerated Large-Scale Electronic Structure Theory on Titan with a First-Principles All-Electron Code

NASA Astrophysics Data System (ADS)

Huhn, William Paul; Lange, Björn; Yu, Victor; Blum, Volker; Lee, Seyong; Yoon, Mina

Density-functional theory has been well established as the dominant quantum-mechanical computational method in the materials community. Large accurate simulations become very challenging on small to mid-scale computers and require high-performance compute platforms to succeed. GPU acceleration is one promising approach. In this talk, we present a first implementation of all-electron density-functional theory in the FHI-aims code for massively parallel GPU-based platforms. Special attention is paid to the update of the density and to the integration of the Hamiltonian and overlap matrices, realized in a domain decomposition scheme on non-uniform grids. The initial implementation scales well across nodes on ORNL's Titan Cray XK7 supercomputer (8 to 64 nodes, 16 MPI ranks/node) and shows an overall speed up in runtime due to utilization of the K20X Tesla GPUs on each Titan node of 1.4x, with the charge density update showing a speed up of 2x. Further acceleration opportunities will be discussed. Work supported by the LDRD Program of ORNL managed by UT-Battle, LLC, for the U.S. DOE and by the Oak Ridge Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC05-00OR22725.

Transport of cosmic-ray protons in intermittent heliospheric turbulence: Model and simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Alouani-Bibi, Fathallah; Le Roux, Jakobus A., E-mail: fb0006@uah.edu

The transport of charged energetic particles in the presence of strong intermittent heliospheric turbulence is computationally analyzed based on known properties of the interplanetary magnetic field and solar wind plasma at 1 astronomical unit. The turbulence is assumed to be static, composite, and quasi-three-dimensional with a varying energy distribution between a one-dimensional Alfvénic (slab) and a structured two-dimensional component. The spatial fluctuations of the turbulent magnetic field are modeled either as homogeneous with a Gaussian probability distribution function (PDF), or as intermittent on large and small scales with a q-Gaussian PDF. Simulations showed that energetic particle diffusion coefficients both parallelmore » and perpendicular to the background magnetic field are significantly affected by intermittency in the turbulence. This effect is especially strong for parallel transport where for large-scale intermittency results show an extended phase of subdiffusive parallel transport during which cross-field transport diffusion dominates. The effects of intermittency are found to depend on particle rigidity and the fraction of slab energy in the turbulence, yielding a perpendicular to parallel mean free path ratio close to 1 for large-scale intermittency. Investigation of higher order transport moments (kurtosis) indicates that non-Gaussian statistical properties of the intermittent turbulent magnetic field are present in the parallel transport, especially for low rigidity particles at all times.« less

Multilevel summation method for electrostatic force evaluation.

PubMed

Hardy, David J; Wu, Zhe; Phillips, James C; Stone, John E; Skeel, Robert D; Schulten, Klaus

2015-02-10

The multilevel summation method (MSM) offers an efficient algorithm utilizing convolution for evaluating long-range forces arising in molecular dynamics simulations. Shifting the balance of computation and communication, MSM provides key advantages over the ubiquitous particle–mesh Ewald (PME) method, offering better scaling on parallel computers and permitting more modeling flexibility, with support for periodic systems as does PME but also for semiperiodic and nonperiodic systems. The version of MSM available in the simulation program NAMD is described, and its performance and accuracy are compared with the PME method. The accuracy feasible for MSM in practical applications reproduces PME results for water property calculations of density, diffusion constant, dielectric constant, surface tension, radial distribution function, and distance-dependent Kirkwood factor, even though the numerical accuracy of PME is higher than that of MSM. Excellent agreement between MSM and PME is found also for interface potentials of air–water and membrane–water interfaces, where long-range Coulombic interactions are crucial. Applications demonstrate also the suitability of MSM for systems with semiperiodic and nonperiodic boundaries. For this purpose, simulations have been performed with periodic boundaries along directions parallel to a membrane surface but not along the surface normal, yielding membrane pore formation induced by an imbalance of charge across the membrane. Using a similar semiperiodic boundary condition, ion conduction through a graphene nanopore driven by an ion gradient has been simulated. Furthermore, proteins have been simulated inside a single spherical water droplet. Finally, parallel scalability results show the ability of MSM to outperform PME when scaling a system of modest size (less than 100 K atoms) to over a thousand processors, demonstrating the suitability of MSM for large-scale parallel simulation.

Space Technology 5 Multi-Point Observations of Temporal Variability of Field-Aligned Currents

NASA Technical Reports Server (NTRS)

Le, Guan; Wang, Yongli; Slavin, James A.; Strangeway, Robert J.

2008-01-01

Space Technology 5 (ST5) is a three micro-satellite constellation deployed into a 300 x 4500 km, dawn-dusk, sun-synchronous polar orbit from March 22 to June 21, 2006, for technology validations. In this paper, we present a study of the temporal variability of field-aligned currents using multi-point magnetic field measurements from ST5. The data demonstrate that meso-scale current structures are commonly embedded within large-scale field-aligned current sheets. The meso-scale current structures are very dynamic with highly variable current density and/or polarity in time scales of approximately 10 min. They exhibit large temporal variations during both quiet and disturbed times in such time scales. On the other hand, the data also shown that the time scales for the currents to be relatively stable are approximately 1 min for meso-scale currents and approximately 10 min for large scale current sheets. These temporal features are obviously associated with dynamic variations of their particle carriers (mainly electrons) as they respond to the variations of the parallel electric field in auroral acceleration region. The characteristic time scales for the temporal variability of meso-scale field-aligned currents are found to be consistent with those of auroral parallel electric field.

fast_protein_cluster: parallel and optimized clustering of large-scale protein modeling data.

PubMed

Hung, Ling-Hong; Samudrala, Ram

2014-06-15

fast_protein_cluster is a fast, parallel and memory efficient package used to cluster 60 000 sets of protein models (with up to 550 000 models per set) generated by the Nutritious Rice for the World project. fast_protein_cluster is an optimized and extensible toolkit that supports Root Mean Square Deviation after optimal superposition (RMSD) and Template Modeling score (TM-score) as metrics. RMSD calculations using a laptop CPU are 60× faster than qcprot and 3× faster than current graphics processing unit (GPU) implementations. New GPU code further increases the speed of RMSD and TM-score calculations. fast_protein_cluster provides novel k-means and hierarchical clustering methods that are up to 250× and 2000× faster, respectively, than Clusco, and identify significantly more accurate models than Spicker and Clusco. fast_protein_cluster is written in C++ using OpenMP for multi-threading support. Custom streaming Single Instruction Multiple Data (SIMD) extensions and advanced vector extension intrinsics code accelerate CPU calculations, and OpenCL kernels support AMD and Nvidia GPUs. fast_protein_cluster is available under the M.I.T. license. (http://software.compbio.washington.edu/fast_protein_cluster) © The Author 2014. Published by Oxford University Press.

Regional-scale calculation of the LS factor using parallel processing

NASA Astrophysics Data System (ADS)

Liu, Kai; Tang, Guoan; Jiang, Ling; Zhu, A.-Xing; Yang, Jianyi; Song, Xiaodong

2015-05-01

With the increase of data resolution and the increasing application of USLE over large areas, the existing serial implementation of algorithms for computing the LS factor is becoming a bottleneck. In this paper, a parallel processing model based on message passing interface (MPI) is presented for the calculation of the LS factor, so that massive datasets at a regional scale can be processed efficiently. The parallel model contains algorithms for calculating flow direction, flow accumulation, drainage network, slope, slope length and the LS factor. According to the existence of data dependence, the algorithms are divided into local algorithms and global algorithms. Parallel strategy are designed according to the algorithm characters including the decomposition method for maintaining the integrity of the results, optimized workflow for reducing the time taken for exporting the unnecessary intermediate data and a buffer-communication-computation strategy for improving the communication efficiency. Experiments on a multi-node system show that the proposed parallel model allows efficient calculation of the LS factor at a regional scale with a massive dataset.

ION ACCELERATION AT THE QUASI-PARALLEL BOW SHOCK: DECODING THE SIGNATURE OF INJECTION

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sundberg, Torbjörn; Haynes, Christopher T.; Burgess, D.

Collisionless shocks are efficient particle accelerators. At Earth, ions with energies exceeding 100 keV are seen upstream of the bow shock when the magnetic geometry is quasi-parallel, and large-scale supernova remnant shocks can accelerate ions into cosmic-ray energies. This energization is attributed to diffusive shock acceleration; however, for this process to become active, the ions must first be sufficiently energized. How and where this initial acceleration takes place has been one of the key unresolved issues in shock acceleration theory. Using Cluster spacecraft observations, we study the signatures of ion reflection events in the turbulent transition layer upstream of the terrestrial bowmore » shock, and with the support of a hybrid simulation of the shock, we show that these reflection signatures are characteristic of the first step in the ion injection process. These reflection events develop in particular in the region where the trailing edge of large-amplitude upstream waves intercept the local shock ramp and the upstream magnetic field changes from quasi-perpendicular to quasi-parallel. The dispersed ion velocity signature observed can be attributed to a rapid succession of ion reflections at this wave boundary. After the ions’ initial interaction with the shock, they flow upstream along the quasi-parallel magnetic field. Each subsequent wavefront in the upstream region will sweep the ions back toward the shock, where they gain energy with each transition between the upstream and the shock wave frames. Within three to five gyroperiods, some ions have gained enough parallel velocity to escape upstream, thus completing the injection process.« less

Approaching the exa-scale: a real-world evaluation of rendering extremely large data sets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Patchett, John M; Ahrens, James P; Lo, Li - Ta

2010-10-15

Extremely large scale analysis is becoming increasingly important as supercomputers and their simulations move from petascale to exascale. The lack of dedicated hardware acceleration for rendering on today's supercomputing platforms motivates our detailed evaluation of the possibility of interactive rendering on the supercomputer. In order to facilitate our understanding of rendering on the supercomputing platform, we focus on scalability of rendering algorithms and architecture envisioned for exascale datasets. To understand tradeoffs for dealing with extremely large datasets, we compare three different rendering algorithms for large polygonal data: software based ray tracing, software based rasterization and hardware accelerated rasterization. We presentmore » a case study of strong and weak scaling of rendering extremely large data on both GPU and CPU based parallel supercomputers using Para View, a parallel visualization tool. Wc use three different data sets: two synthetic and one from a scientific application. At an extreme scale, algorithmic rendering choices make a difference and should be considered while approaching exascale computing, visualization, and analysis. We find software based ray-tracing offers a viable approach for scalable rendering of the projected future massive data sizes.« less

Design and Implementation of a Parallel Multivariate Ensemble Kalman Filter for the Poseidon Ocean General Circulation Model

NASA Technical Reports Server (NTRS)

Keppenne, Christian L.; Rienecker, Michele M.; Koblinsky, Chester (Technical Monitor)

2001-01-01

A multivariate ensemble Kalman filter (MvEnKF) implemented on a massively parallel computer architecture has been implemented for the Poseidon ocean circulation model and tested with a Pacific Basin model configuration. There are about two million prognostic state-vector variables. Parallelism for the data assimilation step is achieved by regionalization of the background-error covariances that are calculated from the phase-space distribution of the ensemble. Each processing element (PE) collects elements of a matrix measurement functional from nearby PEs. To avoid the introduction of spurious long-range covariances associated with finite ensemble sizes, the background-error covariances are given compact support by means of a Hadamard (element by element) product with a three-dimensional canonical correlation function. The methodology and the MvEnKF configuration are discussed. It is shown that the regionalization of the background covariances; has a negligible impact on the quality of the analyses. The parallel algorithm is very efficient for large numbers of observations but does not scale well beyond 100 PEs at the current model resolution. On a platform with distributed memory, memory rather than speed is the limiting factor.

Parallel Computing for Probabilistic Response Analysis of High Temperature Composites

NASA Technical Reports Server (NTRS)

Sues, R. H.; Lua, Y. J.; Smith, M. D.

1994-01-01

The objective of this Phase I research was to establish the required software and hardware strategies to achieve large scale parallelism in solving PCM problems. To meet this objective, several investigations were conducted. First, we identified the multiple levels of parallelism in PCM and the computational strategies to exploit these parallelisms. Next, several software and hardware efficiency investigations were conducted. These involved the use of three different parallel programming paradigms and solution of two example problems on both a shared-memory multiprocessor and a distributed-memory network of workstations.

Hierarchical Parallelism in Finite Difference Analysis of Heat Conduction

NASA Technical Reports Server (NTRS)

Padovan, Joseph; Krishna, Lala; Gute, Douglas

1997-01-01

Based on the concept of hierarchical parallelism, this research effort resulted in highly efficient parallel solution strategies for very large scale heat conduction problems. Overall, the method of hierarchical parallelism involves the partitioning of thermal models into several substructured levels wherein an optimal balance into various associated bandwidths is achieved. The details are described in this report. Overall, the report is organized into two parts. Part 1 describes the parallel modelling methodology and associated multilevel direct, iterative and mixed solution schemes. Part 2 establishes both the formal and computational properties of the scheme.

Space Technology 5 (ST-5) Observations of Field-Aligned Currents: Temporal Variability

NASA Technical Reports Server (NTRS)

Le, Guan

2010-01-01

Space Technology 5 (ST-5) is a three micro-satellite constellation deployed into a 300 x 4500 km, dawn-dusk, sun-synchronous polar orbit from March 22 to June 21, 2006, for technology validations. In this paper, we present a study of the temporal variability of field-aligned currents using multi-point magnetic field measurements from STS. The data demonstrate that masoscale current structures are commonly embedded within large-scale field-aligned current sheets. The meso-scale current structures are very dynamic with highly variable current density and/or polarity in time scales of about 10 min. They exhibit large temporal variations during both quiet and disturbed times in such time scales. On the other hand, the data also shown that the time scales for the currents to be relatively stable are about I min for meso-scale currents and about 10 min for large scale current sheets. These temporal features are obviously associated with dynamic variations of their particle carriers (mainly electrons) as they respond to the variations of the parallel electric field in auroral acceleration region. The characteristic time scales for the temporal variability of meso-scale field-aligned currents are found to be consistent with those of auroral parallel electric field.

Space Technology 5 (ST-5) Multipoint Observations of Temporal and Spatial Variability of Field-Aligned Currents

NASA Technical Reports Server (NTRS)

Le, Guan

2010-01-01

Space Technology 5 (ST-5) is a three micro-satellite constellation deployed into a 300 x 4500 km, dawn-dusk, sun-synchronous polar orbit from March 22 to June 21, 2006, for technology validations. In this paper, we present a study of the temporal variability of field-aligned currents using multi-point magnetic field measurements from ST5. The data demonstrate that mesoscale current structures are commonly embedded within large-scale field-aligned current sheets. The meso-scale current structures are very dynamic with highly variable current density and/or polarity in time scales of about 10 min. They exhibit large temporal variations during both quiet and disturbed times in such time scales. On the other hand, the data also shown that the time scales for the currents to be relatively stable are about 1 min for meso-scale currents and about 10 min for large scale current sheets. These temporal features are obviously associated with dynamic variations of their particle carriers (mainly electrons) as they respond to the variations of the parallel electric field in auroral acceleration region. The characteristic time scales for the temporal variability of meso-scale field-aligned currents are found to be consistent with those of auroral parallel electric field.

New synchrotron powder diffraction facility for long-duration experiments

PubMed Central

Murray, Claire A.; Potter, Jonathan; Day, Sarah J.; Baker, Annabelle R.; Thompson, Stephen P.; Kelly, Jon; Morris, Christopher G.; Tang, Chiu C.

2017-01-01

A new synchrotron X-ray powder diffraction instrument has been built and commissioned for long-duration experiments on beamline I11 at Diamond Light Source. The concept is unique, with design features to house multiple experiments running in parallel, in particular with specific stages for sample environments to study slow kinetic systems or processes. The instrument benefits from a high-brightness X-ray beam and a large area detector. Diffraction data from the commissioning work have shown that the objectives and criteria are met. Supported by two case studies, the results from months of measurements have demonstrated the viability of this large-scale instrument, which is the world’s first dedicated facility for long-term studies (weeks to years) using synchrotron radiation. PMID:28190992

Trace: a high-throughput tomographic reconstruction engine for large-scale datasets.

PubMed

Bicer, Tekin; Gürsoy, Doğa; Andrade, Vincent De; Kettimuthu, Rajkumar; Scullin, William; Carlo, Francesco De; Foster, Ian T

2017-01-01

Modern synchrotron light sources and detectors produce data at such scale and complexity that large-scale computation is required to unleash their full power. One of the widely used imaging techniques that generates data at tens of gigabytes per second is computed tomography (CT). Although CT experiments result in rapid data generation, the analysis and reconstruction of the collected data may require hours or even days of computation time with a medium-sized workstation, which hinders the scientific progress that relies on the results of analysis. We present Trace, a data-intensive computing engine that we have developed to enable high-performance implementation of iterative tomographic reconstruction algorithms for parallel computers. Trace provides fine-grained reconstruction of tomography datasets using both (thread-level) shared memory and (process-level) distributed memory parallelization. Trace utilizes a special data structure called replicated reconstruction object to maximize application performance. We also present the optimizations that we apply to the replicated reconstruction objects and evaluate them using tomography datasets collected at the Advanced Photon Source. Our experimental evaluations show that our optimizations and parallelization techniques can provide 158× speedup using 32 compute nodes (384 cores) over a single-core configuration and decrease the end-to-end processing time of a large sinogram (with 4501 × 1 × 22,400 dimensions) from 12.5 h to <5 min per iteration. The proposed tomographic reconstruction engine can efficiently process large-scale tomographic data using many compute nodes and minimize reconstruction times.

Magnetic intermittency of solar wind turbulence in the dissipation range

NASA Astrophysics Data System (ADS)

Pei, Zhongtian; He, Jiansen; Tu, Chuanyi; Marsch, Eckart; Wang, Linghua

2016-04-01

The feature, nature, and fate of intermittency in the dissipation range are an interesting topic in the solar wind turbulence. We calculate the distribution of flatness for the magnetic field fluctuations as a functionof angle and scale. The flatness distribution shows a "butterfly" pattern, with two wings located at angles parallel/anti-parallel to local mean magnetic field direction and main body located at angles perpendicular to local B0. This "butterfly" pattern illustrates that the flatness profile in (anti-) parallel direction approaches to the maximum value at larger scale and drops faster than that in perpendicular direction. The contours for probability distribution functions at different scales illustrate a "vase" pattern, more clear in parallel direction, which confirms the scale-variation of flatness and indicates the intermittency generation and dissipation. The angular distribution of structure function in the dissipation range shows an anisotropic pattern. The quasi-mono-fractal scaling of structure function in the dissipation range is also illustrated and investigated with the mathematical model for inhomogeneous cascading (extended p-model). Different from the inertial range, the extended p-model for the dissipation range results in approximate uniform fragmentation measure. However, more complete mathematicaland physical model involving both non-uniform cascading and dissipation is needed. The nature of intermittency may be strong structures or large amplitude fluctuations, which may be tested with magnetic helicity. In one case study, we find the heating effect in terms of entropy for large amplitude fluctuations seems to be more obvious than strong structures.

DGDFT: A massively parallel method for large scale density functional theory calculations.

PubMed

Hu, Wei; Lin, Lin; Yang, Chao

2015-09-28

We describe a massively parallel implementation of the recently developed discontinuous Galerkin density functional theory (DGDFT) method, for efficient large-scale Kohn-Sham DFT based electronic structure calculations. The DGDFT method uses adaptive local basis (ALB) functions generated on-the-fly during the self-consistent field iteration to represent the solution to the Kohn-Sham equations. The use of the ALB set provides a systematic way to improve the accuracy of the approximation. By using the pole expansion and selected inversion technique to compute electron density, energy, and atomic forces, we can make the computational complexity of DGDFT scale at most quadratically with respect to the number of electrons for both insulating and metallic systems. We show that for the two-dimensional (2D) phosphorene systems studied here, using 37 basis functions per atom allows us to reach an accuracy level of 1.3 × 10(-4) Hartree/atom in terms of the error of energy and 6.2 × 10(-4) Hartree/bohr in terms of the error of atomic force, respectively. DGDFT can achieve 80% parallel efficiency on 128,000 high performance computing cores when it is used to study the electronic structure of 2D phosphorene systems with 3500-14 000 atoms. This high parallel efficiency results from a two-level parallelization scheme that we will describe in detail.

Institutional Computing Executive Group Review of Multi-programmatic & Institutional Computing, Fiscal Year 2005 and 2006

DOE Office of Scientific and Technical Information (OSTI.GOV)

Langer, S; Rotman, D; Schwegler, E

The Institutional Computing Executive Group (ICEG) review of FY05-06 Multiprogrammatic and Institutional Computing (M and IC) activities is presented in the attached report. In summary, we find that the M and IC staff does an outstanding job of acquiring and supporting a wide range of institutional computing resources to meet the programmatic and scientific goals of LLNL. The responsiveness and high quality of support given to users and the programs investing in M and IC reflects the dedication and skill of the M and IC staff. M and IC has successfully managed serial capacity, parallel capacity, and capability computing resources.more » Serial capacity computing supports a wide range of scientific projects which require access to a few high performance processors within a shared memory computer. Parallel capacity computing supports scientific projects that require a moderate number of processors (up to roughly 1000) on a parallel computer. Capability computing supports parallel jobs that push the limits of simulation science. M and IC has worked closely with Stockpile Stewardship, and together they have made LLNL a premier institution for computational and simulation science. Such a standing is vital to the continued success of laboratory science programs and to the recruitment and retention of top scientists. This report provides recommendations to build on M and IC's accomplishments and improve simulation capabilities at LLNL. We recommend that institution fully fund (1) operation of the atlas cluster purchased in FY06 to support a few large projects; (2) operation of the thunder and zeus clusters to enable 'mid-range' parallel capacity simulations during normal operation and a limited number of large simulations during dedicated application time; (3) operation of the new yana cluster to support a wide range of serial capacity simulations; (4) improvements to the reliability and performance of the Lustre parallel file system; (5) support for the new GDO petabyte-class storage facility on the green network for use in data intensive external collaborations; and (6) continued support for visualization and other methods for analyzing large simulations. We also recommend that M and IC begin planning in FY07 for the next upgrade of its parallel clusters. LLNL investments in M and IC have resulted in a world-class simulation capability leading to innovative science. We thank the LLNL management for its continued support and thank the M and IC staff for its vision and dedicated efforts to make it all happen.« less

The NAS parallel benchmarks

NASA Technical Reports Server (NTRS)

Bailey, David (Editor); Barton, John (Editor); Lasinski, Thomas (Editor); Simon, Horst (Editor)

1993-01-01

A new set of benchmarks was developed for the performance evaluation of highly parallel supercomputers. These benchmarks consist of a set of kernels, the 'Parallel Kernels,' and a simulated application benchmark. Together they mimic the computation and data movement characteristics of large scale computational fluid dynamics (CFD) applications. The principal distinguishing feature of these benchmarks is their 'pencil and paper' specification - all details of these benchmarks are specified only algorithmically. In this way many of the difficulties associated with conventional benchmarking approaches on highly parallel systems are avoided.

A scalable PC-based parallel computer for lattice QCD

NASA Astrophysics Data System (ADS)

Fodor, Z.; Katz, S. D.; Pappa, G.

2003-05-01

A PC-based parallel computer for medium/large scale lattice QCD simulations is suggested. The Eo¨tvo¨s Univ., Inst. Theor. Phys. cluster consists of 137 Intel P4-1.7GHz nodes. Gigabit Ethernet cards are used for nearest neighbor communication in a two-dimensional mesh. The sustained performance for dynamical staggered (wilson) quarks on large lattices is around 70(110) GFlops. The exceptional price/performance ratio is below $1/Mflop.

Knowledge Support and Automation for Performance Analysis with PerfExplorer 2.0

DOE PAGES

Huck, Kevin A.; Malony, Allen D.; Shende, Sameer; ...

2008-01-01

The integration of scalable performance analysis in parallel development tools is difficult. The potential size of data sets and the need to compare results from multiple experiments presents a challenge to manage and process the information. Simply to characterize the performance of parallel applications running on potentially hundreds of thousands of processor cores requires new scalable analysis techniques. Furthermore, many exploratory analysis processes are repeatable and could be automated, but are now implemented as manual procedures. In this paper, we will discuss the current version of PerfExplorer, a performance analysis framework which provides dimension reduction, clustering and correlation analysis ofmore » individual trails of large dimensions, and can perform relative performance analysis between multiple application executions. PerfExplorer analysis processes can be captured in the form of Python scripts, automating what would otherwise be time-consuming tasks. We will give examples of large-scale analysis results, and discuss the future development of the framework, including the encoding and processing of expert performance rules, and the increasing use of performance metadata.« less

Deep crustal deformation by sheath folding in the Adirondack Mountains, USA

NASA Technical Reports Server (NTRS)

Mclelland, J. M.

1988-01-01

As described by McLelland and Isachsen, the southern half of the Adirondacks are underlain by major isoclinal (F sub 1) and open-upright (F sub 2) folds whose axes are parallel, trend approximately E-W, and plunge gently about the horizontal. These large structures are themselves folded by open upright folds trending NNE (F sub 3). It is pointed out that elongation lineations in these rocks are parallel to X of the finite strain ellipsoid developed during progressive rotational strain. The parallelism between F sub 1 and F sub 2 fold axes and elongation lineations led to the hypothesis that progressive rotational strain, with a west-directed tectonic transport, rotated earlier F sub 1-folds into parallelism with the evolving elongation lineation. Rotation is accomplished by ductile, passive flow of F sub 1-axes into extremely arcuate, E-W hinges. In order to test these hypotheses a number of large folds were mapped in the eastern Adirondacks. Other evidence supporting the existence of sheath folds in the Adirondacks is the presence, on a map scale, of synforms whose limbs pass through the vertical and into antiforms. This type of outcrop pattern is best explained by intersecting a horizontal plane with the double curvature of sheath folds. It is proposed that sheath folding is a common response of hot, ductile rocks to rotational strain at deep crustal levels. The recognition of sheath folds in the Adirondacks reconciles the E-W orientation of fold axes with an E-W elongation lineation.

The International Conference on Vector and Parallel Computing (2nd)

DTIC Science & Technology

1989-01-17

Computation of the SVD of Bidiagonal Matrices" ...................................... 11 " Lattice QCD -As a Large Scale Scientific Computation...vectorizcd for the IBM 3090 Vector Facility. In addition, elapsed times " Lattice QCD -As a Large Scale Scientific have been reduced by using 3090...benchmarked Lattice QCD on a large number ofcompu- come from the wavefront solver routine. This was exten- ters: CrayX-MP and Cray 2 (vector

Fast and Accurate Support Vector Machines on Large Scale Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vishnu, Abhinav; Narasimhan, Jayenthi; Holder, Larry

Support Vector Machines (SVM) is a supervised Machine Learning and Data Mining (MLDM) algorithm, which has become ubiquitous largely due to its high accuracy and obliviousness to dimensionality. The objective of SVM is to find an optimal boundary --- also known as hyperplane --- which separates the samples (examples in a dataset) of different classes by a maximum margin. Usually, very few samples contribute to the definition of the boundary. However, existing parallel algorithms use the entire dataset for finding the boundary, which is sub-optimal for performance reasons. In this paper, we propose a novel distributed memory algorithm to eliminatemore » the samples which do not contribute to the boundary definition in SVM. We propose several heuristics, which range from early (aggressive) to late (conservative) elimination of the samples, such that the overall time for generating the boundary is reduced considerably. In a few cases, a sample may be eliminated (shrunk) pre-emptively --- potentially resulting in an incorrect boundary. We propose a scalable approach to synchronize the necessary data structures such that the proposed algorithm maintains its accuracy. We consider the necessary trade-offs of single/multiple synchronization using in-depth time-space complexity analysis. We implement the proposed algorithm using MPI and compare it with libsvm--- de facto sequential SVM software --- which we enhance with OpenMP for multi-core/many-core parallelism. Our proposed approach shows excellent efficiency using up to 4096 processes on several large datasets such as UCI HIGGS Boson dataset and Offending URL dataset.« less

Scaling Up Coordinate Descent Algorithms for Large ℓ1 Regularization Problems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Scherrer, Chad; Halappanavar, Mahantesh; Tewari, Ambuj

2012-07-03

We present a generic framework for parallel coordinate descent (CD) algorithms that has as special cases the original sequential algorithms of Cyclic CD and Stochastic CD, as well as the recent parallel Shotgun algorithm of Bradley et al. We introduce two novel parallel algorithms that are also special cases---Thread-Greedy CD and Coloring-Based CD---and give performance measurements for an OpenMP implementation of these.

A new parallel-vector finite element analysis software on distributed-memory computers

NASA Technical Reports Server (NTRS)

Qin, Jiangning; Nguyen, Duc T.

1993-01-01

A new parallel-vector finite element analysis software package MPFEA (Massively Parallel-vector Finite Element Analysis) is developed for large-scale structural analysis on massively parallel computers with distributed-memory. MPFEA is designed for parallel generation and assembly of the global finite element stiffness matrices as well as parallel solution of the simultaneous linear equations, since these are often the major time-consuming parts of a finite element analysis. Block-skyline storage scheme along with vector-unrolling techniques are used to enhance the vector performance. Communications among processors are carried out concurrently with arithmetic operations to reduce the total execution time. Numerical results on the Intel iPSC/860 computers (such as the Intel Gamma with 128 processors and the Intel Touchstone Delta with 512 processors) are presented, including an aircraft structure and some very large truss structures, to demonstrate the efficiency and accuracy of MPFEA.

Sparse Partial Equilibrium Tables in Chemically Resolved Reactive Flow

NASA Astrophysics Data System (ADS)

Vitello, Peter; Fried, Laurence E.; Pudliner, Brian; McAbee, Tom

2004-07-01

The detonation of an energetic material is the result of a complex interaction between kinetic chemical reactions and hydrodynamics. Unfortunately, little is known concerning the detailed chemical kinetics of detonations in energetic materials. CHEETAH uses rate laws to treat species with the slowest chemical reactions, while assuming other chemical species are in equilibrium. CHEETAH supports a wide range of elements and condensed detonation products and can also be applied to gas detonations. A sparse hash table of equation of state values is used in CHEETAH to enhance the efficiency of kinetic reaction calculations. For large-scale parallel hydrodynamic calculations, CHEETAH uses parallel communication to updates to the cache. We present here details of the sparse caching model used in the CHEETAH coupled to an ALE hydrocode. To demonstrate the efficiency of modeling using a sparse cache model we consider detonations in energetic materials.

ls1 mardyn: The Massively Parallel Molecular Dynamics Code for Large Systems.

PubMed

Niethammer, Christoph; Becker, Stefan; Bernreuther, Martin; Buchholz, Martin; Eckhardt, Wolfgang; Heinecke, Alexander; Werth, Stephan; Bungartz, Hans-Joachim; Glass, Colin W; Hasse, Hans; Vrabec, Jadran; Horsch, Martin

2014-10-14

The molecular dynamics simulation code ls1 mardyn is presented. It is a highly scalable code, optimized for massively parallel execution on supercomputing architectures and currently holds the world record for the largest molecular simulation with over four trillion particles. It enables the application of pair potentials to length and time scales that were previously out of scope for molecular dynamics simulation. With an efficient dynamic load balancing scheme, it delivers high scalability even for challenging heterogeneous configurations. Presently, multicenter rigid potential models based on Lennard-Jones sites, point charges, and higher-order polarities are supported. Due to its modular design, ls1 mardyn can be extended to new physical models, methods, and algorithms, allowing future users to tailor it to suit their respective needs. Possible applications include scenarios with complex geometries, such as fluids at interfaces, as well as nonequilibrium molecular dynamics simulation of heat and mass transfer.

Accelerating Large Scale Image Analyses on Parallel, CPU-GPU Equipped Systems

PubMed Central

Teodoro, George; Kurc, Tahsin M.; Pan, Tony; Cooper, Lee A.D.; Kong, Jun; Widener, Patrick; Saltz, Joel H.

2014-01-01

The past decade has witnessed a major paradigm shift in high performance computing with the introduction of accelerators as general purpose processors. These computing devices make available very high parallel computing power at low cost and power consumption, transforming current high performance platforms into heterogeneous CPU-GPU equipped systems. Although the theoretical performance achieved by these hybrid systems is impressive, taking practical advantage of this computing power remains a very challenging problem. Most applications are still deployed to either GPU or CPU, leaving the other resource under- or un-utilized. In this paper, we propose, implement, and evaluate a performance aware scheduling technique along with optimizations to make efficient collaborative use of CPUs and GPUs on a parallel system. In the context of feature computations in large scale image analysis applications, our evaluations show that intelligently co-scheduling CPUs and GPUs can significantly improve performance over GPU-only or multi-core CPU-only approaches. PMID:25419545

A study of the parallel algorithm for large-scale DC simulation of nonlinear systems

NASA Astrophysics Data System (ADS)

Cortés Udave, Diego Ernesto; Ogrodzki, Jan; Gutiérrez de Anda, Miguel Angel

Newton-Raphson DC analysis of large-scale nonlinear circuits may be an extremely time consuming process even if sparse matrix techniques and bypassing of nonlinear models calculation are used. A slight decrease in the time required for this task may be enabled on multi-core, multithread computers if the calculation of the mathematical models for the nonlinear elements as well as the stamp management of the sparse matrix entries are managed through concurrent processes. This numerical complexity can be further reduced via the circuit decomposition and parallel solution of blocks taking as a departure point the BBD matrix structure. This block-parallel approach may give a considerable profit though it is strongly dependent on the system topology and, of course, on the processor type. This contribution presents the easy-parallelizable decomposition-based algorithm for DC simulation and provides a detailed study of its effectiveness.

Computational Issues in Damping Identification for Large Scale Problems

NASA Technical Reports Server (NTRS)

Pilkey, Deborah L.; Roe, Kevin P.; Inman, Daniel J.

1997-01-01

Two damping identification methods are tested for efficiency in large-scale applications. One is an iterative routine, and the other a least squares method. Numerical simulations have been performed on multiple degree-of-freedom models to test the effectiveness of the algorithm and the usefulness of parallel computation for the problems. High Performance Fortran is used to parallelize the algorithm. Tests were performed using the IBM-SP2 at NASA Ames Research Center. The least squares method tested incurs high communication costs, which reduces the benefit of high performance computing. This method's memory requirement grows at a very rapid rate meaning that larger problems can quickly exceed available computer memory. The iterative method's memory requirement grows at a much slower pace and is able to handle problems with 500+ degrees of freedom on a single processor. This method benefits from parallelization, and significant speedup can he seen for problems of 100+ degrees-of-freedom.

A fully coupled method for massively parallel simulation of hydraulically driven fractures in 3-dimensions: FULLY COUPLED PARALLEL SIMULATION OF HYDRAULIC FRACTURES IN 3-D

DOE PAGES

Settgast, Randolph R.; Fu, Pengcheng; Walsh, Stuart D. C.; ...

2016-09-18

This study describes a fully coupled finite element/finite volume approach for simulating field-scale hydraulically driven fractures in three dimensions, using massively parallel computing platforms. The proposed method is capable of capturing realistic representations of local heterogeneities, layering and natural fracture networks in a reservoir. A detailed description of the numerical implementation is provided, along with numerical studies comparing the model with both analytical solutions and experimental results. The results demonstrate the effectiveness of the proposed method for modeling large-scale problems involving hydraulically driven fractures in three dimensions.

A fully coupled method for massively parallel simulation of hydraulically driven fractures in 3-dimensions: FULLY COUPLED PARALLEL SIMULATION OF HYDRAULIC FRACTURES IN 3-D

DOE Office of Scientific and Technical Information (OSTI.GOV)

Settgast, Randolph R.; Fu, Pengcheng; Walsh, Stuart D. C.

This study describes a fully coupled finite element/finite volume approach for simulating field-scale hydraulically driven fractures in three dimensions, using massively parallel computing platforms. The proposed method is capable of capturing realistic representations of local heterogeneities, layering and natural fracture networks in a reservoir. A detailed description of the numerical implementation is provided, along with numerical studies comparing the model with both analytical solutions and experimental results. The results demonstrate the effectiveness of the proposed method for modeling large-scale problems involving hydraulically driven fractures in three dimensions.

Accelerated Adaptive MGS Phase Retrieval

NASA Technical Reports Server (NTRS)

Lam, Raymond K.; Ohara, Catherine M.; Green, Joseph J.; Bikkannavar, Siddarayappa A.; Basinger, Scott A.; Redding, David C.; Shi, Fang

2011-01-01

The Modified Gerchberg-Saxton (MGS) algorithm is an image-based wavefront-sensing method that can turn any science instrument focal plane into a wavefront sensor. MGS characterizes optical systems by estimating the wavefront errors in the exit pupil using only intensity images of a star or other point source of light. This innovative implementation of MGS significantly accelerates the MGS phase retrieval algorithm by using stream-processing hardware on conventional graphics cards. Stream processing is a relatively new, yet powerful, paradigm to allow parallel processing of certain applications that apply single instructions to multiple data (SIMD). These stream processors are designed specifically to support large-scale parallel computing on a single graphics chip. Computationally intensive algorithms, such as the Fast Fourier Transform (FFT), are particularly well suited for this computing environment. This high-speed version of MGS exploits commercially available hardware to accomplish the same objective in a fraction of the original time. The exploit involves performing matrix calculations in nVidia graphic cards. The graphical processor unit (GPU) is hardware that is specialized for computationally intensive, highly parallel computation. From the software perspective, a parallel programming model is used, called CUDA, to transparently scale multicore parallelism in hardware. This technology gives computationally intensive applications access to the processing power of the nVidia GPUs through a C/C++ programming interface. The AAMGS (Accelerated Adaptive MGS) software takes advantage of these advanced technologies, to accelerate the optical phase error characterization. With a single PC that contains four nVidia GTX-280 graphic cards, the new implementation can process four images simultaneously to produce a JWST (James Webb Space Telescope) wavefront measurement 60 times faster than the previous code.

A Review of High-Performance Computational Strategies for Modeling and Imaging of Electromagnetic Induction Data

NASA Astrophysics Data System (ADS)

Newman, Gregory A.

2014-01-01

Many geoscientific applications exploit electrostatic and electromagnetic fields to interrogate and map subsurface electrical resistivity—an important geophysical attribute for characterizing mineral, energy, and water resources. In complex three-dimensional geologies, where many of these resources remain to be found, resistivity mapping requires large-scale modeling and imaging capabilities, as well as the ability to treat significant data volumes, which can easily overwhelm single-core and modest multicore computing hardware. To treat such problems requires large-scale parallel computational resources, necessary for reducing the time to solution to a time frame acceptable to the exploration process. The recognition that significant parallel computing processes must be brought to bear on these problems gives rise to choices that must be made in parallel computing hardware and software. In this review, some of these choices are presented, along with the resulting trade-offs. We also discuss future trends in high-performance computing and the anticipated impact on electromagnetic (EM) geophysics. Topics discussed in this review article include a survey of parallel computing platforms, graphics processing units to multicore CPUs with a fast interconnect, along with effective parallel solvers and associated solver libraries effective for inductive EM modeling and imaging.

Parallel distributed, reciprocal Monte Carlo radiation in coupled, large eddy combustion simulations

NASA Astrophysics Data System (ADS)

Hunsaker, Isaac L.

Radiation is the dominant mode of heat transfer in high temperature combustion environments. Radiative heat transfer affects the gas and particle phases, including all the associated combustion chemistry. The radiative properties are in turn affected by the turbulent flow field. This bi-directional coupling of radiation turbulence interactions poses a major challenge in creating parallel-capable, high-fidelity combustion simulations. In this work, a new model was developed in which reciprocal monte carlo radiation was coupled with a turbulent, large-eddy simulation combustion model. A technique wherein domain patches are stitched together was implemented to allow for scalable parallelism. The combustion model runs in parallel on a decomposed domain. The radiation model runs in parallel on a recomposed domain. The recomposed domain is stored on each processor after information sharing of the decomposed domain is handled via the message passing interface. Verification and validation testing of the new radiation model were favorable. Strong scaling analyses were performed on the Ember cluster and the Titan cluster for the CPU-radiation model and GPU-radiation model, respectively. The model demonstrated strong scaling to over 1,700 and 16,000 processing cores on Ember and Titan, respectively.

Towards Building a High Performance Spatial Query System for Large Scale Medical Imaging Data.

PubMed

Aji, Ablimit; Wang, Fusheng; Saltz, Joel H

2012-11-06

Support of high performance queries on large volumes of scientific spatial data is becoming increasingly important in many applications. This growth is driven by not only geospatial problems in numerous fields, but also emerging scientific applications that are increasingly data- and compute-intensive. For example, digital pathology imaging has become an emerging field during the past decade, where examination of high resolution images of human tissue specimens enables more effective diagnosis, prediction and treatment of diseases. Systematic analysis of large-scale pathology images generates tremendous amounts of spatially derived quantifications of micro-anatomic objects, such as nuclei, blood vessels, and tissue regions. Analytical pathology imaging provides high potential to support image based computer aided diagnosis. One major requirement for this is effective querying of such enormous amount of data with fast response, which is faced with two major challenges: the "big data" challenge and the high computation complexity. In this paper, we present our work towards building a high performance spatial query system for querying massive spatial data on MapReduce. Our framework takes an on demand index building approach for processing spatial queries and a partition-merge approach for building parallel spatial query pipelines, which fits nicely with the computing model of MapReduce. We demonstrate our framework on supporting multi-way spatial joins for algorithm evaluation and nearest neighbor queries for microanatomic objects. To reduce query response time, we propose cost based query optimization to mitigate the effect of data skew. Our experiments show that the framework can efficiently support complex analytical spatial queries on MapReduce.

Towards Building a High Performance Spatial Query System for Large Scale Medical Imaging Data

PubMed Central

Aji, Ablimit; Wang, Fusheng; Saltz, Joel H.

2013-01-01

Support of high performance queries on large volumes of scientific spatial data is becoming increasingly important in many applications. This growth is driven by not only geospatial problems in numerous fields, but also emerging scientific applications that are increasingly data- and compute-intensive. For example, digital pathology imaging has become an emerging field during the past decade, where examination of high resolution images of human tissue specimens enables more effective diagnosis, prediction and treatment of diseases. Systematic analysis of large-scale pathology images generates tremendous amounts of spatially derived quantifications of micro-anatomic objects, such as nuclei, blood vessels, and tissue regions. Analytical pathology imaging provides high potential to support image based computer aided diagnosis. One major requirement for this is effective querying of such enormous amount of data with fast response, which is faced with two major challenges: the “big data” challenge and the high computation complexity. In this paper, we present our work towards building a high performance spatial query system for querying massive spatial data on MapReduce. Our framework takes an on demand index building approach for processing spatial queries and a partition-merge approach for building parallel spatial query pipelines, which fits nicely with the computing model of MapReduce. We demonstrate our framework on supporting multi-way spatial joins for algorithm evaluation and nearest neighbor queries for microanatomic objects. To reduce query response time, we propose cost based query optimization to mitigate the effect of data skew. Our experiments show that the framework can efficiently support complex analytical spatial queries on MapReduce. PMID:24501719

Efficiency of parallel direct optimization

NASA Technical Reports Server (NTRS)

Janies, D. A.; Wheeler, W. C.

2001-01-01

Tremendous progress has been made at the level of sequential computation in phylogenetics. However, little attention has been paid to parallel computation. Parallel computing is particularly suited to phylogenetics because of the many ways large computational problems can be broken into parts that can be analyzed concurrently. In this paper, we investigate the scaling factors and efficiency of random addition and tree refinement strategies using the direct optimization software, POY, on a small (10 slave processors) and a large (256 slave processors) cluster of networked PCs running LINUX. These algorithms were tested on several data sets composed of DNA and morphology ranging from 40 to 500 taxa. Various algorithms in POY show fundamentally different properties within and between clusters. All algorithms are efficient on the small cluster for the 40-taxon data set. On the large cluster, multibuilding exhibits excellent parallel efficiency, whereas parallel building is inefficient. These results are independent of data set size. Branch swapping in parallel shows excellent speed-up for 16 slave processors on the large cluster. However, there is no appreciable speed-up for branch swapping with the further addition of slave processors (>16). This result is independent of data set size. Ratcheting in parallel is efficient with the addition of up to 32 processors in the large cluster. This result is independent of data set size. c2001 The Willi Hennig Society.

TRACING THE MAGNETIC FIELD MORPHOLOGY OF THE LUPUS I MOLECULAR CLOUD

DOE Office of Scientific and Technical Information (OSTI.GOV)

Franco, G. A. P.; Alves, F. O., E-mail: franco@fisica.ufmg.br, E-mail: falves@mpe.mpg.de

2015-07-01

Deep R-band CCD linear polarimetry collected for fields with lines of sight toward the Lupus I molecular cloud is used to investigate the properties of the magnetic field within this molecular cloud. The observed sample contains about 7000 stars, almost 2000 of them with a polarization signal-to-noise ratio larger than 5. These data cover almost the entire main molecular cloud and also sample two diffuse infrared patches in the neighborhood of Lupus I. The large-scale pattern of the plane-of-sky projection of the magnetic field is perpendicular to the main axis of Lupus I, but parallel to the two diffuse infraredmore » patches. A detailed analysis of our polarization data combined with the Herschel/SPIRE 350 μm dust emission map shows that the principal filament of Lupus I is constituted by three main clumps that are acted on by magnetic fields that have different large-scale structural properties. These differences may be the reason for the observed distribution of pre- and protostellar objects along the molecular cloud and the cloud’s apparent evolutionary stage. On the other hand, assuming that the magnetic field is composed of large-scale and turbulent components, we find that the latter is rather similar in all three clumps. The estimated plane-of-sky component of the large-scale magnetic field ranges from about 70 to 200 μG in these clumps. The intensity increases toward the Galactic plane. The mass-to-magnetic flux ratio is much smaller than unity, implying that Lupus I is magnetically supported on large scales.« less

Xyce Parallel Electronic Simulator Users Guide Version 6.2.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Keiter, Eric R.; Mei, Ting; Russo, Thomas V.

This manual describes the use of the Xyce Parallel Electronic Simulator. Xyce has been de- signed as a SPICE-compatible, high-performance analog circuit simulator, and has been written to support the simulation needs of the Sandia National Laboratories electrical designers. This development has focused on improving capability over the current state-of-the-art in the following areas: Capability to solve extremely large circuit problems by supporting large-scale parallel com- puting platforms (up to thousands of processors). This includes support for most popular parallel and serial computers. A differential-algebraic-equation (DAE) formulation, which better isolates the device model package from solver algorithms. This allows onemore » to develop new types of analysis without requiring the implementation of analysis-specific device models. Device models that are specifically tailored to meet Sandia's needs, including some radiation- aware devices (for Sandia users only). Object-oriented code design and implementation using modern coding practices. Xyce is a parallel code in the most general sense of the phrase -- a message passing parallel implementation -- which allows it to run efficiently a wide range of computing platforms. These include serial, shared-memory and distributed-memory parallel platforms. Attention has been paid to the specific nature of circuit-simulation problems to ensure that optimal parallel efficiency is achieved as the number of processors grows. Trademarks The information herein is subject to change without notice. Copyright c 2002-2014 Sandia Corporation. All rights reserved. Xyce TM Electronic Simulator and Xyce TM are trademarks of Sandia Corporation. Portions of the Xyce TM code are: Copyright c 2002, The Regents of the University of California. Produced at the Lawrence Livermore National Laboratory. Written by Alan Hindmarsh, Allan Taylor, Radu Serban. UCRL-CODE-2002-59 All rights reserved. Orcad, Orcad Capture, PSpice and Probe are registered trademarks of Cadence Design Systems, Inc. Microsoft, Windows and Windows 7 are registered trademarks of Microsoft Corporation. Medici, DaVinci and Taurus are registered trademarks of Synopsys Corporation. Amtec and TecPlot are trademarks of Amtec Engineering, Inc. Xyce 's expression library is based on that inside Spice 3F5 developed by the EECS Department at the University of California. The EKV3 MOSFET model was developed by the EKV Team of the Electronics Laboratory-TUC of the Technical University of Crete. All other trademarks are property of their respective owners. Contacts Bug Reports (Sandia only) http://joseki.sandia.gov/bugzilla http://charleston.sandia.gov/bugzilla World Wide Web http://xyce.sandia.gov http://charleston.sandia.gov/xyce (Sandia only) Email xyce@sandia.gov (outside Sandia) xyce-sandia@sandia.gov (Sandia only)« less

Xyce Parallel Electronic Simulator Users Guide Version 6.4

DOE Office of Scientific and Technical Information (OSTI.GOV)

Keiter, Eric R.; Mei, Ting; Russo, Thomas V.

This manual describes the use of the Xyce Parallel Electronic Simulator. Xyce has been de- signed as a SPICE-compatible, high-performance analog circuit simulator, and has been written to support the simulation needs of the Sandia National Laboratories electrical designers. This development has focused on improving capability over the current state-of-the-art in the following areas: Capability to solve extremely large circuit problems by supporting large-scale parallel com- puting platforms (up to thousands of processors). This includes support for most popular parallel and serial computers. A differential-algebraic-equation (DAE) formulation, which better isolates the device model package from solver algorithms. This allows onemore » to develop new types of analysis without requiring the implementation of analysis-specific device models. Device models that are specifically tailored to meet Sandia's needs, including some radiation- aware devices (for Sandia users only). Object-oriented code design and implementation using modern coding practices. Xyce is a parallel code in the most general sense of the phrase -- a message passing parallel implementation -- which allows it to run efficiently a wide range of computing platforms. These include serial, shared-memory and distributed-memory parallel platforms. Attention has been paid to the specific nature of circuit-simulation problems to ensure that optimal parallel efficiency is achieved as the number of processors grows. Trademarks The information herein is subject to change without notice. Copyright c 2002-2015 Sandia Corporation. All rights reserved. Xyce TM Electronic Simulator and Xyce TM are trademarks of Sandia Corporation. Portions of the Xyce TM code are: Copyright c 2002, The Regents of the University of California. Produced at the Lawrence Livermore National Laboratory. Written by Alan Hindmarsh, Allan Taylor, Radu Serban. UCRL-CODE-2002-59 All rights reserved. Orcad, Orcad Capture, PSpice and Probe are registered trademarks of Cadence Design Systems, Inc. Microsoft, Windows and Windows 7 are registered trademarks of Microsoft Corporation. Medici, DaVinci and Taurus are registered trademarks of Synopsys Corporation. Amtec and TecPlot are trademarks of Amtec Engineering, Inc. Xyce 's expression library is based on that inside Spice 3F5 developed by the EECS Department at the University of California. The EKV3 MOSFET model was developed by the EKV Team of the Electronics Laboratory-TUC of the Technical University of Crete. All other trademarks are property of their respective owners. Contacts Bug Reports (Sandia only) http://joseki.sandia.gov/bugzilla http://charleston.sandia.gov/bugzilla World Wide Web http://xyce.sandia.gov http://charleston.sandia.gov/xyce (Sandia only) Email xyce@sandia.gov (outside Sandia) xyce-sandia@sandia.gov (Sandia only)« less

Parallel algorithm for multiscale atomistic/continuum simulations using LAMMPS

NASA Astrophysics Data System (ADS)

Pavia, F.; Curtin, W. A.

2015-07-01

Deformation and fracture processes in engineering materials often require simultaneous descriptions over a range of length and time scales, with each scale using a different computational technique. Here we present a high-performance parallel 3D computing framework for executing large multiscale studies that couple an atomic domain, modeled using molecular dynamics and a continuum domain, modeled using explicit finite elements. We use the robust Coupled Atomistic/Discrete-Dislocation (CADD) displacement-coupling method, but without the transfer of dislocations between atoms and continuum. The main purpose of the work is to provide a multiscale implementation within an existing large-scale parallel molecular dynamics code (LAMMPS) that enables use of all the tools associated with this popular open-source code, while extending CADD-type coupling to 3D. Validation of the implementation includes the demonstration of (i) stability in finite-temperature dynamics using Langevin dynamics, (ii) elimination of wave reflections due to large dynamic events occurring in the MD region and (iii) the absence of spurious forces acting on dislocations due to the MD/FE coupling, for dislocations further than 10 Å from the coupling boundary. A first non-trivial example application of dislocation glide and bowing around obstacles is shown, for dislocation lengths of ∼50 nm using fewer than 1 000 000 atoms but reproducing results of extremely large atomistic simulations at much lower computational cost.

Neural Parallel Engine: A toolbox for massively parallel neural signal processing.

PubMed

Tam, Wing-Kin; Yang, Zhi

2018-05-01

Large-scale neural recordings provide detailed information on neuronal activities and can help elicit the underlying neural mechanisms of the brain. However, the computational burden is also formidable when we try to process the huge data stream generated by such recordings. In this study, we report the development of Neural Parallel Engine (NPE), a toolbox for massively parallel neural signal processing on graphical processing units (GPUs). It offers a selection of the most commonly used routines in neural signal processing such as spike detection and spike sorting, including advanced algorithms such as exponential-component-power-component (EC-PC) spike detection and binary pursuit spike sorting. We also propose a new method for detecting peaks in parallel through a parallel compact operation. Our toolbox is able to offer a 5× to 110× speedup compared with its CPU counterparts depending on the algorithms. A user-friendly MATLAB interface is provided to allow easy integration of the toolbox into existing workflows. Previous efforts on GPU neural signal processing only focus on a few rudimentary algorithms, are not well-optimized and often do not provide a user-friendly programming interface to fit into existing workflows. There is a strong need for a comprehensive toolbox for massively parallel neural signal processing. A new toolbox for massively parallel neural signal processing has been created. It can offer significant speedup in processing signals from large-scale recordings up to thousands of channels. Copyright © 2018 Elsevier B.V. All rights reserved.

Planetary-Scale Geospatial Data Analysis Techniques in Google's Earth Engine Platform (Invited)

NASA Astrophysics Data System (ADS)

Hancher, M.

2013-12-01

Geoscientists have more and more access to new tools for large-scale computing. With any tool, some tasks are easy and other tasks hard. It is natural to look to new computing platforms to increase the scale and efficiency of existing techniques, but there is a more exiting opportunity to discover and develop a new vocabulary of fundamental analysis idioms that are made easy and effective by these new tools. Google's Earth Engine platform is a cloud computing environment for earth data analysis that combines a public data catalog with a large-scale computational facility optimized for parallel processing of geospatial data. The data catalog includes a nearly complete archive of scenes from Landsat 4, 5, 7, and 8 that have been processed by the USGS, as well as a wide variety of other remotely-sensed and ancillary data products. Earth Engine supports a just-in-time computation model that enables real-time preview during algorithm development and debugging as well as during experimental data analysis and open-ended data exploration. Data processing operations are performed in parallel across many computers in Google's datacenters. The platform automatically handles many traditionally-onerous data management tasks, such as data format conversion, reprojection, resampling, and associating image metadata with pixel data. Early applications of Earth Engine have included the development of Google's global cloud-free fifteen-meter base map and global multi-decadal time-lapse animations, as well as numerous large and small experimental analyses by scientists from a range of academic, government, and non-governmental institutions, working in a wide variety of application areas including forestry, agriculture, urban mapping, and species habitat modeling. Patterns in the successes and failures of these early efforts have begun to emerge, sketching the outlines of a new set of simple and effective approaches to geospatial data analysis.

On the nature of the NAA diffusion attenuated MR signal in the central nervous system.

PubMed

Kroenke, Christopher D; Ackerman, Joseph J H; Yablonskiy, Dmitriy A

2004-11-01

In the brain, on a macroscopic scale, diffusion of the intraneuronal constituent N-acetyl-L-aspartate (NAA) appears to be isotropic. In contrast, on a microscopic scale, NAA diffusion is likely highly anisotropic, with displacements perpendicular to neuronal fibers being markedly hindered, and parallel displacements less so. In this report we first substantiate that local anisotropy influences NAA diffusion in vivo by observing differing diffusivities parallel and perpendicular to human corpus callosum axonal fibers. We then extend our measurements to large voxels within rat brains. As expected, the macroscopic apparent diffusion coefficient (ADC) of NAA is practically isotropic due to averaging of the numerous and diverse fiber orientations. We demonstrate that the substantially non-monoexponential diffusion-mediated MR signal decay vs. b value can be quantitatively explained by a theoretical model of NAA confined to an ensemble of differently oriented neuronal fibers. On the microscopic scale, NAA diffusion is found to be strongly anisotropic, with displacements occurring almost exclusively parallel to the local fiber axis. This parallel diffusivity, ADCparallel, is 0.36 +/- 0.01 microm2/ms, and ADCperpendicular is essentially zero. From ADCparallel the apparent viscosity of the neuron cytoplasm is estimated to be twice as large as that of a temperature-matched dilute aqueous solution. (c) 2004 Wiley-Liss, Inc.

Programming Probabilistic Structural Analysis for Parallel Processing Computer

NASA Technical Reports Server (NTRS)

Sues, Robert H.; Chen, Heh-Chyun; Twisdale, Lawrence A.; Chamis, Christos C.; Murthy, Pappu L. N.

1991-01-01

The ultimate goal of this research program is to make Probabilistic Structural Analysis (PSA) computationally efficient and hence practical for the design environment by achieving large scale parallelism. The paper identifies the multiple levels of parallelism in PSA, identifies methodologies for exploiting this parallelism, describes the development of a parallel stochastic finite element code, and presents results of two example applications. It is demonstrated that speeds within five percent of those theoretically possible can be achieved. A special-purpose numerical technique, the stochastic preconditioned conjugate gradient method, is also presented and demonstrated to be extremely efficient for certain classes of PSA problems.

Argonne simulation framework for intelligent transportation systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ewing, T.; Doss, E.; Hanebutte, U.

1996-04-01

A simulation framework has been developed which defines a high-level architecture for a large-scale, comprehensive, scalable simulation of an Intelligent Transportation System (ITS). The simulator is designed to run on parallel computers and distributed (networked) computer systems; however, a version for a stand alone workstation is also available. The ITS simulator includes an Expert Driver Model (EDM) of instrumented ``smart`` vehicles with in-vehicle navigation units. The EDM is capable of performing optimal route planning and communicating with Traffic Management Centers (TMC). A dynamic road map data base is sued for optimum route planning, where the data is updated periodically tomore » reflect any changes in road or weather conditions. The TMC has probe vehicle tracking capabilities (display position and attributes of instrumented vehicles), and can provide 2-way interaction with traffic to provide advisories and link times. Both the in-vehicle navigation module and the TMC feature detailed graphical user interfaces that includes human-factors studies to support safety and operational research. Realistic modeling of variations of the posted driving speed are based on human factor studies that take into consideration weather, road conditions, driver`s personality and behavior and vehicle type. The simulator has been developed on a distributed system of networked UNIX computers, but is designed to run on ANL`s IBM SP-X parallel computer system for large scale problems. A novel feature of the developed simulator is that vehicles will be represented by autonomous computer processes, each with a behavior model which performs independent route selection and reacts to external traffic events much like real vehicles. Vehicle processes interact with each other and with ITS components by exchanging messages. With this approach, one will be able to take advantage of emerging massively parallel processor (MPP) systems.« less

Parallel stitching of 2D materials

DOE PAGES

Ling, Xi; Wu, Lijun; Lin, Yuxuan; ...

2016-01-27

Diverse parallel stitched 2D heterostructures, including metal–semiconductor, semiconductor–semiconductor, and insulator–semiconductor, are synthesized directly through selective “sowing” of aromatic molecules as the seeds in the chemical vapor deposition (CVD) method. Lastly, the methodology enables the large-scale fabrication of lateral heterostructures, which offers tremendous potential for its application in integrated circuits.

Profiling and Improving I/O Performance of a Large-Scale Climate Scientific Application

NASA Technical Reports Server (NTRS)

Liu, Zhuo; Wang, Bin; Wang, Teng; Tian, Yuan; Xu, Cong; Wang, Yandong; Yu, Weikuan; Cruz, Carlos A.; Zhou, Shujia; Clune, Tom;

Disappearance of Anisotropic Intermittency in Large-amplitude MHD Turbulence and Its Comparison with Small-amplitude MHD Turbulence

NASA Astrophysics Data System (ADS)

Yang, Liping; Zhang, Lei; He, Jiansen; Tu, Chuanyi; Li, Shengtai; Wang, Xin; Wang, Linghua

2018-03-01

Multi-order structure functions in the solar wind are reported to display a monofractal scaling when sampled parallel to the local magnetic field and a multifractal scaling when measured perpendicularly. Whether and to what extent will the scaling anisotropy be weakened by the enhancement of turbulence amplitude relative to the background magnetic strength? In this study, based on two runs of the magnetohydrodynamic (MHD) turbulence simulation with different relative levels of turbulence amplitude, we investigate and compare the scaling of multi-order magnetic structure functions and magnetic probability distribution functions (PDFs) as well as their dependence on the direction of the local field. The numerical results show that for the case of large-amplitude MHD turbulence, the multi-order structure functions display a multifractal scaling at all angles to the local magnetic field, with PDFs deviating significantly from the Gaussian distribution and a flatness larger than 3 at all angles. In contrast, for the case of small-amplitude MHD turbulence, the multi-order structure functions and PDFs have different features in the quasi-parallel and quasi-perpendicular directions: a monofractal scaling and Gaussian-like distribution in the former, and a conversion of a monofractal scaling and Gaussian-like distribution into a multifractal scaling and non-Gaussian tail distribution in the latter. These results hint that when intermittencies are abundant and intense, the multifractal scaling in the structure functions can appear even if it is in the quasi-parallel direction; otherwise, the monofractal scaling in the structure functions remains even if it is in the quasi-perpendicular direction.

Linear-scaling density-functional simulations of charged point defects in Al2O3 using hierarchical sparse matrix algebra.

PubMed

Hine, N D M; Haynes, P D; Mostofi, A A; Payne, M C

2010-09-21

We present calculations of formation energies of defects in an ionic solid (Al(2)O(3)) extrapolated to the dilute limit, corresponding to a simulation cell of infinite size. The large-scale calculations required for this extrapolation are enabled by developments in the approach to parallel sparse matrix algebra operations, which are central to linear-scaling density-functional theory calculations. The computational cost of manipulating sparse matrices, whose sizes are determined by the large number of basis functions present, is greatly improved with this new approach. We present details of the sparse algebra scheme implemented in the ONETEP code using hierarchical sparsity patterns, and demonstrate its use in calculations on a wide range of systems, involving thousands of atoms on hundreds to thousands of parallel processes.

Combining points and lines in rectifying satellite images

NASA Astrophysics Data System (ADS)

Elaksher, Ahmed F.

2017-09-01

The quick advance in remote sensing technologies established the potential to gather accurate and reliable information about the Earth surface using high resolution satellite images. Remote sensing satellite images of less than one-meter pixel size are currently used in large-scale mapping. Rigorous photogrammetric equations are usually used to describe the relationship between the image coordinates and ground coordinates. These equations require the knowledge of the exterior and interior orientation parameters of the image that might not be available. On the other hand, the parallel projection transformation could be used to represent the mathematical relationship between the image-space and objectspace coordinate systems and provides the required accuracy for large-scale mapping using fewer ground control features. This article investigates the differences between point-based and line-based parallel projection transformation models in rectifying satellite images with different resolutions. The point-based parallel projection transformation model and its extended form are presented and the corresponding line-based forms are developed. Results showed that the RMS computed using the point- or line-based transformation models are equivalent and satisfy the requirement for large-scale mapping. The differences between the transformation parameters computed using the point- and line-based transformation models are insignificant. The results showed high correlation between the differences in the ground elevation and the RMS.

A highly scalable particle tracking algorithm using partitioned global address space (PGAS) programming for extreme-scale turbulence simulations

NASA Astrophysics Data System (ADS)

Buaria, D.; Yeung, P. K.

2017-12-01

A new parallel algorithm utilizing a partitioned global address space (PGAS) programming model to achieve high scalability is reported for particle tracking in direct numerical simulations of turbulent fluid flow. The work is motivated by the desire to obtain Lagrangian information necessary for the study of turbulent dispersion at the largest problem sizes feasible on current and next-generation multi-petaflop supercomputers. A large population of fluid particles is distributed among parallel processes dynamically, based on instantaneous particle positions such that all of the interpolation information needed for each particle is available either locally on its host process or neighboring processes holding adjacent sub-domains of the velocity field. With cubic splines as the preferred interpolation method, the new algorithm is designed to minimize the need for communication, by transferring between adjacent processes only those spline coefficients determined to be necessary for specific particles. This transfer is implemented very efficiently as a one-sided communication, using Co-Array Fortran (CAF) features which facilitate small data movements between different local partitions of a large global array. The cost of monitoring transfer of particle properties between adjacent processes for particles migrating across sub-domain boundaries is found to be small. Detailed benchmarks are obtained on the Cray petascale supercomputer Blue Waters at the University of Illinois, Urbana-Champaign. For operations on the particles in a 81923 simulation (0.55 trillion grid points) on 262,144 Cray XE6 cores, the new algorithm is found to be orders of magnitude faster relative to a prior algorithm in which each particle is tracked by the same parallel process at all times. This large speedup reduces the additional cost of tracking of order 300 million particles to just over 50% of the cost of computing the Eulerian velocity field at this scale. Improving support of PGAS models on major compilers suggests that this algorithm will be of wider applicability on most upcoming supercomputers.

Ropes: Support for collective opertions among distributed threads

NASA Technical Reports Server (NTRS)

Haines, Matthew; Mehrotra, Piyush; Cronk, David

1995-01-01

Lightweight threads are becoming increasingly useful in supporting parallelism and asynchronous control structures in applications and language implementations. Recently, systems have been designed and implemented to support interprocessor communication between lightweight threads so that threads can be exploited in a distributed memory system. Their use, in this setting, has been largely restricted to supporting latency hiding techniques and functional parallelism within a single application. However, to execute data parallel codes independent of other threads in the system, collective operations and relative indexing among threads are required. This paper describes the design of ropes: a scoping mechanism for collective operations and relative indexing among threads. We present the design of ropes in the context of the Chant system, and provide performance results evaluating our initial design decisions.

Vectorial finite elements for solving the radiative transfer equation

NASA Astrophysics Data System (ADS)

Badri, M. A.; Jolivet, P.; Rousseau, B.; Le Corre, S.; Digonnet, H.; Favennec, Y.

2018-06-01

The discrete ordinate method coupled with the finite element method is often used for the spatio-angular discretization of the radiative transfer equation. In this paper we attempt to improve upon such a discretization technique. Instead of using standard finite elements, we reformulate the radiative transfer equation using vectorial finite elements. In comparison to standard finite elements, this reformulation yields faster timings for the linear system assemblies, as well as for the solution phase when using scattering media. The proposed vectorial finite element discretization for solving the radiative transfer equation is cross-validated against a benchmark problem available in literature. In addition, we have used the method of manufactured solutions to verify the order of accuracy for our discretization technique within different absorbing, scattering, and emitting media. For solving large problems of radiation on parallel computers, the vectorial finite element method is parallelized using domain decomposition. The proposed domain decomposition method scales on large number of processes, and its performance is unaffected by the changes in optical thickness of the medium. Our parallel solver is used to solve a large scale radiative transfer problem of the Kelvin-cell radiation.

Parallel group independent component analysis for massive fMRI data sets.

PubMed

Chen, Shaojie; Huang, Lei; Qiu, Huitong; Nebel, Mary Beth; Mostofsky, Stewart H; Pekar, James J; Lindquist, Martin A; Eloyan, Ani; Caffo, Brian S

2017-01-01

Independent component analysis (ICA) is widely used in the field of functional neuroimaging to decompose data into spatio-temporal patterns of co-activation. In particular, ICA has found wide usage in the analysis of resting state fMRI (rs-fMRI) data. Recently, a number of large-scale data sets have become publicly available that consist of rs-fMRI scans from thousands of subjects. As a result, efficient ICA algorithms that scale well to the increased number of subjects are required. To address this problem, we propose a two-stage likelihood-based algorithm for performing group ICA, which we denote Parallel Group Independent Component Analysis (PGICA). By utilizing the sequential nature of the algorithm and parallel computing techniques, we are able to efficiently analyze data sets from large numbers of subjects. We illustrate the efficacy of PGICA, which has been implemented in R and is freely available through the Comprehensive R Archive Network, through simulation studies and application to rs-fMRI data from two large multi-subject data sets, consisting of 301 and 779 subjects respectively.

Large-scale optimization-based non-negative computational framework for diffusion equations: Parallel implementation and performance studies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chang, Justin; Karra, Satish; Nakshatrala, Kalyana B.

It is well-known that the standard Galerkin formulation, which is often the formulation of choice under the finite element method for solving self-adjoint diffusion equations, does not meet maximum principles and the non-negative constraint for anisotropic diffusion equations. Recently, optimization-based methodologies that satisfy maximum principles and the non-negative constraint for steady-state and transient diffusion-type equations have been proposed. To date, these methodologies have been tested only on small-scale academic problems. The purpose of this paper is to systematically study the performance of the non-negative methodology in the context of high performance computing (HPC). PETSc and TAO libraries are, respectively, usedmore » for the parallel environment and optimization solvers. For large-scale problems, it is important for computational scientists to understand the computational performance of current algorithms available in these scientific libraries. The numerical experiments are conducted on the state-of-the-art HPC systems, and a single-core performance model is used to better characterize the efficiency of the solvers. Furthermore, our studies indicate that the proposed non-negative computational framework for diffusion-type equations exhibits excellent strong scaling for real-world large-scale problems.« less

Large-scale optimization-based non-negative computational framework for diffusion equations: Parallel implementation and performance studies

DOE PAGES

Chang, Justin; Karra, Satish; Nakshatrala, Kalyana B.

2016-07-26

It is well-known that the standard Galerkin formulation, which is often the formulation of choice under the finite element method for solving self-adjoint diffusion equations, does not meet maximum principles and the non-negative constraint for anisotropic diffusion equations. Recently, optimization-based methodologies that satisfy maximum principles and the non-negative constraint for steady-state and transient diffusion-type equations have been proposed. To date, these methodologies have been tested only on small-scale academic problems. The purpose of this paper is to systematically study the performance of the non-negative methodology in the context of high performance computing (HPC). PETSc and TAO libraries are, respectively, usedmore » for the parallel environment and optimization solvers. For large-scale problems, it is important for computational scientists to understand the computational performance of current algorithms available in these scientific libraries. The numerical experiments are conducted on the state-of-the-art HPC systems, and a single-core performance model is used to better characterize the efficiency of the solvers. Furthermore, our studies indicate that the proposed non-negative computational framework for diffusion-type equations exhibits excellent strong scaling for real-world large-scale problems.« less

Wall Modeled Large Eddy Simulation of Airfoil Trailing Edge Noise

NASA Astrophysics Data System (ADS)

Kocheemoolayil, Joseph; Lele, Sanjiva

2014-11-01

Large eddy simulation (LES) of airfoil trailing edge noise has largely been restricted to low Reynolds numbers due to prohibitive computational cost. Wall modeled LES (WMLES) is a computationally cheaper alternative that makes full-scale Reynolds numbers relevant to large wind turbines accessible. A systematic investigation of trailing edge noise prediction using WMLES is conducted. Detailed comparisons are made with experimental data. The stress boundary condition from a wall model does not constrain the fluctuating velocity to vanish at the wall. This limitation has profound implications for trailing edge noise prediction. The simulation over-predicts the intensity of fluctuating wall pressure and far-field noise. An improved wall model formulation that minimizes the over-prediction of fluctuating wall pressure is proposed and carefully validated. The flow configurations chosen for the study are from the workshop on benchmark problems for airframe noise computations. The large eddy simulation database is used to examine the adequacy of scaling laws that quantify the dependence of trailing edge noise on Mach number, Reynolds number and angle of attack. Simplifying assumptions invoked in engineering approaches towards predicting trailing edge noise are critically evaluated. We gratefully acknowledge financial support from GE Global Research and thank Cascade Technologies Inc. for providing access to their massively-parallel large eddy simulation framework.

Nongyrotropic Electrons in Guide Field Reconnection

NASA Technical Reports Server (NTRS)

Wendel, D. E.; Hesse, M.; Bessho, N.; Adrian, M. L.; Kuznetsova, M.

2016-01-01

We apply a scalar measure of nongyrotropy to the electron pressure tensor in a 2D particle-in-cell simulation of guide field reconnection and assess the corresponding electron distributions and the forces that account for the nongyrotropy. The scalar measure reveals that the nongyrotropy lies in bands that straddle the electron diffusion region and the separatrices, in the same regions where there are parallel electric fields. Analysis of electron distributions and fields shows that the nongyrotropy along the inflow and outflow separatrices emerges as a result of multiple populations of electrons influenced differently by large and small-scale parallel electric fields and by gradients in the electric field. The relevant parallel electric fields include large-scale potential ramps emanating from the x-line and sub-ion inertial scale bipolar electron holes. Gradients in the perpendicular electric field modify electrons differently depending on their phase, thus producing nongyrotropy. Magnetic flux violation occurs along portions of the separatrices that coincide with the parallel electric fields. An inductive electric field in the electron EB drift frame thus develops, which has the effect of enhancing nongyrotropies already produced by other mechanisms and under certain conditions producing their own nongyrotropy. Particle tracing of electrons from nongyrotropic populations along the inflows and outflows shows that the striated structure of nongyrotropy corresponds to electrons arriving from different source regions. We also show that the relevant parallel electric fields receive important contributions not only from the nongyrotropic portion of the electron pressure tensor but from electron spatial and temporal inertial terms as well.

Photonic content-addressable memory system that uses a parallel-readout optical disk

NASA Astrophysics Data System (ADS)

Krishnamoorthy, Ashok V.; Marchand, Philippe J.; Yayla, Gökçe; Esener, Sadik C.

1995-11-01

We describe a high-performance associative-memory system that can be implemented by means of an optical disk modified for parallel readout and a custom-designed silicon integrated circuit with parallel optical input. The system can achieve associative recall on 128 \\times 128 bit images and also on variable-size subimages. The system's behavior and performance are evaluated on the basis of experimental results on a motionless-head parallel-readout optical-disk system, logic simulations of the very-large-scale integrated chip, and a software emulation of the overall system.

The NAS parallel benchmarks

NASA Technical Reports Server (NTRS)

Bailey, D. H.; Barszcz, E.; Barton, J. T.; Carter, R. L.; Lasinski, T. A.; Browning, D. S.; Dagum, L.; Fatoohi, R. A.; Frederickson, P. O.; Schreiber, R. S.

1991-01-01

A new set of benchmarks has been developed for the performance evaluation of highly parallel supercomputers in the framework of the NASA Ames Numerical Aerodynamic Simulation (NAS) Program. These consist of five 'parallel kernel' benchmarks and three 'simulated application' benchmarks. Together they mimic the computation and data movement characteristics of large-scale computational fluid dynamics applications. The principal distinguishing feature of these benchmarks is their 'pencil and paper' specification-all details of these benchmarks are specified only algorithmically. In this way many of the difficulties associated with conventional benchmarking approaches on highly parallel systems are avoided.

pcircle - A Suite of Scalable Parallel File System Tools

DOE Office of Scientific and Technical Information (OSTI.GOV)

WANG, FEIYI

2015-10-01

Most of the software related to file system are written for conventional local file system, they are serialized and can't take advantage of the benefit of a large scale parallel file system. "pcircle" software builds on top of ubiquitous MPI in cluster computing environment and "work-stealing" pattern to provide a scalable, high-performance suite of file system tools. In particular - it implemented parallel data copy and parallel data checksumming, with advanced features such as async progress report, checkpoint and restart, as well as integrity checking.

A Multi-Time Scale Morphable Software Milieu for Polymorphous Computing Architectures (PCA) - Composable, Scalable Systems

DTIC Science & Technology

2004-10-01

MONITORING AGENCY NAME(S) AND ADDRESS(ES) Defense Advanced Research Projects Agency AFRL/IFTC 3701 North Fairfax Drive...Scalable Parallel Libraries for Large-Scale Concurrent Applications," Technical Report UCRL -JC-109251, Lawrence Livermore National Laboratory

Extreme-Scale Bayesian Inference for Uncertainty Quantification of Complex Simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Biros, George

Uncertainty quantification (UQ)—that is, quantifying uncertainties in complex mathematical models and their large-scale computational implementations—is widely viewed as one of the outstanding challenges facing the field of CS&E over the coming decade. The EUREKA project set to address the most difficult class of UQ problems: those for which both the underlying PDE model as well as the uncertain parameters are of extreme scale. In the project we worked on these extreme-scale challenges in the following four areas: 1. Scalable parallel algorithms for sampling and characterizing the posterior distribution that exploit the structure of the underlying PDEs and parameter-to-observable map. Thesemore » include structure-exploiting versions of the randomized maximum likelihood method, which aims to overcome the intractability of employing conventional MCMC methods for solving extreme-scale Bayesian inversion problems by appealing to and adapting ideas from large-scale PDE-constrained optimization, which have been very successful at exploring high-dimensional spaces. 2. Scalable parallel algorithms for construction of prior and likelihood functions based on learning methods and non-parametric density estimation. Constructing problem-specific priors remains a critical challenge in Bayesian inference, and more so in high dimensions. Another challenge is construction of likelihood functions that capture unmodeled couplings between observations and parameters. We will create parallel algorithms for non-parametric density estimation using high dimensional N-body methods and combine them with supervised learning techniques for the construction of priors and likelihood functions. 3. Bayesian inadequacy models, which augment physics models with stochastic models that represent their imperfections. The success of the Bayesian inference framework depends on the ability to represent the uncertainty due to imperfections of the mathematical model of the phenomena of interest. This is a central challenge in UQ, especially for large-scale models. We propose to develop the mathematical tools to address these challenges in the context of extreme-scale problems. 4. Parallel scalable algorithms for Bayesian optimal experimental design (OED). Bayesian inversion yields quantified uncertainties in the model parameters, which can be propagated forward through the model to yield uncertainty in outputs of interest. This opens the way for designing new experiments to reduce the uncertainties in the model parameters and model predictions. Such experimental design problems have been intractable for large-scale problems using conventional methods; we will create OED algorithms that exploit the structure of the PDE model and the parameter-to-output map to overcome these challenges. Parallel algorithms for these four problems were created, analyzed, prototyped, implemented, tuned, and scaled up for leading-edge supercomputers, including UT-Austin’s own 10 petaflops Stampede system, ANL’s Mira system, and ORNL’s Titan system. While our focus is on fundamental mathematical/computational methods and algorithms, we will assess our methods on model problems derived from several DOE mission applications, including multiscale mechanics and ice sheet dynamics.« less

Optimistic barrier synchronization

NASA Technical Reports Server (NTRS)

Nicol, David M.

1992-01-01

Barrier synchronization is fundamental operation in parallel computation. In many contexts, at the point a processor enters a barrier it knows that it has already processed all the work required of it prior to synchronization. The alternative case, when a processor cannot enter a barrier with the assurance that it has already performed all the necessary pre-synchronization computation, is treated. The problem arises when the number of pre-sychronization messages to be received by a processor is unkown, for example, in a parallel discrete simulation or any other computation that is largely driven by an unpredictable exchange of messages. We describe an optimistic O(log sup 2 P) barrier algorithm for such problems, study its performance on a large-scale parallel system, and consider extensions to general associative reductions as well as associative parallel prefix computations.

MOLNs: A CLOUD PLATFORM FOR INTERACTIVE, REPRODUCIBLE, AND SCALABLE SPATIAL STOCHASTIC COMPUTATIONAL EXPERIMENTS IN SYSTEMS BIOLOGY USING PyURDME.

PubMed

Drawert, Brian; Trogdon, Michael; Toor, Salman; Petzold, Linda; Hellander, Andreas

2016-01-01

Computational experiments using spatial stochastic simulations have led to important new biological insights, but they require specialized tools and a complex software stack, as well as large and scalable compute and data analysis resources due to the large computational cost associated with Monte Carlo computational workflows. The complexity of setting up and managing a large-scale distributed computation environment to support productive and reproducible modeling can be prohibitive for practitioners in systems biology. This results in a barrier to the adoption of spatial stochastic simulation tools, effectively limiting the type of biological questions addressed by quantitative modeling. In this paper, we present PyURDME, a new, user-friendly spatial modeling and simulation package, and MOLNs, a cloud computing appliance for distributed simulation of stochastic reaction-diffusion models. MOLNs is based on IPython and provides an interactive programming platform for development of sharable and reproducible distributed parallel computational experiments.

Conjugate-Gradient Algorithms For Dynamics Of Manipulators

NASA Technical Reports Server (NTRS)

Fijany, Amir; Scheid, Robert E.

1993-01-01

Algorithms for serial and parallel computation of forward dynamics of multiple-link robotic manipulators by conjugate-gradient method developed. Parallel algorithms have potential for speedup of computations on multiple linked, specialized processors implemented in very-large-scale integrated circuits. Such processors used to stimulate dynamics, possibly faster than in real time, for purposes of planning and control.

Critical interactions between Global Fund-supported programmes and health systems: a case study in Papua New Guinea.

PubMed

Rudge, James W; Phuanakoonon, Suparat; Nema, K Henry; Mounier-Jack, Sandra; Coker, Richard

2010-11-01

In Papua New Guinea, investment by the Global Fund to Fight AIDS, Tuberculosis and Malaria (the Global Fund) has played an important role in scaling up the response to HIV and tuberculosis (TB). As part of a series of case studies on how Global Fund-supported programmes interact with national health systems, we assessed the nature and extent of integration of the Global Fund portfolios within the national HIV and TB programmes, the integration of the HIV and TB programmes within the general health system, and system-wide effects of Global Fund support in Papua New Guinea. The study relied on a literature review and 30 interviews with key stakeholders using the Systemic Rapid Assessment Toolkit and thematic analysis. Global Fund-supported activities were found to be largely integrated, or at least coordinated, with the national HIV and TB programmes. However, this has reinforced the vertical nature of these programmes with respect to the general health system, with parallel systems established to meet the demands of programme scale-up and the performance-based nature of Global Fund investment in the weak health system context of Papua New Guinea. The more parallel functions include monitoring and evaluation, and procurement and supply chain systems, while human resources and infrastructure for service delivery are increasingly integrated at more local levels. Positive synergies of Global Fund support include engagement of civil-society partners, and a reliable supply of high-quality drugs which may have increased patient confidence in the health system. However, the severely limited and overburdened pool of human resources has been skewed towards the three diseases, both at management and service delivery levels. There is also concern surrounding the sustainability of the disease programmes, given their dependence on donors. Increasing Global Fund attention towards health system strengthening was viewed positively, but should acknowledge that system changes are slow, difficult to measure and require long-term support.

VisIVO: A Library and Integrated Tools for Large Astrophysical Dataset Exploration

NASA Astrophysics Data System (ADS)

Becciani, U.; Costa, A.; Ersotelos, N.; Krokos, M.; Massimino, P.; Petta, C.; Vitello, F.

2012-09-01

VisIVO provides an integrated suite of tools and services that can be used in many scientific fields. VisIVO development starts in the Virtual Observatory framework. VisIVO allows users to visualize meaningfully highly-complex, large-scale datasets and create movies of these visualizations based on distributed infrastructures. VisIVO supports high-performance, multi-dimensional visualization of large-scale astrophysical datasets. Users can rapidly obtain meaningful visualizations while preserving full and intuitive control of the relevant parameters. VisIVO consists of VisIVO Desktop - a stand-alone application for interactive visualization on standard PCs, VisIVO Server - a platform for high performance visualization, VisIVO Web - a custom designed web portal, VisIVOSmartphone - an application to exploit the VisIVO Server functionality and the latest VisIVO features: VisIVO Library allows a job running on a computational system (grid, HPC, etc.) to produce movies directly with the code internal data arrays without the need to produce intermediate files. This is particularly important when running on large computational facilities, where the user wants to have a look at the results during the data production phase. For example, in grid computing facilities, images can be produced directly in the grid catalogue while the user code is running in a system that cannot be directly accessed by the user (a worker node). The deployment of VisIVO on the DG and gLite is carried out with the support of EDGI and EGI-Inspire projects. Depending on the structure and size of datasets under consideration, the data exploration process could take several hours of CPU for creating customized views and the production of movies could potentially last several days. For this reason an MPI parallel version of VisIVO could play a fundamental role in increasing performance, e.g. it could be automatically deployed on nodes that are MPI aware. A central concept in our development is thus to produce unified code that can run either on serial nodes or in parallel by using HPC oriented grid nodes. Another important aspect, to obtain as high performance as possible, is the integration of VisIVO processes with grid nodes where GPUs are available. We have selected CUDA for implementing a range of computationally heavy modules. VisIVO is supported by EGI-Inspire, EDGI and SCI-BUS projects.

THE EFFECT OF INTERMITTENT GYRO-SCALE SLAB TURBULENCE ON PARALLEL AND PERPENDICULAR COSMIC-RAY TRANSPORT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Le Roux, J. A.

Earlier work based on nonlinear guiding center (NLGC) theory suggested that perpendicular cosmic-ray transport is diffusive when cosmic rays encounter random three-dimensional magnetohydrodynamic turbulence dominated by uniform two-dimensional (2D) turbulence with a minor uniform slab turbulence component. In this approach large-scale perpendicular cosmic-ray transport is due to cosmic rays microscopically diffusing along the meandering magnetic field dominated by 2D turbulence because of gyroresonant interactions with slab turbulence. However, turbulence in the solar wind is intermittent and it has been suggested that intermittent turbulence might be responsible for the observation of 'dropout' events in solar energetic particle fluxes on small scales.more » In a previous paper le Roux et al. suggested, using NLGC theory as a basis, that if gyro-scale slab turbulence is intermittent, large-scale perpendicular cosmic-ray transport in weak uniform 2D turbulence will be superdiffusive or subdiffusive depending on the statistical characteristics of the intermittent slab turbulence. In this paper we expand and refine our previous work further by investigating how both parallel and perpendicular transport are affected by intermittent slab turbulence for weak as well as strong uniform 2D turbulence. The main new finding is that both parallel and perpendicular transport are the net effect of an interplay between diffusive and nondiffusive (superdiffusive or subdiffusive) transport effects as a consequence of this intermittency.« less

An Implicit Solver on A Parallel Block-Structured Adaptive Mesh Grid for FLASH

NASA Astrophysics Data System (ADS)

Lee, D.; Gopal, S.; Mohapatra, P.

2012-07-01

We introduce a fully implicit solver for FLASH based on a Jacobian-Free Newton-Krylov (JFNK) approach with an appropriate preconditioner. The main goal of developing this JFNK-type implicit solver is to provide efficient high-order numerical algorithms and methodology for simulating stiff systems of differential equations on large-scale parallel computer architectures. A large number of natural problems in nonlinear physics involve a wide range of spatial and time scales of interest. A system that encompasses such a wide magnitude of scales is described as "stiff." A stiff system can arise in many different fields of physics, including fluid dynamics/aerodynamics, laboratory/space plasma physics, low Mach number flows, reactive flows, radiation hydrodynamics, and geophysical flows. One of the big challenges in solving such a stiff system using current-day computational resources lies in resolving time and length scales varying by several orders of magnitude. We introduce FLASH's preliminary implementation of a time-accurate JFNK-based implicit solver in the framework of FLASH's unsplit hydro solver.

Automation of large scale transient protein expression in mammalian cells

PubMed Central

Zhao, Yuguang; Bishop, Benjamin; Clay, Jordan E.; Lu, Weixian; Jones, Margaret; Daenke, Susan; Siebold, Christian; Stuart, David I.; Yvonne Jones, E.; Radu Aricescu, A.

2011-01-01

Traditional mammalian expression systems rely on the time-consuming generation of stable cell lines; this is difficult to accommodate within a modern structural biology pipeline. Transient transfections are a fast, cost-effective solution, but require skilled cell culture scientists, making man-power a limiting factor in a setting where numerous samples are processed in parallel. Here we report a strategy employing a customised CompacT SelecT cell culture robot allowing the large-scale expression of multiple protein constructs in a transient format. Successful protocols have been designed for automated transient transfection of human embryonic kidney (HEK) 293T and 293S GnTI− cells in various flask formats. Protein yields obtained by this method were similar to those produced manually, with the added benefit of reproducibility, regardless of user. Automation of cell maintenance and transient transfection allows the expression of high quality recombinant protein in a completely sterile environment with limited support from a cell culture scientist. The reduction in human input has the added benefit of enabling continuous cell maintenance and protein production, features of particular importance to structural biology laboratories, which typically use large quantities of pure recombinant proteins, and often require rapid characterisation of a series of modified constructs. This automated method for large scale transient transfection is now offered as a Europe-wide service via the P-cube initiative. PMID:21571074

Eigensolver for a Sparse, Large Hermitian Matrix

NASA Technical Reports Server (NTRS)

Tisdale, E. Robert; Oyafuso, Fabiano; Klimeck, Gerhard; Brown, R. Chris

2003-01-01

A parallel-processing computer program finds a few eigenvalues in a sparse Hermitian matrix that contains as many as 100 million diagonal elements. This program finds the eigenvalues faster, using less memory, than do other, comparable eigensolver programs. This program implements a Lanczos algorithm in the American National Standards Institute/ International Organization for Standardization (ANSI/ISO) C computing language, using the Message Passing Interface (MPI) standard to complement an eigensolver in PARPACK. [PARPACK (Parallel Arnoldi Package) is an extension, to parallel-processing computer architectures, of ARPACK (Arnoldi Package), which is a collection of Fortran 77 subroutines that solve large-scale eigenvalue problems.] The eigensolver runs on Beowulf clusters of computers at the Jet Propulsion Laboratory (JPL).

Hybrid-optimization strategy for the communication of large-scale Kinetic Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Wu, Baodong; Li, Shigang; Zhang, Yunquan; Nie, Ningming

2017-02-01

The parallel Kinetic Monte Carlo (KMC) algorithm based on domain decomposition has been widely used in large-scale physical simulations. However, the communication overhead of the parallel KMC algorithm is critical, and severely degrades the overall performance and scalability. In this paper, we present a hybrid optimization strategy to reduce the communication overhead for the parallel KMC simulations. We first propose a communication aggregation algorithm to reduce the total number of messages and eliminate the communication redundancy. Then, we utilize the shared memory to reduce the memory copy overhead of the intra-node communication. Finally, we optimize the communication scheduling using the neighborhood collective operations. We demonstrate the scalability and high performance of our hybrid optimization strategy by both theoretical and experimental analysis. Results show that the optimized KMC algorithm exhibits better performance and scalability than the well-known open-source library-SPPARKS. On 32-node Xeon E5-2680 cluster (total 640 cores), the optimized algorithm reduces the communication time by 24.8% compared with SPPARKS.

A global database with parallel measurements to study non-climatic changes

NASA Astrophysics Data System (ADS)

Venema, Victor; Auchman, Renate; Aguilar, Enric

2017-04-01

In this work we introduce the rationale behind the ongoing compilation of a parallel measurements database, in the framework of the International Surface Temperatures Initiative (ISTI) and with the support of the World Meteorological Organization. We intend this database to become instrumental for a better understanding of inhomogeneities affecting the evaluation of long-term changes in daily climate data. Long instrumental climate records are usually affected by non-climatic changes, due to, e.g., (i) station re- locations, (ii) instrument height changes, (iii) instrumentation changes, (iv) observing environment changes, (v) different sampling intervals or data collection procedures, among others. These so-called inhomogeneities distort the climate signal and can hamper the assessment of long-term trends and variability of climate. Thus to study climatic changes we need to accurately distinguish non-climatic and climatic signals. The most direct way to study the influence of non-climatic changes on the distribution and to understand the reasons for these biases is the analysis of parallel measurements representing the old and new situation (in terms of e.g. instruments, location, different radiation shields, etc.). According to the limited number of available studies and our understanding of the causes of inhomogeneity, we expect that they will have a strong impact on the tails of the distribution of air temperatures and most likely of other climate elements. Our abilities to statistically homogenize daily data will be increased by systematically studying different causes of inhomogeneity replicated through parallel measurements. Current studies of non-climatic changes using parallel data are limited to local and regional case studies. However, the effect of specific transitions depends on the local climate and the most interesting climatic questions are about the systematic large-scale biases produced by transitions that occurred in many regions. Important potentially biasing transitions are the adoption of Stevenson screens, relocations (to airports) efforts to reduce undercatchment of precipitation or the move to automatic weather stations. Thus a large global parallel dataset is highly desirable as it allows for the study of systematic biases in the global record. We are interested in data from all climate variables at all time scales; from annual to sub-daily. High-resolution data is important for understanding the physical causes for the differences between the parallel measurements. For the same reason, we are also interested in other climate variables measured at the same station. For example, in case of parallel air temperature measurements, the influencing factors are expected to be global radiation, wind, humidity and cloud cover; in case of parallel precipitation measurements, wind and wet-bulb temperature are potentially important.

A global database with parallel measurements to study non-climatic changes

NASA Astrophysics Data System (ADS)

Venema, Victor; Auchmann, Renate; Aguilar, Enric

2015-04-01

n this work we introduce the rationale behind the ongoing compilation of a parallel measurements database, under the umbrella of the International Surface Temperatures Initiative (ISTI) and with the support of the World Meteorological Organization. We intend this database to become instrumental for a better understanding of inhomogeneities affecting the evaluation of long term changes in daily climate data. Long instrumental climate records are usually affected by non-climatic changes, due to, e.g., relocations and changes in instrumentation, instrument height or data collection and manipulation procedures. These so-called inhomogeneities distort the climate signal and can hamper the assessment of trends and variability. Thus to study climatic changes we need to accurately distinguish non-climatic and climatic signals. .The most direct way to study the influence of non-climatic changes on the distribution and to understand the reasons for these biases is the analysis of parallel measurements representing the old and new situation (in terms of e.g. instruments, location). According to the limited number of available studies and our understanding of the causes of inhomogeneity, we expect that they will have a strong impact on the tails of the distribution of temperatures and most likely of other climate elements. Our abilities to statistically homogenize daily data will be increased by systematically studying different causes of inhomogeneity replicated through parallel measurements. Current studies of non-climatic changes using parallel data are limited to local and regional case studies. However, the effect of specific transitions depends on the local climate and the most interesting climatic questions are about the systematic large-scale biases produced by transitions that occurred in many regions. Important potentially biasing transitions are the adoption of Stevenson screens, efforts to reduce undercatchment of precipitation or the move to automatic weather stations. Thus a large global parallel dataset is highly desirable as it allows for the study of systematic biases in the global record. In the ISTI Parallel Observations Science Team (POST), we will gather parallel data in their native format (to avoid undetectable conversion errors we will convert it to a standard format ourselves). We are interested in data from all climate variables at all time scales; from annual to sub-daily. High-resolution data is important for understanding the physical causes for the differences between the parallel measurements. For the same reason, we are also interested in other climate variables measured at the same station. For example, in case of parallel temperature measurements, the influencing factors are expected to be insolation, wind and clouds cover; in case of parallel precipitation measurements, wind and temperature are potentially important. Metadata that describe the parallel measurements is as important as the data itself and will be collected as well. For example, the types of the instruments, their siting, height, maintenance, etc. Because they are widely used to study moderate extremes, we will compute the indices of the Expert Team on Climate Change Detection and Indices (ETCCDI). In case the daily data cannot be shared, we would appreciate these indices from parallel measurements. For more information: http://tinyurl.com/ISTI-Parallel

Concurrent Programming Using Actors: Exploiting Large-Scale Parallelism,

DTIC Science & Technology

1985-10-07

ORGANIZATION NAME AND ADDRESS 10. PROGRAM ELEMENT. PROJECT. TASK* Artificial Inteligence Laboratory AREA Is WORK UNIT NUMBERS 545 Technology Square...D-R162 422 CONCURRENT PROGRMMIZNG USING f"OS XL?ITP TEH l’ LARGE-SCALE PARALLELISH(U) NASI AC E Al CAMBRIDGE ARTIFICIAL INTELLIGENCE L. G AGHA ET AL...RESOLUTION TEST CHART N~ATIONAL BUREAU OF STANDA.RDS - -96 A -E. __ _ __ __’ .,*- - -- •. - MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL

Parallel-vector out-of-core equation solver for computational mechanics

NASA Technical Reports Server (NTRS)

Qin, J.; Agarwal, T. K.; Storaasli, O. O.; Nguyen, D. T.; Baddourah, M. A.

1993-01-01

A parallel/vector out-of-core equation solver is developed for shared-memory computers, such as the Cray Y-MP machine. The input/ output (I/O) time is reduced by using the a synchronous BUFFER IN and BUFFER OUT, which can be executed simultaneously with the CPU instructions. The parallel and vector capability provided by the supercomputers is also exploited to enhance the performance. Numerical applications in large-scale structural analysis are given to demonstrate the efficiency of the present out-of-core solver.

Modification in drag of turbulent boundary layers resulting from manipulation of large-scale structures

NASA Technical Reports Server (NTRS)

Corke, T. C.; Guezennec, Y.; Nagib, H. M.

1981-01-01

The effects of placing a parallel-plate turbulence manipulator in a boundary layer are documented through flow visualization and hot wire measurements. The boundary layer manipulator was designed to manage the large scale structures of turbulence leading to a reduction in surface drag. The differences in the turbulent structure of the boundary layer are summarized to demonstrate differences in various flow properties. The manipulator inhibited the intermittent large scale structure of the turbulent boundary layer for at least 70 boundary layer thicknesses downstream. With the removal of the large scale, the streamwise turbulence intensity levels near the wall were reduced. The downstream distribution of the skin friction was also altered by the introduction of the manipulator.

A topology visualization early warning distribution algorithm for large-scale network security incidents.

PubMed

He, Hui; Fan, Guotao; Ye, Jianwei; Zhang, Weizhe

2013-01-01

It is of great significance to research the early warning system for large-scale network security incidents. It can improve the network system's emergency response capabilities, alleviate the cyber attacks' damage, and strengthen the system's counterattack ability. A comprehensive early warning system is presented in this paper, which combines active measurement and anomaly detection. The key visualization algorithm and technology of the system are mainly discussed. The large-scale network system's plane visualization is realized based on the divide and conquer thought. First, the topology of the large-scale network is divided into some small-scale networks by the MLkP/CR algorithm. Second, the sub graph plane visualization algorithm is applied to each small-scale network. Finally, the small-scale networks' topologies are combined into a topology based on the automatic distribution algorithm of force analysis. As the algorithm transforms the large-scale network topology plane visualization problem into a series of small-scale network topology plane visualization and distribution problems, it has higher parallelism and is able to handle the display of ultra-large-scale network topology.

Synchronization Of Parallel Discrete Event Simulations

NASA Technical Reports Server (NTRS)

Steinman, Jeffrey S.

1992-01-01

Adaptive, parallel, discrete-event-simulation-synchronization algorithm, Breathing Time Buckets, developed in Synchronous Parallel Environment for Emulation and Discrete Event Simulation (SPEEDES) operating system. Algorithm allows parallel simulations to process events optimistically in fluctuating time cycles that naturally adapt while simulation in progress. Combines best of optimistic and conservative synchronization strategies while avoiding major disadvantages. Algorithm processes events optimistically in time cycles adapting while simulation in progress. Well suited for modeling communication networks, for large-scale war games, for simulated flights of aircraft, for simulations of computer equipment, for mathematical modeling, for interactive engineering simulations, and for depictions of flows of information.

Load Balancing Scientific Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pearce, Olga Tkachyshyn

2014-12-01

The largest supercomputers have millions of independent processors, and concurrency levels are rapidly increasing. For ideal efficiency, developers of the simulations that run on these machines must ensure that computational work is evenly balanced among processors. Assigning work evenly is challenging because many large modern parallel codes simulate behavior of physical systems that evolve over time, and their workloads change over time. Furthermore, the cost of imbalanced load increases with scale because most large-scale scientific simulations today use a Single Program Multiple Data (SPMD) parallel programming model, and an increasing number of processors will wait for the slowest one atmore » the synchronization points. To address load imbalance, many large-scale parallel applications use dynamic load balance algorithms to redistribute work evenly. The research objective of this dissertation is to develop methods to decide when and how to load balance the application, and to balance it effectively and affordably. We measure and evaluate the computational load of the application, and develop strategies to decide when and how to correct the imbalance. Depending on the simulation, a fast, local load balance algorithm may be suitable, or a more sophisticated and expensive algorithm may be required. We developed a model for comparison of load balance algorithms for a specific state of the simulation that enables the selection of a balancing algorithm that will minimize overall runtime.« less

Large-scale virtual screening on public cloud resources with Apache Spark.

PubMed

Capuccini, Marco; Ahmed, Laeeq; Schaal, Wesley; Laure, Erwin; Spjuth, Ola

2017-01-01

Structure-based virtual screening is an in-silico method to screen a target receptor against a virtual molecular library. Applying docking-based screening to large molecular libraries can be computationally expensive, however it constitutes a trivially parallelizable task. Most of the available parallel implementations are based on message passing interface, relying on low failure rate hardware and fast network connection. Google's MapReduce revolutionized large-scale analysis, enabling the processing of massive datasets on commodity hardware and cloud resources, providing transparent scalability and fault tolerance at the software level. Open source implementations of MapReduce include Apache Hadoop and the more recent Apache Spark. We developed a method to run existing docking-based screening software on distributed cloud resources, utilizing the MapReduce approach. We benchmarked our method, which is implemented in Apache Spark, docking a publicly available target receptor against [Formula: see text]2.2 M compounds. The performance experiments show a good parallel efficiency (87%) when running in a public cloud environment. Our method enables parallel Structure-based virtual screening on public cloud resources or commodity computer clusters. The degree of scalability that we achieve allows for trying out our method on relatively small libraries first and then to scale to larger libraries. Our implementation is named Spark-VS and it is freely available as open source from GitHub (https://github.com/mcapuccini/spark-vs).Graphical abstract.

How far can we go in chronic disorders of consciousness differential diagnosis? The use of neuromodulation in detecting internal and external awareness.

PubMed

Naro, Antonino; Leo, Antonino; Manuli, Alfredo; Cannavò, Antonino; Bramanti, Alessia; Bramanti, Placido; Calabrò, Rocco Salvatore

2017-05-04

Awareness generation and modulation may depend on a balanced information integration and differentiation across default mode network (DMN) and external awareness networks (EAN). Neuromodulation approaches, capable of shaping information processing, may highlight residual network activities supporting awareness, which are not detectable through active paradigms, thus allowing to differentiate chronic disorders of consciousness (DoC). We studied aftereffects of repetitive transcranial magnetic stimulation (rTMS) by applying graph theory within canonical frequency bands to compare the markers of these networks in the electroencephalographic data from 20 patients with DoC. We found that patients' high-frequency networks suffered from a large-scale connectivity breakdown, paralleled by a local hyperconnectivity, whereas low-frequency networks showed a preserved but dysfunctional large-scale connectivity. There was a correlation between metrics and the behavioral awareness. Interestingly, two persons with UWS showed a residual rTMS-induced modulation of the functional correlations between the DMN and the EAN, as observed in patients with MCS. Hence, we may hypothesize that the patients with UWS who demonstrate evidence of residual DMN-EAN functional correlation may be misdiagnosed, given that such residual network correlations could support covert consciousness. Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.

A gyrofluid description of Alfvenic turbulence and its parallel electric field

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bian, N. H.; Kontar, E. P.

2010-06-15

Anisotropic Alfvenic fluctuations with k{sub ||}/k{sub perpendicular}<<1 remain at frequencies much smaller than the ion cyclotron frequency in the presence of a strong background magnetic field. Based on the simplest truncation of the electromagnetic gyrofluid equations in a homogeneous plasma, a model for the energy cascade produced by Alfvenic turbulence is constructed, which smoothly connects the large magnetohydrodynamics scales and the small 'kinetic' scales. Scaling relations are obtained for the electromagnetic fluctuations, as a function of k{sub perpendicular} and k{sub ||}. Moreover, a particular attention is paid to the spectral structure of the parallel electric field which is produced bymore » Alfvenic turbulence. The reason is the potential implication of this parallel electric field in turbulent acceleration and transport of particles. For electromagnetic turbulence, this issue was raised some time ago in Hasegawa and Mima [J. Geophys. Res. 83, 1117 (1978)].« less

Pushing configuration-interaction to the limit: Towards massively parallel MCSCF calculations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vogiatzis, Konstantinos D.; Ma, Dongxia; Olsen, Jeppe

A new large-scale parallel multiconfigurational self-consistent field (MCSCF) implementation in the open-source NWChem computational chemistry code is presented. The generalized active space approach is used to partition large configuration interaction (CI) vectors and generate a sufficient number of batches that can be distributed to the available cores. Massively parallel CI calculations with large active spaces can be performed. The new parallel MCSCF implementation is tested for the chromium trimer and for an active space of 20 electrons in 20 orbitals, which can now routinely be performed. Unprecedented CI calculations with an active space of 22 electrons in 22 orbitals formore » the pentacene systems were performed and a single CI iteration calculation with an active space of 24 electrons in 24 orbitals for the chromium tetramer was possible. In conclusion, the chromium tetramer corresponds to a CI expansion of one trillion Slater determinants (914 058 513 424) and is the largest conventional CI calculation attempted up to date.« less

Pushing configuration-interaction to the limit: Towards massively parallel MCSCF calculations

DOE PAGES

Vogiatzis, Konstantinos D.; Ma, Dongxia; Olsen, Jeppe; ...

2017-11-14

A new large-scale parallel multiconfigurational self-consistent field (MCSCF) implementation in the open-source NWChem computational chemistry code is presented. The generalized active space approach is used to partition large configuration interaction (CI) vectors and generate a sufficient number of batches that can be distributed to the available cores. Massively parallel CI calculations with large active spaces can be performed. The new parallel MCSCF implementation is tested for the chromium trimer and for an active space of 20 electrons in 20 orbitals, which can now routinely be performed. Unprecedented CI calculations with an active space of 22 electrons in 22 orbitals formore » the pentacene systems were performed and a single CI iteration calculation with an active space of 24 electrons in 24 orbitals for the chromium tetramer was possible. In conclusion, the chromium tetramer corresponds to a CI expansion of one trillion Slater determinants (914 058 513 424) and is the largest conventional CI calculation attempted up to date.« less

Pushing configuration-interaction to the limit: Towards massively parallel MCSCF calculations

NASA Astrophysics Data System (ADS)

Vogiatzis, Konstantinos D.; Ma, Dongxia; Olsen, Jeppe; Gagliardi, Laura; de Jong, Wibe A.

2017-11-01

A new large-scale parallel multiconfigurational self-consistent field (MCSCF) implementation in the open-source NWChem computational chemistry code is presented. The generalized active space approach is used to partition large configuration interaction (CI) vectors and generate a sufficient number of batches that can be distributed to the available cores. Massively parallel CI calculations with large active spaces can be performed. The new parallel MCSCF implementation is tested for the chromium trimer and for an active space of 20 electrons in 20 orbitals, which can now routinely be performed. Unprecedented CI calculations with an active space of 22 electrons in 22 orbitals for the pentacene systems were performed and a single CI iteration calculation with an active space of 24 electrons in 24 orbitals for the chromium tetramer was possible. The chromium tetramer corresponds to a CI expansion of one trillion Slater determinants (914 058 513 424) and is the largest conventional CI calculation attempted up to date.

Parallel block schemes for large scale least squares computations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Golub, G.H.; Plemmons, R.J.; Sameh, A.

1986-04-01

Large scale least squares computations arise in a variety of scientific and engineering problems, including geodetic adjustments and surveys, medical image analysis, molecular structures, partial differential equations and substructuring methods in structural engineering. In each of these problems, matrices often arise which possess a block structure which reflects the local connection nature of the underlying physical problem. For example, such super-large nonlinear least squares computations arise in geodesy. Here the coordinates of positions are calculated by iteratively solving overdetermined systems of nonlinear equations by the Gauss-Newton method. The US National Geodetic Survey will complete this year (1986) the readjustment ofmore » the North American Datum, a problem which involves over 540 thousand unknowns and over 6.5 million observations (equations). The observation matrix for these least squares computations has a block angular form with 161 diagnonal blocks, each containing 3 to 4 thousand unknowns. In this paper parallel schemes are suggested for the orthogonal factorization of matrices in block angular form and for the associated backsubstitution phase of the least squares computations. In addition, a parallel scheme for the calculation of certain elements of the covariance matrix for such problems is described. It is shown that these algorithms are ideally suited for multiprocessors with three levels of parallelism such as the Cedar system at the University of Illinois. 20 refs., 7 figs.« less

Enabling large-scale next-generation sequence assembly with Blacklight

PubMed Central

Couger, M. Brian; Pipes, Lenore; Squina, Fabio; Prade, Rolf; Siepel, Adam; Palermo, Robert; Katze, Michael G.; Mason, Christopher E.; Blood, Philip D.

2014-01-01

Summary A variety of extremely challenging biological sequence analyses were conducted on the XSEDE large shared memory resource Blacklight, using current bioinformatics tools and encompassing a wide range of scientific applications. These include genomic sequence assembly, very large metagenomic sequence assembly, transcriptome assembly, and sequencing error correction. The data sets used in these analyses included uncategorized fungal species, reference microbial data, very large soil and human gut microbiome sequence data, and primate transcriptomes, composed of both short-read and long-read sequence data. A new parallel command execution program was developed on the Blacklight resource to handle some of these analyses. These results, initially reported previously at XSEDE13 and expanded here, represent significant advances for their respective scientific communities. The breadth and depth of the results achieved demonstrate the ease of use, versatility, and unique capabilities of the Blacklight XSEDE resource for scientific analysis of genomic and transcriptomic sequence data, and the power of these resources, together with XSEDE support, in meeting the most challenging scientific problems. PMID:25294974

Runtime support for parallelizing data mining algorithms

NASA Astrophysics Data System (ADS)

Jin, Ruoming; Agrawal, Gagan

2002-03-01

With recent technological advances, shared memory parallel machines have become more scalable, and offer large main memories and high bus bandwidths. They are emerging as good platforms for data warehousing and data mining. In this paper, we focus on shared memory parallelization of data mining algorithms. We have developed a series of techniques for parallelization of data mining algorithms, including full replication, full locking, fixed locking, optimized full locking, and cache-sensitive locking. Unlike previous work on shared memory parallelization of specific data mining algorithms, all of our techniques apply to a large number of common data mining algorithms. In addition, we propose a reduction-object based interface for specifying a data mining algorithm. We show how our runtime system can apply any of the technique we have developed starting from a common specification of the algorithm.

Compiled MPI: Cost-Effective Exascale Applications Development

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bronevetsky, G; Quinlan, D; Lumsdaine, A

2012-04-10

The complexity of petascale and exascale machines makes it increasingly difficult to develop applications that can take advantage of them. Future systems are expected to feature billion-way parallelism, complex heterogeneous compute nodes and poor availability of memory (Peter Kogge, 2008). This new challenge for application development is motivating a significant amount of research and development on new programming models and runtime systems designed to simplify large-scale application development. Unfortunately, DoE has significant multi-decadal investment in a large family of mission-critical scientific applications. Scaling these applications to exascale machines will require a significant investment that will dwarf the costs of hardwaremore » procurement. A key reason for the difficulty in transitioning today's applications to exascale hardware is their reliance on explicit programming techniques, such as the Message Passing Interface (MPI) programming model to enable parallelism. MPI provides a portable and high performance message-passing system that enables scalable performance on a wide variety of platforms. However, it also forces developers to lock the details of parallelization together with application logic, making it very difficult to adapt the application to significant changes in the underlying system. Further, MPI's explicit interface makes it difficult to separate the application's synchronization and communication structure, reducing the amount of support that can be provided by compiler and run-time tools. This is in contrast to the recent research on more implicit parallel programming models such as Chapel, OpenMP and OpenCL, which promise to provide significantly more flexibility at the cost of reimplementing significant portions of the application. We are developing CoMPI, a novel compiler-driven approach to enable existing MPI applications to scale to exascale systems with minimal modifications that can be made incrementally over the application's lifetime. It includes: (1) New set of source code annotations, inserted either manually or automatically, that will clarify the application's use of MPI to the compiler infrastructure, enabling greater accuracy where needed; (2) A compiler transformation framework that leverages these annotations to transform the original MPI source code to improve its performance and scalability; (3) Novel MPI runtime implementation techniques that will provide a rich set of functionality extensions to be used by applications that have been transformed by our compiler; and (4) A novel compiler analysis that leverages simple user annotations to automatically extract the application's communication structure and synthesize most complex code annotations.« less

Evaluation of the scale dependent dynamic SGS model in the open source code caffa3d.MBRi in wall-bounded flows

NASA Astrophysics Data System (ADS)

Draper, Martin; Usera, Gabriel

2015-04-01

The Scale Dependent Dynamic Model (SDDM) has been widely validated in large-eddy simulations using pseudo-spectral codes [1][2][3]. The scale dependency, particularly the potential law, has been proved also in a priori studies [4][5]. To the authors' knowledge there have been only few attempts to use the SDDM in finite difference (FD) and finite volume (FV) codes [6][7], finding some improvements with the dynamic procedures (scale independent or scale dependent approach), but not showing the behavior of the scale-dependence parameter when using the SDDM. The aim of the present paper is to evaluate the SDDM in the open source code caffa3d.MBRi, an updated version of the code presented in [8]. caffa3d.MBRi is a FV code, second-order accurate, parallelized with MPI, in which the domain is divided in unstructured blocks of structured grids. To accomplish this, 2 cases are considered: flow between flat plates and flow over a rough surface with the presence of a model wind turbine, taking for this case the experimental data presented in [9]. In both cases the standard Smagorinsky Model (SM), the Scale Independent Dynamic Model (SIDM) and the SDDM are tested. As presented in [6][7] slight improvements are obtained with the SDDM. Nevertheless, the behavior of the scale-dependence parameter supports the generalization of the dynamic procedure proposed in the SDDM, particularly taking into account that no explicit filter is used (the implicit filter is unknown). [1] F. Porté-Agel, C. Meneveau, M.B. Parlange. "A scale-dependent dynamic model for large-eddy simulation: application to a neutral atmospheric boundary layer". Journal of Fluid Mechanics, 2000, 415, 261-284. [2] E. Bou-Zeid, C. Meneveau, M. Parlante. "A scale-dependent Lagrangian dynamic model for large eddy simulation of complex turbulent flows". Physics of Fluids, 2005, 17, 025105 (18p). [3] R. Stoll, F. Porté-Agel. "Dynamic subgrid-scale models for momentum and scalar fluxes in large-eddy simulations of neutrally stratified atmospheric boundary layers over heterogeneous terrain". Water Resources Research, 2006, 42, WO1409 (18 p). [4] J. Keissl, M. Parlange, C. Meneveau. "Field experimental study of dynamic Smagorinsky models in the atmospheric surface layer". Journal of the Atmospheric Science, 2004, 61, 2296-2307. [5] E. Bou-Zeid, N. Vercauteren, M.B. Parlange, C. Meneveau. "Scale dependence of subgrid-scale model coefficients: An a priori study". Physics of Fluids, 2008, 20, 115106. [6] G. Kirkil, J. Mirocha, E. Bou-Zeid, F.K. Chow, B. Kosovic, "Implementation and evaluation of dynamic subfilter - scale stress models for large - eddy simulation using WRF". Monthly Weather Review, 2012, 140, 266-284. [7] S. Radhakrishnan, U. Piomelli. "Large-eddy simulation of oscillating boundary layers: model comparison and validation". Journal of Geophysical Research, 2008, 113, C02022. [8] G. Usera, A. Vernet, J.A. Ferré. "A parallel block-structured finite volume method for flows in complex geometry with sliding interfaces". Flow, Turbulence and Combustion, 2008, 81, 471-495. [9] Y-T. Wu, F. Porté-Agel. "Large-eddy simulation of wind-turbine wakes: evaluation of turbine parametrisations". BoundaryLayerMeteorology, 2011, 138, 345-366.

First Applications of the New Parallel Krylov Solver for MODFLOW on a National and Global Scale

NASA Astrophysics Data System (ADS)

Verkaik, J.; Hughes, J. D.; Sutanudjaja, E.; van Walsum, P.

2016-12-01

Integrated high-resolution hydrologic models are increasingly being used for evaluating water management measures at field scale. Their drawbacks are large memory requirements and long run times. Examples of such models are The Netherlands Hydrological Instrument (NHI) model and the PCRaster Global Water Balance (PCR-GLOBWB) model. Typical simulation periods are 30-100 years with daily timesteps. The NHI model predicts water demands in periods of drought, supporting operational and long-term water-supply decisions. The NHI is a state-of-the-art coupling of several models: a 7-layer MODFLOW groundwater model ( 6.5M 250m cells), a MetaSWAP model for the unsaturated zone (Richards emulator of 0.5M cells), and a surface water model (MOZART-DM). The PCR-GLOBWB model provides a grid-based representation of global terrestrial hydrology and this work uses the version that includes a 2-layer MODFLOW groundwater model ( 4.5M 10km cells). The Parallel Krylov Solver (PKS) speeds up computation by both distributed memory parallelization (Message Passing Interface) and shared memory parallelization (Open Multi-Processing). PKS includes conjugate gradient, bi-conjugate gradient stabilized, and generalized minimal residual linear accelerators that use an overlapping additive Schwarz domain decomposition preconditioner. PKS can be used for both structured and unstructured grids and has been fully integrated in MODFLOW-USG using METIS partitioning and in iMODFLOW using RCB partitioning. iMODFLOW is an accelerated version of MODFLOW-2005 that is implicitly and online coupled to MetaSWAP. Results for benchmarks carried out on the Cartesius Dutch supercomputer (https://userinfo.surfsara.nl/systems/cartesius) for the PCRGLOB-WB model and on a 2x16 core Windows machine for the NHI model show speedups up to 10-20 and 5-10, respectively.

Multidisciplinary Design Optimization (MDO) Methods: Their Synergy with Computer Technology in Design Process

NASA Technical Reports Server (NTRS)

Sobieszczanski-Sobieski, Jaroslaw

1998-01-01

The paper identifies speed, agility, human interface, generation of sensitivity information, task decomposition, and data transmission (including storage) as important attributes for a computer environment to have in order to support engineering design effectively. It is argued that when examined in terms of these attributes the presently available environment can be shown to be inadequate a radical improvement is needed, and it may be achieved by combining new methods that have recently emerged from multidisciplinary design optimization (MDO) with massively parallel processing computer technology. The caveat is that, for successful use of that technology in engineering computing, new paradigms for computing will have to be developed - specifically, innovative algorithms that are intrinsically parallel so that their performance scales up linearly with the number of processors. It may be speculated that the idea of simulating a complex behavior by interaction of a large number of very simple models may be an inspiration for the above algorithms, the cellular automata are an example. Because of the long lead time needed to develop and mature new paradigms, development should be now, even though the widespread availability of massively parallel processing is still a few years away.

Multidisciplinary Design Optimisation (MDO) Methods: Their Synergy with Computer Technology in the Design Process

NASA Technical Reports Server (NTRS)

Sobieszczanski-Sobieski, Jaroslaw

1999-01-01

The paper identifies speed, agility, human interface, generation of sensitivity information, task decomposition, and data transmission (including storage) as important attributes for a computer environment to have in order to support engineering design effectively. It is argued that when examined in terms of these attributes the presently available environment can be shown to be inadequate. A radical improvement is needed, and it may be achieved by combining new methods that have recently emerged from multidisciplinary design optimisation (MDO) with massively parallel processing computer technology. The caveat is that, for successful use of that technology in engineering computing, new paradigms for computing will have to be developed - specifically, innovative algorithms that are intrinsically parallel so that their performance scales up linearly with the number of processors. It may be speculated that the idea of simulating a complex behaviour by interaction of a large number of very simple models may be an inspiration for the above algorithms; the cellular automata are an example. Because of the long lead time needed to develop and mature new paradigms, development should begin now, even though the widespread availability of massively parallel processing is still a few years away.

Low-Speed Investigation of Upper-Surface Leading-Edge Blowing on a High-Speed Civil Transport Configuration

NASA Technical Reports Server (NTRS)

Banks, Daniel W.; Laflin, Brenda E. Gile; Kemmerly, Guy T.; Campbell, Bryan A.

1999-01-01

The paper identifies speed, agility, human interface, generation of sensitivity information, task decomposition, and data transmission (including storage) as important attributes for a computer environment to have in order to support engineering design effectively. It is argued that when examined in terms of these attributes the presently available environment can be shown to be inadequate. A radical improvement is needed, and it may be achieved by combining new methods that have recently emerged from multidisciplinary design optimisation (MDO) with massively parallel processing computer technology. The caveat is that, for successful use of that technology in engineering computing, new paradigms for computing will have to be developed - specifically, innovative algorithms that are intrinsically parallel so that their performance scales up linearly with the number of processors. It may be speculated that the idea of simulating a complex behaviour by interaction of a large number of very simple models may be an inspiration for the above algorithms; the cellular automata are an example. Because of the long lead time needed to develop and mature new paradigms, development should begin now, even though the widespread availability of massively parallel processing is still a few years away.

Onset of a Large Ejective Solar Eruption from a Typical Coronal-jet-base Field Configuration

NASA Astrophysics Data System (ADS)

Joshi, Navin Chandra; Sterling, Alphonse C.; Moore, Ronald L.; Magara, Tetsuya; Moon, Yong-Jae

2017-08-01

Utilizing multiwavelength observations and magnetic field data from the Solar Dynamics Observatory (SDO)/Atmospheric Imaging Assembly (AIA), SDO/Helioseismic and Magnetic Imager (HMI), the Geostationary Operational Environmental Satellite (GOES), and RHESSI, we investigate a large-scale ejective solar eruption of 2014 December 18 from active region NOAA 12241. This event produced a distinctive “three-ribbon” flare, having two parallel ribbons corresponding to the ribbons of a standard two-ribbon flare, and a larger-scale third quasi-circular ribbon offset from the other two. There are two components to this eruptive event. First, a flux rope forms above a strong-field polarity inversion line and erupts and grows as the parallel ribbons turn on, grow, and spread apart from that polarity inversion line; this evolution is consistent with the mechanism of tether-cutting reconnection for eruptions. Second, the eruption of the arcade that has the erupting flux rope in its core undergoes magnetic reconnection at the null point of a fan dome that envelops the erupting arcade, resulting in formation of the quasi-circular ribbon; this is consistent with the breakout reconnection mechanism for eruptions. We find that the parallel ribbons begin well before (˜12 minutes) the onset of the circular ribbon, indicating that tether-cutting reconnection (or a non-ideal MHD instability) initiated this event, rather than breakout reconnection. The overall setup for this large-scale eruption (diameter of the circular ribbon ˜105 km) is analogous to that of coronal jets (base size ˜104 km), many of which, according to recent findings, result from eruptions of small-scale “minifilaments.” Thus these findings confirm that eruptions of sheared-core magnetic arcades seated in fan-spine null-point magnetic topology happen on a wide range of size scales on the Sun.

Sentinel-1 data massive processing for large scale DInSAR analyses within Cloud Computing environments through the P-SBAS approach

NASA Astrophysics Data System (ADS)

Lanari, Riccardo; Bonano, Manuela; Buonanno, Sabatino; Casu, Francesco; De Luca, Claudio; Fusco, Adele; Manunta, Michele; Manzo, Mariarosaria; Pepe, Antonio; Zinno, Ivana

2017-04-01

The SENTINEL-1 (S1) mission is designed to provide operational capability for continuous mapping of the Earth thanks to its two polar-orbiting satellites (SENTINEL-1A and B) performing C-band synthetic aperture radar (SAR) imaging. It is, indeed, characterized by enhanced revisit frequency, coverage and reliability for operational services and applications requiring long SAR data time series. Moreover, SENTINEL-1 is specifically oriented to interferometry applications with stringent requirements based on attitude and orbit accuracy and it is intrinsically characterized by small spatial and temporal baselines. Consequently, SENTINEL-1 data are particularly suitable to be exploited through advanced interferometric techniques such as the well-known DInSAR algorithm referred to as Small BAseline Subset (SBAS), which allows the generation of deformation time series and displacement velocity maps. In this work we present an advanced interferometric processing chain, based on the Parallel SBAS (P-SBAS) approach, for the massive processing of S1 Interferometric Wide Swath (IWS) data aimed at generating deformation time series in efficient, automatic and systematic way. Such a DInSAR chain is designed to exploit distributed computing infrastructures, and more specifically Cloud Computing environments, to properly deal with the storage and the processing of huge S1 datasets. In particular, since S1 IWS data are acquired with the innovative Terrain Observation with Progressive Scans (TOPS) mode, we could benefit from the structure of S1 data, which are composed by bursts that can be considered as separate acquisitions. Indeed, the processing is intrinsically parallelizable with respect to such independent input data and therefore we basically exploited this coarse granularity parallelization strategy in the majority of the steps of the SBAS processing chain. Moreover, we also implemented more sophisticated parallelization approaches, exploiting both multi-node and multi-core programming techniques. Currently, Cloud Computing environments make available large collections of computing resources and storage that can be effectively exploited through the presented S1 P-SBAS processing chain to carry out interferometric analyses at a very large scale, in reduced time. This allows us to deal also with the problems connected to the use of S1 P-SBAS chain in operational contexts, related to hazard monitoring and risk prevention and mitigation, where handling large amounts of data represents a challenging task. As a significant experimental result we performed a large spatial scale SBAS analysis relevant to the Central and Southern Italy by exploiting the Amazon Web Services Cloud Computing platform. In particular, we processed in parallel 300 S1 acquisitions covering the Italian peninsula from Lazio to Sicily through the presented S1 P-SBAS processing chain, generating 710 interferograms, thus finally obtaining the displacement time series of the whole processed area. This work has been partially supported by the CNR-DPC agreement, the H2020 EPOS-IP project (GA 676564) and the ESA GEP project.

GLAD: a system for developing and deploying large-scale bioinformatics grid.

PubMed

Teo, Yong-Meng; Wang, Xianbing; Ng, Yew-Kwong

2005-03-01

Grid computing is used to solve large-scale bioinformatics problems with gigabytes database by distributing the computation across multiple platforms. Until now in developing bioinformatics grid applications, it is extremely tedious to design and implement the component algorithms and parallelization techniques for different classes of problems, and to access remotely located sequence database files of varying formats across the grid. In this study, we propose a grid programming toolkit, GLAD (Grid Life sciences Applications Developer), which facilitates the development and deployment of bioinformatics applications on a grid. GLAD has been developed using ALiCE (Adaptive scaLable Internet-based Computing Engine), a Java-based grid middleware, which exploits the task-based parallelism. Two bioinformatics benchmark applications, such as distributed sequence comparison and distributed progressive multiple sequence alignment, have been developed using GLAD.

Comparing multi-module connections in membrane chromatography scale-up.

PubMed

Yu, Zhou; Karkaria, Tishtar; Espina, Marianela; Hunjun, Manjeet; Surendran, Abera; Luu, Tina; Telychko, Julia; Yang, Yan-Ping

2015-07-20

Membrane chromatography is increasingly used for protein purification in the biopharmaceutical industry. Membrane adsorbers are often pre-assembled by manufacturers as ready-to-use modules. In large-scale protein manufacturing settings, the use of multiple membrane modules for a single batch is often required due to the large quantity of feed material. The question as to how multiple modules can be connected to achieve optimum separation and productivity has been previously approached using model proteins and mass transport theories. In this study, we compare the performance of multiple membrane modules in series and in parallel in the production of a protein antigen. Series connection was shown to provide superior separation compared to parallel connection in the context of competitive adsorption. Copyright © 2015 Elsevier B.V. All rights reserved.

Architectural Implications for Spatial Object Association Algorithms*

PubMed Central

Kumar, Vijay S.; Kurc, Tahsin; Saltz, Joel; Abdulla, Ghaleb; Kohn, Scott R.; Matarazzo, Celeste

2013-01-01

Spatial object association, also referred to as crossmatch of spatial datasets, is the problem of identifying and comparing objects in two or more datasets based on their positions in a common spatial coordinate system. In this work, we evaluate two crossmatch algorithms that are used for astronomical sky surveys, on the following database system architecture configurations: (1) Netezza Performance Server®, a parallel database system with active disk style processing capabilities, (2) MySQL Cluster, a high-throughput network database system, and (3) a hybrid configuration consisting of a collection of independent database system instances with data replication support. Our evaluation provides insights about how architectural characteristics of these systems affect the performance of the spatial crossmatch algorithms. We conducted our study using real use-case scenarios borrowed from a large-scale astronomy application known as the Large Synoptic Survey Telescope (LSST). PMID:25692244

Big data analytics workflow management for eScience

NASA Astrophysics Data System (ADS)

Fiore, Sandro; D'Anca, Alessandro; Palazzo, Cosimo; Elia, Donatello; Mariello, Andrea; Nassisi, Paola; Aloisio, Giovanni

2015-04-01

In many domains such as climate and astrophysics, scientific data is often n-dimensional and requires tools that support specialized data types and primitives if it is to be properly stored, accessed, analysed and visualized. Currently, scientific data analytics relies on domain-specific software and libraries providing a huge set of operators and functionalities. However, most of these software fail at large scale since they: (i) are desktop based, rely on local computing capabilities and need the data locally; (ii) cannot benefit from available multicore/parallel machines since they are based on sequential codes; (iii) do not provide declarative languages to express scientific data analysis tasks, and (iv) do not provide newer or more scalable storage models to better support the data multidimensionality. Additionally, most of them: (v) are domain-specific, which also means they support a limited set of data formats, and (vi) do not provide a workflow support, to enable the construction, execution and monitoring of more complex "experiments". The Ophidia project aims at facing most of the challenges highlighted above by providing a big data analytics framework for eScience. Ophidia provides several parallel operators to manipulate large datasets. Some relevant examples include: (i) data sub-setting (slicing and dicing), (ii) data aggregation, (iii) array-based primitives (the same operator applies to all the implemented UDF extensions), (iv) data cube duplication, (v) data cube pivoting, (vi) NetCDF-import and export. Metadata operators are available too. Additionally, the Ophidia framework provides array-based primitives to perform data sub-setting, data aggregation (i.e. max, min, avg), array concatenation, algebraic expressions and predicate evaluation on large arrays of scientific data. Bit-oriented plugins have also been implemented to manage binary data cubes. Defining processing chains and workflows with tens, hundreds of data analytics operators is the real challenge in many practical scientific use cases. This talk will specifically address the main needs, requirements and challenges regarding data analytics workflow management applied to large scientific datasets. Three real use cases concerning analytics workflows for sea situational awareness, fire danger prevention, climate change and biodiversity will be discussed in detail.

Scaling Support Vector Machines On Modern HPC Platforms

DOE Office of Scientific and Technical Information (OSTI.GOV)

You, Yang; Fu, Haohuan; Song, Shuaiwen

2015-02-01

We designed and implemented MIC-SVM, a highly efficient parallel SVM for x86 based multicore and many-core architectures, such as the Intel Ivy Bridge CPUs and Intel Xeon Phi co-processor (MIC). We propose various novel analysis methods and optimization techniques to fully utilize the multilevel parallelism provided by these architectures and serve as general optimization methods for other machine learning tools.

Studying an Eulerian Computer Model on Different High-performance Computer Platforms and Some Applications

NASA Astrophysics Data System (ADS)

Georgiev, K.; Zlatev, Z.

2010-11-01

The Danish Eulerian Model (DEM) is an Eulerian model for studying the transport of air pollutants on large scale. Originally, the model was developed at the National Environmental Research Institute of Denmark. The model computational domain covers Europe and some neighbour parts belong to the Atlantic Ocean, Asia and Africa. If DEM model is to be applied by using fine grids, then its discretization leads to a huge computational problem. This implies that such a model as DEM must be run only on high-performance computer architectures. The implementation and tuning of such a complex large-scale model on each different computer is a non-trivial task. Here, some comparison results of running of this model on different kind of vector (CRAY C92A, Fujitsu, etc.), parallel computers with distributed memory (IBM SP, CRAY T3E, Beowulf clusters, Macintosh G4 clusters, etc.), parallel computers with shared memory (SGI Origin, SUN, etc.) and parallel computers with two levels of parallelism (IBM SMP, IBM BlueGene/P, clusters of multiprocessor nodes, etc.) will be presented. The main idea in the parallel version of DEM is domain partitioning approach. Discussions according to the effective use of the cache and hierarchical memories of the modern computers as well as the performance, speed-ups and efficiency achieved will be done. The parallel code of DEM, created by using MPI standard library, appears to be highly portable and shows good efficiency and scalability on different kind of vector and parallel computers. Some important applications of the computer model output are presented in short.

Grain-boundary unzipping by oxidation in polycrystalline graphene

NASA Astrophysics Data System (ADS)

Alexandre, Simone; Lucio, Aline; Nunes, Ricardo

2011-03-01

The need for large-scale production of graphene will inevitably lead to synthesis of the polycrystalline material [1,2]. Understanding the chemical, mechanical, and electronic properties of grain boundaries in graphene polycrystals will be crucial for the development of graphene-based electronics. Oxidation of this material has been suggested to lead to graphene ribbons, by the oxygen-driven unzipping mechanism. A cooperative-strain mechanism, based on the formation of epoxy groups along lines of parallel bonds in the hexagons of graphene's honeycomb lattice, was proposed to explain the unzipping effect in bulk graphene In this work we employ ab initio calculations to study the oxidation of polycrystalline graphene by chemisorption of oxygen at the grain boundaries. Our results indicate that oxygen tends to segregate at the boundaries, and that the unzipping mechanism is also operative along the grain boundaries, despite the lack of the parallel bonds due to the presence of fivefold and sevenfold carbon rings along the boundary core. We acknowledge support from the Brazilian agencies: CNPq, Fapemig, and INCT-Materiais de Carbono.

GPU accelerated particle visualization with Splotch

NASA Astrophysics Data System (ADS)

Rivi, M.; Gheller, C.; Dykes, T.; Krokos, M.; Dolag, K.

2014-07-01

Splotch is a rendering algorithm for exploration and visual discovery in particle-based datasets coming from astronomical observations or numerical simulations. The strengths of the approach are production of high quality imagery and support for very large-scale datasets through an effective mix of the OpenMP and MPI parallel programming paradigms. This article reports our experiences in re-designing Splotch for exploiting emerging HPC architectures nowadays increasingly populated with GPUs. A performance model is introduced to guide our re-factoring of Splotch. A number of parallelization issues are discussed, in particular relating to race conditions and workload balancing, towards achieving optimal performances. Our implementation was accomplished by using the CUDA programming paradigm. Our strategy is founded on novel schemes achieving optimized data organization and classification of particles. We deploy a reference cosmological simulation to present performance results on acceleration gains and scalability. We finally outline our vision for future work developments including possibilities for further optimizations and exploitation of hybrid systems and emerging accelerators.

Reducing computational costs in large scale 3D EIT by using a sparse Jacobian matrix with block-wise CGLS reconstruction.

PubMed

Yang, C L; Wei, H Y; Adler, A; Soleimani, M

2013-06-01

Electrical impedance tomography (EIT) is a fast and cost-effective technique to provide a tomographic conductivity image of a subject from boundary current-voltage data. This paper proposes a time and memory efficient method for solving a large scale 3D EIT inverse problem using a parallel conjugate gradient (CG) algorithm. The 3D EIT system with a large number of measurement data can produce a large size of Jacobian matrix; this could cause difficulties in computer storage and the inversion process. One of challenges in 3D EIT is to decrease the reconstruction time and memory usage, at the same time retaining the image quality. Firstly, a sparse matrix reduction technique is proposed using thresholding to set very small values of the Jacobian matrix to zero. By adjusting the Jacobian matrix into a sparse format, the element with zeros would be eliminated, which results in a saving of memory requirement. Secondly, a block-wise CG method for parallel reconstruction has been developed. The proposed method has been tested using simulated data as well as experimental test samples. Sparse Jacobian with a block-wise CG enables the large scale EIT problem to be solved efficiently. Image quality measures are presented to quantify the effect of sparse matrix reduction in reconstruction results.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rizzi, Silvio; Hereld, Mark; Insley, Joseph

In this work we perform in-situ visualization of molecular dynamics simulations, which can help scientists to visualize simulation output on-the-fly, without incurring storage overheads. We present a case study to couple LAMMPS, the large-scale molecular dynamics simulation code with vl3, our parallel framework for large-scale visualization and analysis. Our motivation is to identify effective approaches for covisualization and exploration of large-scale atomistic simulations at interactive frame rates.We propose a system of coupled libraries and describe its architecture, with an implementation that runs on GPU-based clusters. We present the results of strong and weak scalability experiments, as well as future researchmore » avenues based on our results.« less

Analysis and optimization of gyrokinetic toroidal simulations on homogenous and heterogenous platforms

DOE PAGES

Ibrahim, Khaled Z.; Madduri, Kamesh; Williams, Samuel; ...

2013-07-18

The Gyrokinetic Toroidal Code (GTC) uses the particle-in-cell method to efficiently simulate plasma microturbulence. This paper presents novel analysis and optimization techniques to enhance the performance of GTC on large-scale machines. We introduce cell access analysis to better manage locality vs. synchronization tradeoffs on CPU and GPU-based architectures. Finally, our optimized hybrid parallel implementation of GTC uses MPI, OpenMP, and NVIDIA CUDA, achieves up to a 2× speedup over the reference Fortran version on multiple parallel systems, and scales efficiently to tens of thousands of cores.

Applying Parallel Adaptive Methods with GeoFEST/PYRAMID to Simulate Earth Surface Crustal Dynamics

NASA Technical Reports Server (NTRS)

Norton, Charles D.; Lyzenga, Greg; Parker, Jay; Glasscoe, Margaret; Donnellan, Andrea; Li, Peggy

2006-01-01

This viewgraph presentation reviews the use Adaptive Mesh Refinement (AMR) in simulating the Crustal Dynamics of Earth's Surface. AMR simultaneously improves solution quality, time to solution, and computer memory requirements when compared to generating/running on a globally fine mesh. The use of AMR in simulating the dynamics of the Earth's Surface is spurred by future proposed NASA missions, such as InSAR for Earth surface deformation and other measurements. These missions will require support for large-scale adaptive numerical methods using AMR to model observations. AMR was chosen because it has been successful in computation fluid dynamics for predictive simulation of complex flows around complex structures.

A global database with parallel measurements to study non-climatic changes

NASA Astrophysics Data System (ADS)

Venema, Victor; Auchmann, Renate; Aguilar, Enric; Auer, Ingeborg; Azorin-Molina, Cesar; Brandsma, Theo; Brunetti, Michele; Dienst, Manuel; Domonkos, Peter; Gilabert, Alba; Lindén, Jenny; Milewska, Ewa; Nordli, Øyvind; Prohom, Marc; Rennie, Jared; Stepanek, Petr; Trewin, Blair; Vincent, Lucie; Willett, Kate; Wolff, Mareile

2016-04-01

In this work we introduce the rationale behind the ongoing compilation of a parallel measurements database, in the framework of the International Surface Temperatures Initiative (ISTI) and with the support of the World Meteorological Organization. We intend this database to become instrumental for a better understanding of inhomogeneities affecting the evaluation of long-term changes in daily climate data. Long instrumental climate records are usually affected by non-climatic changes, due to, e.g., (i) station relocations, (ii) instrument height changes, (iii) instrumentation changes, (iv) observing environment changes, (v) different sampling intervals or data collection procedures, among others. These so-called inhomogeneities distort the climate signal and can hamper the assessment of long-term trends and variability of climate. Thus to study climatic changes we need to accurately distinguish non-climatic and climatic signals. The most direct way to study the influence of non-climatic changes on the distribution and to understand the reasons for these biases is the analysis of parallel measurements representing the old and new situation (in terms of e.g. instruments, location, different radiation shields, etc.). According to the limited number of available studies and our understanding of the causes of inhomogeneity, we expect that they will have a strong impact on the tails of the distribution of air temperatures and most likely of other climate elements. Our abilities to statistically homogenize daily data will be increased by systematically studying different causes of inhomogeneity replicated through parallel measurements. Current studies of non-climatic changes using parallel data are limited to local and regional case studies. However, the effect of specific transitions depends on the local climate and the most interesting climatic questions are about the systematic large-scale biases produced by transitions that occurred in many regions. Important potentially biasing transitions are the adoption of Stevenson screens, relocations (to airports) efforts to reduce undercatchment of precipitation or the move to automatic weather stations. Thus a large global parallel dataset is highly desirable as it allows for the study of systematic biases in the global record. We are interested in data from all climate variables at all time scales; from annual to sub-daily. High-resolution data is important for understanding the physical causes for the differences between the parallel measurements. For the same reason, we are also interested in other climate variables measured at the same station. For example, in case of parallel air temperature measurements, the influencing factors are expected to be global radiation, wind, humidity and cloud cover; in case of parallel precipitation measurements, wind and wet-bulb temperature are potentially important. Metadata that describe the parallel measurements is as important as the data itself and will be collected as well. For example, the types of the instruments, their siting, height, maintenance, etc. Because they are widely used to study moderate extremes, we will compute the indices of the Expert Team on Climate Change Detection and Indices (ETCCDI). In case the daily data cannot be shared, we would appreciate contributions containing these indices from parallel measurements. For more information: http://tinyurl.com/ISTI-Parallel

RAMA: A file system for massively parallel computers

NASA Technical Reports Server (NTRS)

Miller, Ethan L.; Katz, Randy H.

1993-01-01

This paper describes a file system design for massively parallel computers which makes very efficient use of a few disks per processor. This overcomes the traditional I/O bottleneck of massively parallel machines by storing the data on disks within the high-speed interconnection network. In addition, the file system, called RAMA, requires little inter-node synchronization, removing another common bottleneck in parallel processor file systems. Support for a large tertiary storage system can easily be integrated in lo the file system; in fact, RAMA runs most efficiently when tertiary storage is used.

MapReduce Based Parallel Neural Networks in Enabling Large Scale Machine Learning

PubMed Central

Yang, Jie; Huang, Yuan; Xu, Lixiong; Li, Siguang; Qi, Man

2015-01-01

Artificial neural networks (ANNs) have been widely used in pattern recognition and classification applications. However, ANNs are notably slow in computation especially when the size of data is large. Nowadays, big data has received a momentum from both industry and academia. To fulfill the potentials of ANNs for big data applications, the computation process must be speeded up. For this purpose, this paper parallelizes neural networks based on MapReduce, which has become a major computing model to facilitate data intensive applications. Three data intensive scenarios are considered in the parallelization process in terms of the volume of classification data, the size of the training data, and the number of neurons in the neural network. The performance of the parallelized neural networks is evaluated in an experimental MapReduce computer cluster from the aspects of accuracy in classification and efficiency in computation. PMID:26681933

MapReduce Based Parallel Neural Networks in Enabling Large Scale Machine Learning.

PubMed

Liu, Yang; Yang, Jie; Huang, Yuan; Xu, Lixiong; Li, Siguang; Qi, Man

2015-01-01

Artificial neural networks (ANNs) have been widely used in pattern recognition and classification applications. However, ANNs are notably slow in computation especially when the size of data is large. Nowadays, big data has received a momentum from both industry and academia. To fulfill the potentials of ANNs for big data applications, the computation process must be speeded up. For this purpose, this paper parallelizes neural networks based on MapReduce, which has become a major computing model to facilitate data intensive applications. Three data intensive scenarios are considered in the parallelization process in terms of the volume of classification data, the size of the training data, and the number of neurons in the neural network. The performance of the parallelized neural networks is evaluated in an experimental MapReduce computer cluster from the aspects of accuracy in classification and efficiency in computation.

Program Correctness, Verification and Testing for Exascale (Corvette)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sen, Koushik; Iancu, Costin; Demmel, James W

The goal of this project is to provide tools to assess the correctness of parallel programs written using hybrid parallelism. There is a dire lack of both theoretical and engineering know-how in the area of finding bugs in hybrid or large scale parallel programs, which our research aims to change. In the project we have demonstrated novel approaches in several areas: 1. Low overhead automated and precise detection of concurrency bugs at scale. 2. Using low overhead bug detection tools to guide speculative program transformations for performance. 3. Techniques to reduce the concurrency required to reproduce a bug using partialmore » program restart/replay. 4. Techniques to provide reproducible execution of floating point programs. 5. Techniques for tuning the floating point precision used in codes.« less

Genome sequencing in microfabricated high-density picolitre reactors.

PubMed

Margulies, Marcel; Egholm, Michael; Altman, William E; Attiya, Said; Bader, Joel S; Bemben, Lisa A; Berka, Jan; Braverman, Michael S; Chen, Yi-Ju; Chen, Zhoutao; Dewell, Scott B; Du, Lei; Fierro, Joseph M; Gomes, Xavier V; Godwin, Brian C; He, Wen; Helgesen, Scott; Ho, Chun Heen; Ho, Chun He; Irzyk, Gerard P; Jando, Szilveszter C; Alenquer, Maria L I; Jarvie, Thomas P; Jirage, Kshama B; Kim, Jong-Bum; Knight, James R; Lanza, Janna R; Leamon, John H; Lefkowitz, Steven M; Lei, Ming; Li, Jing; Lohman, Kenton L; Lu, Hong; Makhijani, Vinod B; McDade, Keith E; McKenna, Michael P; Myers, Eugene W; Nickerson, Elizabeth; Nobile, John R; Plant, Ramona; Puc, Bernard P; Ronan, Michael T; Roth, George T; Sarkis, Gary J; Simons, Jan Fredrik; Simpson, John W; Srinivasan, Maithreyan; Tartaro, Karrie R; Tomasz, Alexander; Vogt, Kari A; Volkmer, Greg A; Wang, Shally H; Wang, Yong; Weiner, Michael P; Yu, Pengguang; Begley, Richard F; Rothberg, Jonathan M

2005-09-15

The proliferation of large-scale DNA-sequencing projects in recent years has driven a search for alternative methods to reduce time and cost. Here we describe a scalable, highly parallel sequencing system with raw throughput significantly greater than that of state-of-the-art capillary electrophoresis instruments. The apparatus uses a novel fibre-optic slide of individual wells and is able to sequence 25 million bases, at 99% or better accuracy, in one four-hour run. To achieve an approximately 100-fold increase in throughput over current Sanger sequencing technology, we have developed an emulsion method for DNA amplification and an instrument for sequencing by synthesis using a pyrosequencing protocol optimized for solid support and picolitre-scale volumes. Here we show the utility, throughput, accuracy and robustness of this system by shotgun sequencing and de novo assembly of the Mycoplasma genitalium genome with 96% coverage at 99.96% accuracy in one run of the machine.

Machine Learning Toolkit for Extreme Scale

DOE Office of Scientific and Technical Information (OSTI.GOV)

2014-03-31

Support Vector Machines (SVM) is a popular machine learning technique, which has been applied to a wide range of domains such as science, finance, and social networks for supervised learning. MaTEx undertakes the challenge of designing a scalable parallel SVM training algorithm for large scale systems, which includes commodity multi-core machines, tightly connected supercomputers and cloud computing systems. Several techniques are proposed for improved speed and memory space usage including adaptive and aggressive elimination of samples for faster convergence , and sparse format representation of data samples. Several heuristics for earliest possible to lazy elimination of non-contributing samples are consideredmore » in MaTEx. In many cases, where an early sample elimination might result in a false positive, low overhead mechanisms for reconstruction of key data structures are proposed. The proposed algorithm and heuristics are implemented and evaluated on various publicly available datasets« less

Scalable Preconditioners for Structure Preserving Discretizations of Maxwell Equations in First Order Form

DOE PAGES

Phillips, Edward Geoffrey; Shadid, John N.; Cyr, Eric C.

2018-05-01

Here, we report multiple physical time-scales can arise in electromagnetic simulations when dissipative effects are introduced through boundary conditions, when currents follow external time-scales, and when material parameters vary spatially. In such scenarios, the time-scales of interest may be much slower than the fastest time-scales supported by the Maxwell equations, therefore making implicit time integration an efficient approach. The use of implicit temporal discretizations results in linear systems in which fast time-scales, which severely constrain the stability of an explicit method, can manifest as so-called stiff modes. This study proposes a new block preconditioner for structure preserving (also termed physicsmore » compatible) discretizations of the Maxwell equations in first order form. The intent of the preconditioner is to enable the efficient solution of multiple-time-scale Maxwell type systems. An additional benefit of the developed preconditioner is that it requires only a traditional multigrid method for its subsolves and compares well against alternative approaches that rely on specialized edge-based multigrid routines that may not be readily available. Lastly, results demonstrate parallel scalability at large electromagnetic wave CFL numbers on a variety of test problems.« less

Scalable Preconditioners for Structure Preserving Discretizations of Maxwell Equations in First Order Form

DOE Office of Scientific and Technical Information (OSTI.GOV)

Phillips, Edward Geoffrey; Shadid, John N.; Cyr, Eric C.

Here, we report multiple physical time-scales can arise in electromagnetic simulations when dissipative effects are introduced through boundary conditions, when currents follow external time-scales, and when material parameters vary spatially. In such scenarios, the time-scales of interest may be much slower than the fastest time-scales supported by the Maxwell equations, therefore making implicit time integration an efficient approach. The use of implicit temporal discretizations results in linear systems in which fast time-scales, which severely constrain the stability of an explicit method, can manifest as so-called stiff modes. This study proposes a new block preconditioner for structure preserving (also termed physicsmore » compatible) discretizations of the Maxwell equations in first order form. The intent of the preconditioner is to enable the efficient solution of multiple-time-scale Maxwell type systems. An additional benefit of the developed preconditioner is that it requires only a traditional multigrid method for its subsolves and compares well against alternative approaches that rely on specialized edge-based multigrid routines that may not be readily available. Lastly, results demonstrate parallel scalability at large electromagnetic wave CFL numbers on a variety of test problems.« less

A scalable parallel black oil simulator on distributed memory parallel computers

NASA Astrophysics Data System (ADS)

Wang, Kun; Liu, Hui; Chen, Zhangxin

2015-11-01

This paper presents our work on developing a parallel black oil simulator for distributed memory computers based on our in-house parallel platform. The parallel simulator is designed to overcome the performance issues of common simulators that are implemented for personal computers and workstations. The finite difference method is applied to discretize the black oil model. In addition, some advanced techniques are employed to strengthen the robustness and parallel scalability of the simulator, including an inexact Newton method, matrix decoupling methods, and algebraic multigrid methods. A new multi-stage preconditioner is proposed to accelerate the solution of linear systems from the Newton methods. Numerical experiments show that our simulator is scalable and efficient, and is capable of simulating extremely large-scale black oil problems with tens of millions of grid blocks using thousands of MPI processes on parallel computers.

PIPER: Performance Insight for Programmers and Exascale Runtimes: Guiding the Development of the Exascale Software Stack

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mellor-Crummey, John

The PIPER project set out to develop methodologies and software for measurement, analysis, attribution, and presentation of performance data for extreme-scale systems. Goals of the project were to support analysis of massive multi-scale parallelism, heterogeneous architectures, multi-faceted performance concerns, and to support both post-mortem performance analysis to identify program features that contribute to problematic performance and on-line performance analysis to drive adaptation. This final report summarizes the research and development activity at Rice University as part of the PIPER project. Producing a complete suite of performance tools for exascale platforms during the course of this project was impossible since bothmore » hardware and software for exascale systems is still a moving target. For that reason, the project focused broadly on the development of new techniques for measurement and analysis of performance on modern parallel architectures, enhancements to HPCToolkit’s software infrastructure to support our research goals or use on sophisticated applications, engaging developers of multithreaded runtimes to explore how support for tools should be integrated into their designs, engaging operating system developers with feature requests for enhanced monitoring support, engaging vendors with requests that they add hardware measure- ment capabilities and software interfaces needed by tools as they design new components of HPC platforms including processors, accelerators and networks, and finally collaborations with partners interested in using HPCToolkit to analyze and tune scalable parallel applications.« less

Kink-style detachment folding in Bachu fold belt of central Tarim Basin, China: geometry and seismic interpretation

NASA Astrophysics Data System (ADS)

Bo, Zhang; Jinjiang, Zhang; Shuyu, Yan; Jiang, Liu; Jinhai, Zhang; Zhongpei, Zhang

2010-05-01

The phenomenon of Kink banding is well known throughout the engineering and geophysical sciences. Associated with layered structures compressed in a layer-parallel direction, it arises for example in stratified geological systems under tectonic compression. Our work documented it is also possible to develop super large-scale kink-bands in sedimentary sequences. We interpret the Bachu fold uplift belt of the central Tarim basin in western China to be composed of detachment folds flanked by megascopic-scale kink-bands. Those previous principal fold models for the Bachu uplift belt incorporated components of large-scale thrust faulting, such as the imbricate fault-related fold model and the high-angle, reverse-faulted detachment fold model. Based on our observations in the outcrops and on the two-dimension seismic profiles, we interpret that first-order structures in the region are kink-band style detachment folds to accommodate regional shortening, and thrust faulting can be a second-order deformation style occurring on the limb of the detachment folds or at the cores of some folds to accommodate the further strain of these folds. The belt mainly consists of detachment folds overlying a ductile decollement layer. The crests of the detachment folds are bounded by large-scale kink-bands, which are zones of angularly folded strata. These low-signal-tonoise, low-reflectivity zones observed on seismic profiles across the Bachu belt are poorly imaged sections, which resulted from steeply dipping bedding in the kink-bands. The substantial width (beyond 200m) of these low-reflectivity zones, their sub-parallel edges in cross section, and their orientations at a high angle to layering between 50 and 60 degrees, as well as their conjugate geometry, support a kink-band interpretation. The kink-band interpretation model is based on the Maximum Effective Moment Criteria for continuous deformation, rather than Mohr-Column Criteria for brittle fracture. Seismic modeling is done to identify the characteristics and natures of seismic waves within the kink-band and its fold structure, which supplies the further evidences for the kink-band interpretation in the region.

The application of parallel wells to support the use of groundwater for sustainable irrigation

NASA Astrophysics Data System (ADS)

Suhardi

2018-05-01

The use of groundwater as a source of irrigation is one alternative in meeting water needs of plants. Using groundwater for irrigation requires a high cost because of the discharge that can be taken is limited. In addition, the use of large groundwater can cause environmental damage and social conflict. To minimize costs, maintain quality of the environment and to prevent social conflicts, it is necessary to innovate in the groundwater taking system. The study was conducted with an innovation of using parallel wells. Performance is measured by comparing parallel wells with a single well. The results showed that the use of parallel wells to meet the water needs of rice plants and increase the pump discharge up to 100%. In addition, parallel wells can reduce the influence radius of taking of groundwater compared to single well so as to prevent social conflict. Thus, the use of parallel wells can support the achievement of the use of groundwater for sustainable irrigation.

Parallel Adjective High-Order CFD Simulations Characterizing SOFIA Cavity Acoustics

NASA Technical Reports Server (NTRS)

Barad, Michael F.; Brehm, Christoph; Kiris, Cetin C.; Biswas, Rupak

2016-01-01

This paper presents large-scale MPI-parallel computational uid dynamics simulations for the Stratospheric Observatory for Infrared Astronomy (SOFIA). SOFIA is an airborne, 2.5-meter infrared telescope mounted in an open cavity in the aft fuselage of a Boeing 747SP. These simulations focus on how the unsteady ow eld inside and over the cavity interferes with the optical path and mounting structure of the telescope. A temporally fourth-order accurate Runge-Kutta, and spatially fth-order accurate WENO- 5Z scheme was used to perform implicit large eddy simulations. An immersed boundary method provides automated gridding for complex geometries and natural coupling to a block-structured Cartesian adaptive mesh re nement framework. Strong scaling studies using NASA's Pleiades supercomputer with up to 32k CPU cores and 4 billion compu- tational cells shows excellent scaling. Dynamic load balancing based on execution time on individual AMR blocks addresses irregular numerical cost associated with blocks con- taining boundaries. Limits to scaling beyond 32k cores are identi ed, and targeted code optimizations are discussed.

Parallel Adaptive High-Order CFD Simulations Characterizing SOFIA Cavitiy Acoustics

NASA Technical Reports Server (NTRS)

Barad, Michael F.; Brehm, Christoph; Kiris, Cetin C.; Biswas, Rupak

2015-01-01

This paper presents large-scale MPI-parallel computational uid dynamics simulations for the Stratospheric Observatory for Infrared Astronomy (SOFIA). SOFIA is an airborne, 2.5-meter infrared telescope mounted in an open cavity in the aft fuselage of a Boeing 747SP. These simulations focus on how the unsteady ow eld inside and over the cavity interferes with the optical path and mounting structure of the telescope. A tempo- rally fourth-order accurate Runge-Kutta, and a spatially fth-order accurate WENO-5Z scheme were used to perform implicit large eddy simulations. An immersed boundary method provides automated gridding for complex geometries and natural coupling to a block-structured Cartesian adaptive mesh re nement framework. Strong scaling studies using NASA's Pleiades supercomputer with up to 32k CPU cores and 4 billion compu- tational cells shows excellent scaling. Dynamic load balancing based on execution time on individual AMR blocks addresses irregular numerical cost associated with blocks con- taining boundaries. Limits to scaling beyond 32k cores are identi ed, and targeted code optimizations are discussed.

Eddy diffusivity of quasi-neutrally-buoyant inertial particles

NASA Astrophysics Data System (ADS)

Martins Afonso, Marco; Muratore-Ginanneschi, Paolo; Gama, Sílvio M. A.; Mazzino, Andrea

2018-04-01

We investigate the large-scale transport properties of quasi-neutrally-buoyant inertial particles carried by incompressible zero-mean periodic or steady ergodic flows. We show how to compute large-scale indicators such as the inertial-particle terminal velocity and eddy diffusivity from first principles in a perturbative expansion around the limit of added-mass factor close to unity. Physically, this limit corresponds to the case where the mass density of the particles is constant and close in value to the mass density of the fluid, which is also constant. Our approach differs from the usual over-damped expansion inasmuch as we do not assume a separation of time scales between thermalization and small-scale convection effects. For a general flow in the class of incompressible zero-mean periodic velocity fields, we derive closed-form cell equations for the auxiliary quantities determining the terminal velocity and effective diffusivity. In the special case of parallel flows these equations admit explicit analytic solution. We use parallel flows to show that our approach sheds light onto the behavior of terminal velocity and effective diffusivity for Stokes numbers of the order of unity.

The Ophidia framework: toward cloud-based data analytics for climate change

NASA Astrophysics Data System (ADS)

Fiore, Sandro; D'Anca, Alessandro; Elia, Donatello; Mancini, Marco; Mariello, Andrea; Mirto, Maria; Palazzo, Cosimo; Aloisio, Giovanni

2015-04-01

The Ophidia project is a research effort on big data analytics facing scientific data analysis challenges in the climate change domain. It provides parallel (server-side) data analysis, an internal storage model and a hierarchical data organization to manage large amount of multidimensional scientific data. The Ophidia analytics platform provides several MPI-based parallel operators to manipulate large datasets (data cubes) and array-based primitives to perform data analysis on large arrays of scientific data. The most relevant data analytics use cases implemented in national and international projects target fire danger prevention (OFIDIA), interactions between climate change and biodiversity (EUBrazilCC), climate indicators and remote data analysis (CLIP-C), sea situational awareness (TESSA), large scale data analytics on CMIP5 data in NetCDF format, Climate and Forecast (CF) convention compliant (ExArch). Two use cases regarding the EU FP7 EUBrazil Cloud Connect and the INTERREG OFIDIA projects will be presented during the talk. In the former case (EUBrazilCC) the Ophidia framework is being extended to integrate scalable VM-based solutions for the management of large volumes of scientific data (both climate and satellite data) in a cloud-based environment to study how climate change affects biodiversity. In the latter one (OFIDIA) the data analytics framework is being exploited to provide operational support regarding processing chains devoted to fire danger prevention. To tackle the project challenges, data analytics workflows consisting of about 130 operators perform, among the others, parallel data analysis, metadata management, virtual file system tasks, maps generation, rolling of datasets, import/export of datasets in NetCDF format. Finally, the entire Ophidia software stack has been deployed at CMCC on 24-nodes (16-cores/node) of the Athena HPC cluster. Moreover, a cloud-based release tested with OpenNebula is also available and running in the private cloud infrastructure of the CMCC Supercomputing Centre.

Characterizing parallel file-access patterns on a large-scale multiprocessor

NASA Technical Reports Server (NTRS)

Purakayastha, A.; Ellis, Carla; Kotz, David; Nieuwejaar, Nils; Best, Michael L.

1995-01-01

High-performance parallel file systems are needed to satisfy tremendous I/O requirements of parallel scientific applications. The design of such high-performance parallel file systems depends on a comprehensive understanding of the expected workload, but so far there have been very few usage studies of multiprocessor file systems. This paper is part of the CHARISMA project, which intends to fill this void by measuring real file-system workloads on various production parallel machines. In particular, we present results from the CM-5 at the National Center for Supercomputing Applications. Our results are unique because we collect information about nearly every individual I/O request from the mix of jobs running on the machine. Analysis of the traces leads to various recommendations for parallel file-system design.

The build up of the correlation between halo spin and the large-scale structure

NASA Astrophysics Data System (ADS)

Wang, Peng; Kang, Xi

2018-01-01

Both simulations and observations have confirmed that the spin of haloes/galaxies is correlated with the large-scale structure (LSS) with a mass dependence such that the spin of low-mass haloes/galaxies tend to be parallel with the LSS, while that of massive haloes/galaxies tend to be perpendicular with the LSS. It is still unclear how this mass dependence is built up over time. We use N-body simulations to trace the evolution of the halo spin-LSS correlation and find that at early times the spin of all halo progenitors is parallel with the LSS. As time goes on, mass collapsing around massive halo is more isotropic, especially the recent mass accretion along the slowest collapsing direction is significant and it brings the halo spin to be perpendicular with the LSS. Adopting the fractional anisotropy (FA) parameter to describe the degree of anisotropy of the large-scale environment, we find that the spin-LSS correlation is a strong function of the environment such that a higher FA (more anisotropic environment) leads to an aligned signal, and a lower anisotropy leads to a misaligned signal. In general, our results show that the spin-LSS correlation is a combined consequence of mass flow and halo growth within the cosmic web. Our predicted environmental dependence between spin and large-scale structure can be further tested using galaxy surveys.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chrisochoides, N.; Sukup, F.

In this paper we present a parallel implementation of the Bowyer-Watson (BW) algorithm using the task-parallel programming model. The BW algorithm constitutes an ideal mesh refinement strategy for implementing a large class of unstructured mesh generation techniques on both sequential and parallel computers, by preventing the need for global mesh refinement. Its implementation on distributed memory multicomputes using the traditional data-parallel model has been proven very inefficient due to excessive synchronization needed among processors. In this paper we demonstrate that with the task-parallel model we can tolerate synchronization costs inherent to data-parallel methods by exploring concurrency in the processor level.more » Our preliminary performance data indicate that the task- parallel approach: (i) is almost four times faster than the existing data-parallel methods, (ii) scales linearly, and (iii) introduces minimum overheads compared to the {open_quotes}best{close_quotes} sequential implementation of the BW algorithm.« less

Heart beats in the cloud: distributed analysis of electrophysiological ‘Big Data’ using cloud computing for epilepsy clinical research

PubMed Central

Sahoo, Satya S; Jayapandian, Catherine; Garg, Gaurav; Kaffashi, Farhad; Chung, Stephanie; Bozorgi, Alireza; Chen, Chien-Hun; Loparo, Kenneth; Lhatoo, Samden D; Zhang, Guo-Qiang

2014-01-01

Objective The rapidly growing volume of multimodal electrophysiological signal data is playing a critical role in patient care and clinical research across multiple disease domains, such as epilepsy and sleep medicine. To facilitate secondary use of these data, there is an urgent need to develop novel algorithms and informatics approaches using new cloud computing technologies as well as ontologies for collaborative multicenter studies. Materials and methods We present the Cloudwave platform, which (a) defines parallelized algorithms for computing cardiac measures using the MapReduce parallel programming framework, (b) supports real-time interaction with large volumes of electrophysiological signals, and (c) features signal visualization and querying functionalities using an ontology-driven web-based interface. Cloudwave is currently used in the multicenter National Institute of Neurological Diseases and Stroke (NINDS)-funded Prevention and Risk Identification of SUDEP (sudden unexplained death in epilepsy) Mortality (PRISM) project to identify risk factors for sudden death in epilepsy. Results Comparative evaluations of Cloudwave with traditional desktop approaches to compute cardiac measures (eg, QRS complexes, RR intervals, and instantaneous heart rate) on epilepsy patient data show one order of magnitude improvement for single-channel ECG data and 20 times improvement for four-channel ECG data. This enables Cloudwave to support real-time user interaction with signal data, which is semantically annotated with a novel epilepsy and seizure ontology. Discussion Data privacy is a critical issue in using cloud infrastructure, and cloud platforms, such as Amazon Web Services, offer features to support Health Insurance Portability and Accountability Act standards. Conclusion The Cloudwave platform is a new approach to leverage of large-scale electrophysiological data for advancing multicenter clinical research. PMID:24326538

Heart beats in the cloud: distributed analysis of electrophysiological 'Big Data' using cloud computing for epilepsy clinical research.

PubMed

Sahoo, Satya S; Jayapandian, Catherine; Garg, Gaurav; Kaffashi, Farhad; Chung, Stephanie; Bozorgi, Alireza; Chen, Chien-Hun; Loparo, Kenneth; Lhatoo, Samden D; Zhang, Guo-Qiang

2014-01-01

The rapidly growing volume of multimodal electrophysiological signal data is playing a critical role in patient care and clinical research across multiple disease domains, such as epilepsy and sleep medicine. To facilitate secondary use of these data, there is an urgent need to develop novel algorithms and informatics approaches using new cloud computing technologies as well as ontologies for collaborative multicenter studies. We present the Cloudwave platform, which (a) defines parallelized algorithms for computing cardiac measures using the MapReduce parallel programming framework, (b) supports real-time interaction with large volumes of electrophysiological signals, and (c) features signal visualization and querying functionalities using an ontology-driven web-based interface. Cloudwave is currently used in the multicenter National Institute of Neurological Diseases and Stroke (NINDS)-funded Prevention and Risk Identification of SUDEP (sudden unexplained death in epilepsy) Mortality (PRISM) project to identify risk factors for sudden death in epilepsy. Comparative evaluations of Cloudwave with traditional desktop approaches to compute cardiac measures (eg, QRS complexes, RR intervals, and instantaneous heart rate) on epilepsy patient data show one order of magnitude improvement for single-channel ECG data and 20 times improvement for four-channel ECG data. This enables Cloudwave to support real-time user interaction with signal data, which is semantically annotated with a novel epilepsy and seizure ontology. Data privacy is a critical issue in using cloud infrastructure, and cloud platforms, such as Amazon Web Services, offer features to support Health Insurance Portability and Accountability Act standards. The Cloudwave platform is a new approach to leverage of large-scale electrophysiological data for advancing multicenter clinical research.

Building up the spin - orbit alignment of interacting galaxy pairs

NASA Astrophysics Data System (ADS)

Moon, Jun-Sung; Yoon, Suk-Jin

2018-01-01

Galaxies are not just randomly distributed throughout space. Instead, they are in alignment over a wide range of scales from the cosmic web down to a pair of galaxies. Motivated by recent findings that the spin and the orbital angular momentum vectors of galaxy pairs tend to be parallel, we here investigate the spin - orbit orientation in close pairs using the Illustris cosmological simulation. We find that since z ~ 1, the parallel alignment has become progressively stronger with time through repetitive encounters. The pair Interactions are preferentially in prograde at z = 0 (over 5 sigma significance). The prograde fraction at z = 0 is larger for the pairs influenced more heavily by each other during their evolution. We find no correlation between the spin - orbit orientation and the surrounding large-scale structure. Our results favor the scenario in which the alignment in close pairs is caused by tidal interactions later on, rather than the primordial torquing by the large-scale structures.

Amplitudes and Anisotropies at Kinetic Scales in Reflection-Driven Turbulence

NASA Astrophysics Data System (ADS)

Chandran, B. D. G.; Perez, J. C.

2016-12-01

The dissipation processes in solar-wind turbulence depend critically on the amplitudes and anisotropies of the fluctuations at kinetic scales. For example, the efficiencies of nonlinear dissipation mechanisms such as stochastic heating are a strongly increasing function of the kinetic-scale fluctuation amplitudes. In addition, ``slab-like'' fluctuations that vary most rapidly parallel to the background magnetic field dissipate very differently than ``quasi-2D'' fluctuations that vary most rapidly perpendicular to the magnetic field. Both the amplitudes and anisotropies of the kinetic-scale fluctuations are heavily influenced by the cascade mechanisms and spectral scalings in the inertial range of the turbulence. More precisely, the properties and dynamics of the turbulence within the inertial range (at ``fluid length scales'') to a large extent determine the amplitudes and anisotropies of the fluctuations at the proton kinetic scales, which bound the inertial range from below. In this presentation I will describe recent work by Jean Perez and myself on direct numerical simulations of non-compressive turbulence at ``fluid length scales'' between the Sun and a heliocentric distance of 65 solar radii. These simulations account for the non-WKB reflection of outward-propagating Alfven-wave-like fluctuations. This partial reflection produces Sunward-propagating fluctuations, which interact with the outward-propagating fluctuations to produce turbulence and a cascade of energy from large scales to small scales. I will discuss the relative strength of the parallel and perpendicular energy cascades in our simulations, and the implications of our results for the spatial anisotropies of non-compressive fluctuations at the proton kinetic scales near the Sun. I will also present results on the parallel and perpendicular power spectra of both outward-propagating and inward-propagating Alfven-wave-like fluctuations at different heliocentric distances. I will discuss the implications of these inertial-range spectra for the relative importance of cyclotron heating, stochastic heating, and Landau damping.

A Stream Tilling Approach to Surface Area Estimation for Large Scale Spatial Data in a Shared Memory System

NASA Astrophysics Data System (ADS)

Liu, Jiping; Kang, Xiaochen; Dong, Chun; Xu, Shenghua

2017-12-01

Surface area estimation is a widely used tool for resource evaluation in the physical world. When processing large scale spatial data, the input/output (I/O) can easily become the bottleneck in parallelizing the algorithm due to the limited physical memory resources and the very slow disk transfer rate. In this paper, we proposed a stream tilling approach to surface area estimation that first decomposed a spatial data set into tiles with topological expansions. With these tiles, the one-to-one mapping relationship between the input and the computing process was broken. Then, we realized a streaming framework towards the scheduling of the I/O processes and computing units. Herein, each computing unit encapsulated a same copy of the estimation algorithm, and multiple asynchronous computing units could work individually in parallel. Finally, the performed experiment demonstrated that our stream tilling estimation can efficiently alleviate the heavy pressures from the I/O-bound work, and the measured speedup after being optimized have greatly outperformed the directly parallel versions in shared memory systems with multi-core processors.

Large-eddy simulations of compressible convection on massively parallel computers. [stellar physics

NASA Technical Reports Server (NTRS)

Xie, Xin; Toomre, Juri

1993-01-01

We report preliminary implementation of the large-eddy simulation (LES) technique in 2D simulations of compressible convection carried out on the CM-2 massively parallel computer. The convective flow fields in our simulations possess structures similar to those found in a number of direct simulations, with roll-like flows coherent across the entire depth of the layer that spans several density scale heights. Our detailed assessment of the effects of various subgrid scale (SGS) terms reveals that they may affect the gross character of convection. Yet, somewhat surprisingly, we find that our LES solutions, and another in which the SGS terms are turned off, only show modest differences. The resulting 2D flows realized here are rather laminar in character, and achieving substantial turbulence may require stronger forcing and less dissipation.

Large-scale parallel genome assembler over cloud computing environment.

PubMed

Das, Arghya Kusum; Koppa, Praveen Kumar; Goswami, Sayan; Platania, Richard; Park, Seung-Jong

2017-06-01

The size of high throughput DNA sequencing data has already reached the terabyte scale. To manage this huge volume of data, many downstream sequencing applications started using locality-based computing over different cloud infrastructures to take advantage of elastic (pay as you go) resources at a lower cost. However, the locality-based programming model (e.g. MapReduce) is relatively new. Consequently, developing scalable data-intensive bioinformatics applications using this model and understanding the hardware environment that these applications require for good performance, both require further research. In this paper, we present a de Bruijn graph oriented Parallel Giraph-based Genome Assembler (GiGA), as well as the hardware platform required for its optimal performance. GiGA uses the power of Hadoop (MapReduce) and Giraph (large-scale graph analysis) to achieve high scalability over hundreds of compute nodes by collocating the computation and data. GiGA achieves significantly higher scalability with competitive assembly quality compared to contemporary parallel assemblers (e.g. ABySS and Contrail) over traditional HPC cluster. Moreover, we show that the performance of GiGA is significantly improved by using an SSD-based private cloud infrastructure over traditional HPC cluster. We observe that the performance of GiGA on 256 cores of this SSD-based cloud infrastructure closely matches that of 512 cores of traditional HPC cluster.

HAlign-II: efficient ultra-large multiple sequence alignment and phylogenetic tree reconstruction with distributed and parallel computing.

PubMed

Wan, Shixiang; Zou, Quan

2017-01-01

Multiple sequence alignment (MSA) plays a key role in biological sequence analyses, especially in phylogenetic tree construction. Extreme increase in next-generation sequencing results in shortage of efficient ultra-large biological sequence alignment approaches for coping with different sequence types. Distributed and parallel computing represents a crucial technique for accelerating ultra-large (e.g. files more than 1 GB) sequence analyses. Based on HAlign and Spark distributed computing system, we implement a highly cost-efficient and time-efficient HAlign-II tool to address ultra-large multiple biological sequence alignment and phylogenetic tree construction. The experiments in the DNA and protein large scale data sets, which are more than 1GB files, showed that HAlign II could save time and space. It outperformed the current software tools. HAlign-II can efficiently carry out MSA and construct phylogenetic trees with ultra-large numbers of biological sequences. HAlign-II shows extremely high memory efficiency and scales well with increases in computing resource. THAlign-II provides a user-friendly web server based on our distributed computing infrastructure. HAlign-II with open-source codes and datasets was established at http://lab.malab.cn/soft/halign.

Space Technology 5 Multipoint Observations of Temporal and Spatial Variability of Field-Aligned Currents

NASA Technical Reports Server (NTRS)

Le, G.; Wang, Y.; Slavin, J. A.; Strangeway, R. L.

2009-01-01

Space Technology 5 (ST5) is a constellation mission consisting of three microsatellites. It provides the first multipoint magnetic field measurements in low Earth orbit, which enables us to separate spatial and temporal variations. In this paper, we present a study of the temporal variability of field-aligned currents using the ST5 data. We examine the field-aligned current observations during and after a geomagnetic storm and compare the magnetic field profiles at the three spacecraft. The multipoint data demonstrate that mesoscale current structures, commonly embedded within large-scale current sheets, are very dynamic with highly variable current density and/or polarity in approx.10 min time scales. On the other hand, the data also show that the time scales for the currents to be relatively stable are approx.1 min for mesoscale currents and approx.10 min for large-scale currents. These temporal features are very likely associated with dynamic variations of their charge carriers (mainly electrons) as they respond to the variations of the parallel electric field in auroral acceleration region. The characteristic time scales for the temporal variability of mesoscale field-aligned currents are found to be consistent with those of auroral parallel electric field.

Scalable Visual Analytics of Massive Textual Datasets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Krishnan, Manoj Kumar; Bohn, Shawn J.; Cowley, Wendy E.

2007-04-01

This paper describes the first scalable implementation of text processing engine used in Visual Analytics tools. These tools aid information analysts in interacting with and understanding large textual information content through visual interfaces. By developing parallel implementation of the text processing engine, we enabled visual analytics tools to exploit cluster architectures and handle massive dataset. The paper describes key elements of our parallelization approach and demonstrates virtually linear scaling when processing multi-gigabyte data sets such as Pubmed. This approach enables interactive analysis of large datasets beyond capabilities of existing state-of-the art visual analytics tools.

Solving Navier-Stokes equations on a massively parallel processor; The 1 GFLOP performance

DOE Office of Scientific and Technical Information (OSTI.GOV)

Saati, A.; Biringen, S.; Farhat, C.

This paper reports on experience in solving large-scale fluid dynamics problems on the Connection Machine model CM-2. The authors have implemented a parallel version of the MacCormack scheme for the solution of the Navier-Stokes equations. By using triad floating point operations and reducing the number of interprocessor communications, they have achieved a sustained performance rate of 1.42 GFLOPS.

LASER APPLICATIONS AND OTHER TOPICS IN QUANTUM ELECTRONICS: Application of the stochastic parallel gradient descent algorithm for numerical simulation and analysis of the coherent summation of radiation from fibre amplifiers

NASA Astrophysics Data System (ADS)

Zhou, Pu; Wang, Xiaolin; Li, Xiao; Chen, Zilum; Xu, Xiaojun; Liu, Zejin

2009-10-01

Coherent summation of fibre laser beams, which can be scaled to a relatively large number of elements, is simulated by using the stochastic parallel gradient descent (SPGD) algorithm. The applicability of this algorithm for coherent summation is analysed and its optimisaton parameters and bandwidth limitations are studied.

Parallel computation with the force

NASA Technical Reports Server (NTRS)

Jordan, H. F.

1985-01-01

A methodology, called the force, supports the construction of programs to be executed in parallel by a force of processes. The number of processes in the force is unspecified, but potentially very large. The force idea is embodied in a set of macros which produce multiproceossor FORTRAN code and has been studied on two shared memory multiprocessors of fairly different character. The method has simplified the writing of highly parallel programs within a limited class of parallel algorithms and is being extended to cover a broader class. The individual parallel constructs which comprise the force methodology are discussed. Of central concern are their semantics, implementation on different architectures and performance implications.

Large-Scale Modeling of Epileptic Seizures: Scaling Properties of Two Parallel Neuronal Network Simulation Algorithms

DOE PAGES

Pesce, Lorenzo L.; Lee, Hyong C.; Hereld, Mark; ...

2013-01-01

Our limited understanding of the relationship between the behavior of individual neurons and large neuronal networks is an important limitation in current epilepsy research and may be one of the main causes of our inadequate ability to treat it. Addressing this problem directly via experiments is impossibly complex; thus, we have been developing and studying medium-large-scale simulations of detailed neuronal networks to guide us. Flexibility in the connection schemas and a complete description of the cortical tissue seem necessary for this purpose. In this paper we examine some of the basic issues encountered in these multiscale simulations. We have determinedmore » the detailed behavior of two such simulators on parallel computer systems. The observed memory and computation-time scaling behavior for a distributed memory implementation were very good over the range studied, both in terms of network sizes (2,000 to 400,000 neurons) and processor pool sizes (1 to 256 processors). Our simulations required between a few megabytes and about 150 gigabytes of RAM and lasted between a few minutes and about a week, well within the capability of most multinode clusters. Therefore, simulations of epileptic seizures on networks with millions of cells should be feasible on current supercomputers.« less

Continental-scale patterns of canopy tree composition and function across Amazonia.

PubMed

ter Steege, Hans; Pitman, Nigel C A; Phillips, Oliver L; Chave, Jerome; Sabatier, Daniel; Duque, Alvaro; Molino, Jean-François; Prévost, Marie-Françoise; Spichiger, Rodolphe; Castellanos, Hernán; von Hildebrand, Patricio; Vásquez, Rodolfo

2006-09-28

The world's greatest terrestrial stores of biodiversity and carbon are found in the forests of northern South America, where large-scale biogeographic patterns and processes have recently begun to be described. Seven of the nine countries with territory in the Amazon basin and the Guiana shield have carried out large-scale forest inventories, but such massive data sets have been little exploited by tropical plant ecologists. Although forest inventories often lack the species-level identifications favoured by tropical plant ecologists, their consistency of measurement and vast spatial coverage make them ideally suited for numerical analyses at large scales, and a valuable resource to describe the still poorly understood spatial variation of biomass, diversity, community composition and forest functioning across the South American tropics. Here we show, by using the seven forest inventories complemented with trait and inventory data collected elsewhere, two dominant gradients in tree composition and function across the Amazon, one paralleling a major gradient in soil fertility and the other paralleling a gradient in dry season length. The data set also indicates that the dominance of Fabaceae in the Guiana shield is not necessarily the result of root adaptations to poor soils (nodulation or ectomycorrhizal associations) but perhaps also the result of their remarkably high seed mass there as a potential adaptation to low rates of disturbance.

Continental-scale patterns of canopy tree composition and function across Amazonia

NASA Astrophysics Data System (ADS)

Ter Steege, Hans; Pitman, Nigel C. A.; Phillips, Oliver L.; Chave, Jerome; Sabatier, Daniel; Duque, Alvaro; Molino, Jean-François; Prévost, Marie-Françoise; Spichiger, Rodolphe; Castellanos, Hernán; von Hildebrand, Patricio; Vásquez, Rodolfo

2006-09-01

The world's greatest terrestrial stores of biodiversity and carbon are found in the forests of northern South America, where large-scale biogeographic patterns and processes have recently begun to be described. Seven of the nine countries with territory in the Amazon basin and the Guiana shield have carried out large-scale forest inventories, but such massive data sets have been little exploited by tropical plant ecologists. Although forest inventories often lack the species-level identifications favoured by tropical plant ecologists, their consistency of measurement and vast spatial coverage make them ideally suited for numerical analyses at large scales, and a valuable resource to describe the still poorly understood spatial variation of biomass, diversity, community composition and forest functioning across the South American tropics. Here we show, by using the seven forest inventories complemented with trait and inventory data collected elsewhere, two dominant gradients in tree composition and function across the Amazon, one paralleling a major gradient in soil fertility and the other paralleling a gradient in dry season length. The data set also indicates that the dominance of Fabaceae in the Guiana shield is not necessarily the result of root adaptations to poor soils (nodulation or ectomycorrhizal associations) but perhaps also the result of their remarkably high seed mass there as a potential adaptation to low rates of disturbance.

Generating Billion-Edge Scale-Free Networks in Seconds: Performance Study of a Novel GPU-based Preferential Attachment Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Perumalla, Kalyan S.; Alam, Maksudul

A novel parallel algorithm is presented for generating random scale-free networks using the preferential-attachment model. The algorithm, named cuPPA, is custom-designed for single instruction multiple data (SIMD) style of parallel processing supported by modern processors such as graphical processing units (GPUs). To the best of our knowledge, our algorithm is the first to exploit GPUs, and also the fastest implementation available today, to generate scale free networks using the preferential attachment model. A detailed performance study is presented to understand the scalability and runtime characteristics of the cuPPA algorithm. In one of the best cases, when executed on an NVidiamore » GeForce 1080 GPU, cuPPA generates a scale free network of a billion edges in less than 2 seconds.« less

Xyce Parallel Electronic Simulator - Users' Guide Version 2.1.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hutchinson, Scott A; Hoekstra, Robert J.; Russo, Thomas V.

This manual describes the use of theXyceParallel Electronic Simulator.Xycehasbeen designed as a SPICE-compatible, high-performance analog circuit simulator, andhas been written to support the simulation needs of the Sandia National Laboratorieselectrical designers. This development has focused on improving capability over thecurrent state-of-the-art in the following areas:%04Capability to solve extremely large circuit problems by supporting large-scale par-allel computing platforms (up to thousands of processors). Note that this includessupport for most popular parallel and serial computers.%04Improved performance for all numerical kernels (e.g., time integrator, nonlinearand linear solvers) through state-of-the-art algorithms and novel techniques.%04Device models which are specifically tailored to meet Sandia's needs, includingmanymore » radiation-aware devices.3 XyceTMUsers' Guide%04Object-oriented code design and implementation using modern coding practicesthat ensure that theXyceParallel Electronic Simulator will be maintainable andextensible far into the future.Xyceis a parallel code in the most general sense of the phrase - a message passingparallel implementation - which allows it to run efficiently on the widest possible numberof computing platforms. These include serial, shared-memory and distributed-memoryparallel as well as heterogeneous platforms. Careful attention has been paid to thespecific nature of circuit-simulation problems to ensure that optimal parallel efficiencyis achieved as the number of processors grows.The development ofXyceprovides a platform for computational research and de-velopment aimed specifically at the needs of the Laboratory. WithXyce, Sandia hasan %22in-house%22 capability with which both new electrical (e.g., device model develop-ment) and algorithmic (e.g., faster time-integration methods, parallel solver algorithms)research and development can be performed. As a result,Xyceis a unique electricalsimulation capability, designed to meet the unique needs of the laboratory.4 XyceTMUsers' GuideAcknowledgementsThe authors would like to acknowledge the entire Sandia National Laboratories HPEMS(High Performance Electrical Modeling and Simulation) team, including Steve Wix, CarolynBogdan, Regina Schells, Ken Marx, Steve Brandon and Bill Ballard, for their support onthis project. We also appreciate very much the work of Jim Emery, Becky Arnold and MikeWilliamson for the help in reviewing this document.Lastly, a very special thanks to Hue Lai for typesetting this document with LATEX.TrademarksThe information herein is subject to change without notice.Copyrightc 2002-2003 Sandia Corporation. All rights reserved.XyceTMElectronic Simulator andXyceTMtrademarks of Sandia Corporation.Orcad, Orcad Capture, PSpice and Probe are registered trademarks of Cadence DesignSystems, Inc.Silicon Graphics, the Silicon Graphics logo and IRIX are registered trademarks of SiliconGraphics, Inc.Microsoft, Windows and Windows 2000 are registered trademark of Microsoft Corporation.Solaris and UltraSPARC are registered trademarks of Sun Microsystems Corporation.Medici, DaVinci and Taurus are registered trademarks of Synopsys Corporation.HP and Alpha are registered trademarks of Hewlett-Packard company.Amtec and TecPlot are trademarks of Amtec Engineering, Inc.Xyce's expression library is based on that inside Spice 3F5 developed by the EECS De-partment at the University of California.All other trademarks are property of their respective owners.ContactsBug Reportshttp://tvrusso.sandia.gov/bugzillaEmailxyce-support%40sandia.govWorld Wide Webhttp://www.cs.sandia.gov/xyce5 XyceTMUsers' GuideThis page is left intentionally blank6« less

Preparing for Exascale: Towards convection-permitting, global atmospheric simulations with the Model for Prediction Across Scales (MPAS)

NASA Astrophysics Data System (ADS)

Heinzeller, Dominikus; Duda, Michael G.; Kunstmann, Harald

2017-04-01

With strong financial and political support from national and international initiatives, exascale computing is projected for the end of this decade. Energy requirements and physical limitations imply the use of accelerators and the scaling out to orders of magnitudes larger numbers of cores then today to achieve this milestone. In order to fully exploit the capabilities of these Exascale computing systems, existing applications need to undergo significant development. The Model for Prediction Across Scales (MPAS) is a novel set of Earth system simulation components and consists of an atmospheric core, an ocean core, a land-ice core and a sea-ice core. Its distinct features are the use of unstructured Voronoi meshes and C-grid discretisation to address shortcomings of global models on regular grids and the use of limited area models nested in a forcing data set, with respect to parallel scalability, numerical accuracy and physical consistency. Here, we present work towards the application of the atmospheric core (MPAS-A) on current and future high performance computing systems for problems at extreme scale. In particular, we address the issue of massively parallel I/O by extending the model to support the highly scalable SIONlib library. Using global uniform meshes with a convection-permitting resolution of 2-3km, we demonstrate the ability of MPAS-A to scale out to half a million cores while maintaining a high parallel efficiency. We also demonstrate the potential benefit of a hybrid parallelisation of the code (MPI/OpenMP) on the latest generation of Intel's Many Integrated Core Architecture, the Intel Xeon Phi Knights Landing.

A Parallel Adaboost-Backpropagation Neural Network for Massive Image Dataset Classification

NASA Astrophysics Data System (ADS)

Cao, Jianfang; Chen, Lichao; Wang, Min; Shi, Hao; Tian, Yun

2016-12-01

Image classification uses computers to simulate human understanding and cognition of images by automatically categorizing images. This study proposes a faster image classification approach that parallelizes the traditional Adaboost-Backpropagation (BP) neural network using the MapReduce parallel programming model. First, we construct a strong classifier by assembling the outputs of 15 BP neural networks (which are individually regarded as weak classifiers) based on the Adaboost algorithm. Second, we design Map and Reduce tasks for both the parallel Adaboost-BP neural network and the feature extraction algorithm. Finally, we establish an automated classification model by building a Hadoop cluster. We use the Pascal VOC2007 and Caltech256 datasets to train and test the classification model. The results are superior to those obtained using traditional Adaboost-BP neural network or parallel BP neural network approaches. Our approach increased the average classification accuracy rate by approximately 14.5% and 26.0% compared to the traditional Adaboost-BP neural network and parallel BP neural network, respectively. Furthermore, the proposed approach requires less computation time and scales very well as evaluated by speedup, sizeup and scaleup. The proposed approach may provide a foundation for automated large-scale image classification and demonstrates practical value.

A Parallel Adaboost-Backpropagation Neural Network for Massive Image Dataset Classification.

PubMed

Cao, Jianfang; Chen, Lichao; Wang, Min; Shi, Hao; Tian, Yun

2016-12-01

Image classification uses computers to simulate human understanding and cognition of images by automatically categorizing images. This study proposes a faster image classification approach that parallelizes the traditional Adaboost-Backpropagation (BP) neural network using the MapReduce parallel programming model. First, we construct a strong classifier by assembling the outputs of 15 BP neural networks (which are individually regarded as weak classifiers) based on the Adaboost algorithm. Second, we design Map and Reduce tasks for both the parallel Adaboost-BP neural network and the feature extraction algorithm. Finally, we establish an automated classification model by building a Hadoop cluster. We use the Pascal VOC2007 and Caltech256 datasets to train and test the classification model. The results are superior to those obtained using traditional Adaboost-BP neural network or parallel BP neural network approaches. Our approach increased the average classification accuracy rate by approximately 14.5% and 26.0% compared to the traditional Adaboost-BP neural network and parallel BP neural network, respectively. Furthermore, the proposed approach requires less computation time and scales very well as evaluated by speedup, sizeup and scaleup. The proposed approach may provide a foundation for automated large-scale image classification and demonstrates practical value.

Parallel Tensor Compression for Large-Scale Scientific Data.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kolda, Tamara G.; Ballard, Grey; Austin, Woody Nathan

As parallel computing trends towards the exascale, scientific data produced by high-fidelity simulations are growing increasingly massive. For instance, a simulation on a three-dimensional spatial grid with 512 points per dimension that tracks 64 variables per grid point for 128 time steps yields 8 TB of data. By viewing the data as a dense five way tensor, we can compute a Tucker decomposition to find inherent low-dimensional multilinear structure, achieving compression ratios of up to 10000 on real-world data sets with negligible loss in accuracy. So that we can operate on such massive data, we present the first-ever distributed memorymore » parallel implementation for the Tucker decomposition, whose key computations correspond to parallel linear algebra operations, albeit with nonstandard data layouts. Our approach specifies a data distribution for tensors that avoids any tensor data redistribution, either locally or in parallel. We provide accompanying analysis of the computation and communication costs of the algorithms. To demonstrate the compression and accuracy of the method, we apply our approach to real-world data sets from combustion science simulations. We also provide detailed performance results, including parallel performance in both weak and strong scaling experiments.« less

A Parallel Adaboost-Backpropagation Neural Network for Massive Image Dataset Classification

PubMed Central

Cao, Jianfang; Chen, Lichao; Wang, Min; Shi, Hao; Tian, Yun

2016-01-01

Image classification uses computers to simulate human understanding and cognition of images by automatically categorizing images. This study proposes a faster image classification approach that parallelizes the traditional Adaboost-Backpropagation (BP) neural network using the MapReduce parallel programming model. First, we construct a strong classifier by assembling the outputs of 15 BP neural networks (which are individually regarded as weak classifiers) based on the Adaboost algorithm. Second, we design Map and Reduce tasks for both the parallel Adaboost-BP neural network and the feature extraction algorithm. Finally, we establish an automated classification model by building a Hadoop cluster. We use the Pascal VOC2007 and Caltech256 datasets to train and test the classification model. The results are superior to those obtained using traditional Adaboost-BP neural network or parallel BP neural network approaches. Our approach increased the average classification accuracy rate by approximately 14.5% and 26.0% compared to the traditional Adaboost-BP neural network and parallel BP neural network, respectively. Furthermore, the proposed approach requires less computation time and scales very well as evaluated by speedup, sizeup and scaleup. The proposed approach may provide a foundation for automated large-scale image classification and demonstrates practical value. PMID:27905520

Parallel scalability of Hartree-Fock calculations

NASA Astrophysics Data System (ADS)

Chow, Edmond; Liu, Xing; Smelyanskiy, Mikhail; Hammond, Jeff R.

2015-03-01

Quantum chemistry is increasingly performed using large cluster computers consisting of multiple interconnected nodes. For a fixed molecular problem, the efficiency of a calculation usually decreases as more nodes are used, due to the cost of communication between the nodes. This paper empirically investigates the parallel scalability of Hartree-Fock calculations. The construction of the Fock matrix and the density matrix calculation are analyzed separately. For the former, we use a parallelization of Fock matrix construction based on a static partitioning of work followed by a work stealing phase. For the latter, we use density matrix purification from the linear scaling methods literature, but without using sparsity. When using large numbers of nodes for moderately sized problems, density matrix computations are network-bandwidth bound, making purification methods potentially faster than eigendecomposition methods.

Implementation and performance of FDPS: a framework for developing parallel particle simulation codes

NASA Astrophysics Data System (ADS)

Iwasawa, Masaki; Tanikawa, Ataru; Hosono, Natsuki; Nitadori, Keigo; Muranushi, Takayuki; Makino, Junichiro

2016-08-01

We present the basic idea, implementation, measured performance, and performance model of FDPS (Framework for Developing Particle Simulators). FDPS is an application-development framework which helps researchers to develop simulation programs using particle methods for large-scale distributed-memory parallel supercomputers. A particle-based simulation program for distributed-memory parallel computers needs to perform domain decomposition, exchange of particles which are not in the domain of each computing node, and gathering of the particle information in other nodes which are necessary for interaction calculation. Also, even if distributed-memory parallel computers are not used, in order to reduce the amount of computation, algorithms such as the Barnes-Hut tree algorithm or the Fast Multipole Method should be used in the case of long-range interactions. For short-range interactions, some methods to limit the calculation to neighbor particles are required. FDPS provides all of these functions which are necessary for efficient parallel execution of particle-based simulations as "templates," which are independent of the actual data structure of particles and the functional form of the particle-particle interaction. By using FDPS, researchers can write their programs with the amount of work necessary to write a simple, sequential and unoptimized program of O(N2) calculation cost, and yet the program, once compiled with FDPS, will run efficiently on large-scale parallel supercomputers. A simple gravitational N-body program can be written in around 120 lines. We report the actual performance of these programs and the performance model. The weak scaling performance is very good, and almost linear speed-up was obtained for up to the full system of the K computer. The minimum calculation time per timestep is in the range of 30 ms (N = 107) to 300 ms (N = 109). These are currently limited by the time for the calculation of the domain decomposition and communication necessary for the interaction calculation. We discuss how we can overcome these bottlenecks.

Architectural Implications for Spatial Object Association Algorithms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kumar, V S; Kurc, T; Saltz, J

2009-01-29

Spatial object association, also referred to as cross-match of spatial datasets, is the problem of identifying and comparing objects in two or more datasets based on their positions in a common spatial coordinate system. In this work, we evaluate two crossmatch algorithms that are used for astronomical sky surveys, on the following database system architecture configurations: (1) Netezza Performance Server R, a parallel database system with active disk style processing capabilities, (2) MySQL Cluster, a high-throughput network database system, and (3) a hybrid configuration consisting of a collection of independent database system instances with data replication support. Our evaluation providesmore » insights about how architectural characteristics of these systems affect the performance of the spatial crossmatch algorithms. We conducted our study using real use-case scenarios borrowed from a large-scale astronomy application known as the Large Synoptic Survey Telescope (LSST).« less

MOLNs: A CLOUD PLATFORM FOR INTERACTIVE, REPRODUCIBLE, AND SCALABLE SPATIAL STOCHASTIC COMPUTATIONAL EXPERIMENTS IN SYSTEMS BIOLOGY USING PyURDME

PubMed Central

Drawert, Brian; Trogdon, Michael; Toor, Salman; Petzold, Linda; Hellander, Andreas

2017-01-01

Computational experiments using spatial stochastic simulations have led to important new biological insights, but they require specialized tools and a complex software stack, as well as large and scalable compute and data analysis resources due to the large computational cost associated with Monte Carlo computational workflows. The complexity of setting up and managing a large-scale distributed computation environment to support productive and reproducible modeling can be prohibitive for practitioners in systems biology. This results in a barrier to the adoption of spatial stochastic simulation tools, effectively limiting the type of biological questions addressed by quantitative modeling. In this paper, we present PyURDME, a new, user-friendly spatial modeling and simulation package, and MOLNs, a cloud computing appliance for distributed simulation of stochastic reaction-diffusion models. MOLNs is based on IPython and provides an interactive programming platform for development of sharable and reproducible distributed parallel computational experiments. PMID:28190948

Reverse engineering and analysis of large genome-scale gene networks

PubMed Central

Aluru, Maneesha; Zola, Jaroslaw; Nettleton, Dan; Aluru, Srinivas

2013-01-01

Reverse engineering the whole-genome networks of complex multicellular organisms continues to remain a challenge. While simpler models easily scale to large number of genes and gene expression datasets, more accurate models are compute intensive limiting their scale of applicability. To enable fast and accurate reconstruction of large networks, we developed Tool for Inferring Network of Genes (TINGe), a parallel mutual information (MI)-based program. The novel features of our approach include: (i) B-spline-based formulation for linear-time computation of MI, (ii) a novel algorithm for direct permutation testing and (iii) development of parallel algorithms to reduce run-time and facilitate construction of large networks. We assess the quality of our method by comparison with ARACNe (Algorithm for the Reconstruction of Accurate Cellular Networks) and GeneNet and demonstrate its unique capability by reverse engineering the whole-genome network of Arabidopsis thaliana from 3137 Affymetrix ATH1 GeneChips in just 9 min on a 1024-core cluster. We further report on the development of a new software Gene Network Analyzer (GeNA) for extracting context-specific subnetworks from a given set of seed genes. Using TINGe and GeNA, we performed analysis of 241 Arabidopsis AraCyc 8.0 pathways, and the results are made available through the web. PMID:23042249

Argonne Simulation Framework for Intelligent Transportation Systems

DOT National Transportation Integrated Search

1996-01-01

A simulation framework has been developed which defines a high-level architecture for a large-scale, comprehensive, scalable simulation of an Intelligent Transportation System (ITS). The simulator is designed to run on parallel computers and distribu...

Astrophysical N-body Simulations Using Hierarchical Tree Data Structures

NASA Astrophysics Data System (ADS)

Warren, M. S.; Salmon, J. K.

The authors report on recent large astrophysical N-body simulations executed on the Intel Touchstone Delta system. They review the astrophysical motivation and the numerical techniques and discuss steps taken to parallelize these simulations. The methods scale as O(N log N), for large values of N, and also scale linearly with the number of processors. The performance sustained for a duration of 67 h, was between 5.1 and 5.4 Gflop/s on a 512-processor system.

Mesh-free data transfer algorithms for partitioned multiphysics problems: Conservation, accuracy, and parallelism

DOE PAGES

Slattery, Stuart R.

2015-12-02

In this study we analyze and extend mesh-free algorithms for three-dimensional data transfer problems in partitioned multiphysics simulations. We first provide a direct comparison between a mesh-based weighted residual method using the common-refinement scheme and two mesh-free algorithms leveraging compactly supported radial basis functions: one using a spline interpolation and one using a moving least square reconstruction. Through the comparison we assess both the conservation and accuracy of the data transfer obtained from each of the methods. We do so for a varying set of geometries with and without curvature and sharp features and for functions with and without smoothnessmore » and with varying gradients. Our results show that the mesh-based and mesh-free algorithms are complementary with cases where each was demonstrated to perform better than the other. We then focus on the mesh-free methods by developing a set of algorithms to parallelize them based on sparse linear algebra techniques. This includes a discussion of fast parallel radius searching in point clouds and restructuring the interpolation algorithms to leverage data structures and linear algebra services designed for large distributed computing environments. The scalability of our new algorithms is demonstrated on a leadership class computing facility using a set of basic scaling studies. Finally, these scaling studies show that for problems with reasonable load balance, our new algorithms for both spline interpolation and moving least square reconstruction demonstrate both strong and weak scalability using more than 100,000 MPI processes with billions of degrees of freedom in the data transfer operation.« less

Massive Cloud Computing Processing of P-SBAS Time Series for Displacement Analyses at Large Spatial Scale

NASA Astrophysics Data System (ADS)

Casu, F.; de Luca, C.; Lanari, R.; Manunta, M.; Zinno, I.

2016-12-01

A methodology for computing surface deformation time series and mean velocity maps of large areas is presented. Our approach relies on the availability of a multi-temporal set of Synthetic Aperture Radar (SAR) data collected from ascending and descending orbits over an area of interest, and also permits to estimate the vertical and horizontal (East-West) displacement components of the Earth's surface. The adopted methodology is based on an advanced Cloud Computing implementation of the Differential SAR Interferometry (DInSAR) Parallel Small Baseline Subset (P-SBAS) processing chain which allows the unsupervised processing of large SAR data volumes, from the raw data (level-0) imagery up to the generation of DInSAR time series and maps. The presented solution, which is highly scalable, has been tested on the ascending and descending ENVISAT SAR archives, which have been acquired over a large area of Southern California (US) that extends for about 90.000 km2. Such an input dataset has been processed in parallel by exploiting 280 computing nodes of the Amazon Web Services Cloud environment. Moreover, to produce the final mean deformation velocity maps of the vertical and East-West displacement components of the whole investigated area, we took also advantage of the information available from external GPS measurements that permit to account for possible regional trends not easily detectable by DInSAR and to refer the P-SBAS measurements to an external geodetic datum. The presented results clearly demonstrate the effectiveness of the proposed approach that paves the way to the extensive use of the available ERS and ENVISAT SAR data archives. Furthermore, the proposed methodology can be particularly suitable to deal with the very huge data flow provided by the Sentinel-1 constellation, thus permitting to extend the DInSAR analyses at a nearly global scale. This work is partially supported by: the DPC-CNR agreement, the EPOS-IP project and the ESA GEP project.

A model for optimizing file access patterns using spatio-temporal parallelism

DOE Office of Scientific and Technical Information (OSTI.GOV)

Boonthanome, Nouanesengsy; Patchett, John; Geveci, Berk

2013-01-01

For many years now, I/O read time has been recognized as the primary bottleneck for parallel visualization and analysis of large-scale data. In this paper, we introduce a model that can estimate the read time for a file stored in a parallel filesystem when given the file access pattern. Read times ultimately depend on how the file is stored and the access pattern used to read the file. The file access pattern will be dictated by the type of parallel decomposition used. We employ spatio-temporal parallelism, which combines both spatial and temporal parallelism, to provide greater flexibility to possible filemore » access patterns. Using our model, we were able to configure the spatio-temporal parallelism to design optimized read access patterns that resulted in a speedup factor of approximately 400 over traditional file access patterns.« less

Parallel Computation of the Regional Ocean Modeling System (ROMS)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, P; Song, Y T; Chao, Y

2005-04-05

The Regional Ocean Modeling System (ROMS) is a regional ocean general circulation modeling system solving the free surface, hydrostatic, primitive equations over varying topography. It is free software distributed world-wide for studying both complex coastal ocean problems and the basin-to-global scale ocean circulation. The original ROMS code could only be run on shared-memory systems. With the increasing need to simulate larger model domains with finer resolutions and on a variety of computer platforms, there is a need in the ocean-modeling community to have a ROMS code that can be run on any parallel computer ranging from 10 to hundreds ofmore » processors. Recently, we have explored parallelization for ROMS using the MPI programming model. In this paper, an efficient parallelization strategy for such a large-scale scientific software package, based on an existing shared-memory computing model, is presented. In addition, scientific applications and data-performance issues on a couple of SGI systems, including Columbia, the world's third-fastest supercomputer, are discussed.« less

Pair-barcode high-throughput sequencing for large-scale multiplexed sample analysis

PubMed Central

2012-01-01

Background The multiplexing becomes the major limitation of the next-generation sequencing (NGS) in application to low complexity samples. Physical space segregation allows limited multiplexing, while the existing barcode approach only permits simultaneously analysis of up to several dozen samples. Results Here we introduce pair-barcode sequencing (PBS), an economic and flexible barcoding technique that permits parallel analysis of large-scale multiplexed samples. In two pilot runs using SOLiD sequencer (Applied Biosystems Inc.), 32 independent pair-barcoded miRNA libraries were simultaneously discovered by the combination of 4 unique forward barcodes and 8 unique reverse barcodes. Over 174,000,000 reads were generated and about 64% of them are assigned to both of the barcodes. After mapping all reads to pre-miRNAs in miRBase, different miRNA expression patterns are captured from the two clinical groups. The strong correlation using different barcode pairs and the high consistency of miRNA expression in two independent runs demonstrates that PBS approach is valid. Conclusions By employing PBS approach in NGS, large-scale multiplexed pooled samples could be practically analyzed in parallel so that high-throughput sequencing economically meets the requirements of samples which are low sequencing throughput demand. PMID:22276739

Pair-barcode high-throughput sequencing for large-scale multiplexed sample analysis.

PubMed

Tu, Jing; Ge, Qinyu; Wang, Shengqin; Wang, Lei; Sun, Beili; Yang, Qi; Bai, Yunfei; Lu, Zuhong

2012-01-25

The multiplexing becomes the major limitation of the next-generation sequencing (NGS) in application to low complexity samples. Physical space segregation allows limited multiplexing, while the existing barcode approach only permits simultaneously analysis of up to several dozen samples. Here we introduce pair-barcode sequencing (PBS), an economic and flexible barcoding technique that permits parallel analysis of large-scale multiplexed samples. In two pilot runs using SOLiD sequencer (Applied Biosystems Inc.), 32 independent pair-barcoded miRNA libraries were simultaneously discovered by the combination of 4 unique forward barcodes and 8 unique reverse barcodes. Over 174,000,000 reads were generated and about 64% of them are assigned to both of the barcodes. After mapping all reads to pre-miRNAs in miRBase, different miRNA expression patterns are captured from the two clinical groups. The strong correlation using different barcode pairs and the high consistency of miRNA expression in two independent runs demonstrates that PBS approach is valid. By employing PBS approach in NGS, large-scale multiplexed pooled samples could be practically analyzed in parallel so that high-throughput sequencing economically meets the requirements of samples which are low sequencing throughput demand.

Development and Evaluation of a Parallel Reaction Monitoring Strategy for Large-Scale Targeted Metabolomics Quantification.

PubMed

Zhou, Juntuo; Liu, Huiying; Liu, Yang; Liu, Jia; Zhao, Xuyang; Yin, Yuxin

2016-04-19

Recent advances in mass spectrometers which have yielded higher resolution and faster scanning speeds have expanded their application in metabolomics of diverse diseases. Using a quadrupole-Orbitrap LC-MS system, we developed an efficient large-scale quantitative method targeting 237 metabolites involved in various metabolic pathways using scheduled, parallel reaction monitoring (PRM). We assessed the dynamic range, linearity, reproducibility, and system suitability of the PRM assay by measuring concentration curves, biological samples, and clinical serum samples. The quantification performances of PRM and MS1-based assays in Q-Exactive were compared, and the MRM assay in QTRAP 6500 was also compared. The PRM assay monitoring 237 polar metabolites showed greater reproducibility and quantitative accuracy than MS1-based quantification and also showed greater flexibility in postacquisition assay refinement than the MRM assay in QTRAP 6500. We present a workflow for convenient PRM data processing using Skyline software which is free of charge. In this study we have established a reliable PRM methodology on a quadrupole-Orbitrap platform for evaluation of large-scale targeted metabolomics, which provides a new choice for basic and clinical metabolomics study.

: A Scalable and Transparent System for Simulating MPI Programs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Perumalla, Kalyan S

2010-01-01

is a scalable, transparent system for experimenting with the execution of parallel programs on simulated computing platforms. The level of simulated detail can be varied for application behavior as well as for machine characteristics. Unique features of are repeatability of execution, scalability to millions of simulated (virtual) MPI ranks, scalability to hundreds of thousands of host (real) MPI ranks, portability of the system to a variety of host supercomputing platforms, and the ability to experiment with scientific applications whose source-code is available. The set of source-code interfaces supported by is being expanded to support a wider set of applications, andmore » MPI-based scientific computing benchmarks are being ported. In proof-of-concept experiments, has been successfully exercised to spawn and sustain very large-scale executions of an MPI test program given in source code form. Low slowdowns are observed, due to its use of purely discrete event style of execution, and due to the scalability and efficiency of the underlying parallel discrete event simulation engine, sik. In the largest runs, has been executed on up to 216,000 cores of a Cray XT5 supercomputer, successfully simulating over 27 million virtual MPI ranks, each virtual rank containing its own thread context, and all ranks fully synchronized by virtual time.« less

A Multiscale Parallel Computing Architecture for Automated Segmentation of the Brain Connectome

PubMed Central

Knobe, Kathleen; Newton, Ryan R.; Schlimbach, Frank; Blower, Melanie; Reid, R. Clay

2015-01-01

Several groups in neurobiology have embarked into deciphering the brain circuitry using large-scale imaging of a mouse brain and manual tracing of the connections between neurons. Creating a graph of the brain circuitry, also called a connectome, could have a huge impact on the understanding of neurodegenerative diseases such as Alzheimer’s disease. Although considerably smaller than a human brain, a mouse brain already exhibits one billion connections and manually tracing the connectome of a mouse brain can only be achieved partially. This paper proposes to scale up the tracing by using automated image segmentation and a parallel computing approach designed for domain experts. We explain the design decisions behind our parallel approach and we present our results for the segmentation of the vasculature and the cell nuclei, which have been obtained without any manual intervention. PMID:21926011

Using Agent Base Models to Optimize Large Scale Network for Large System Inventories

NASA Technical Reports Server (NTRS)

Shameldin, Ramez Ahmed; Bowling, Shannon R.

2010-01-01

The aim of this paper is to use Agent Base Models (ABM) to optimize large scale network handling capabilities for large system inventories and to implement strategies for the purpose of reducing capital expenses. The models used in this paper either use computational algorithms or procedure implementations developed by Matlab to simulate agent based models in a principal programming language and mathematical theory using clusters, these clusters work as a high performance computational performance to run the program in parallel computational. In both cases, a model is defined as compilation of a set of structures and processes assumed to underlie the behavior of a network system.

Genetic Parallel Programming: design and implementation.

PubMed

Cheang, Sin Man; Leung, Kwong Sak; Lee, Kin Hong

2006-01-01

This paper presents a novel Genetic Parallel Programming (GPP) paradigm for evolving parallel programs running on a Multi-Arithmetic-Logic-Unit (Multi-ALU) Processor (MAP). The MAP is a Multiple Instruction-streams, Multiple Data-streams (MIMD), general-purpose register machine that can be implemented on modern Very Large-Scale Integrated Circuits (VLSIs) in order to evaluate genetic programs at high speed. For human programmers, writing parallel programs is more difficult than writing sequential programs. However, experimental results show that GPP evolves parallel programs with less computational effort than that of their sequential counterparts. It creates a new approach to evolving a feasible problem solution in parallel program form and then serializes it into a sequential program if required. The effectiveness and efficiency of GPP are investigated using a suite of 14 well-studied benchmark problems. Experimental results show that GPP speeds up evolution substantially.

Parallel-In-Time For Moving Meshes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Falgout, R. D.; Manteuffel, T. A.; Southworth, B.

2016-02-04

With steadily growing computational resources available, scientists must develop e ective ways to utilize the increased resources. High performance, highly parallel software has be- come a standard. However until recent years parallelism has focused primarily on the spatial domain. When solving a space-time partial di erential equation (PDE), this leads to a sequential bottleneck in the temporal dimension, particularly when taking a large number of time steps. The XBraid parallel-in-time library was developed as a practical way to add temporal parallelism to existing se- quential codes with only minor modi cations. In this work, a rezoning-type moving mesh is appliedmore » to a di usion problem and formulated in a parallel-in-time framework. Tests and scaling studies are run using XBraid and demonstrate excellent results for the simple model problem considered herein.« less

ParBiBit: Parallel tool for binary biclustering on modern distributed-memory systems

PubMed Central

Expósito, Roberto R.

2018-01-01

Biclustering techniques are gaining attention in the analysis of large-scale datasets as they identify two-dimensional submatrices where both rows and columns are correlated. In this work we present ParBiBit, a parallel tool to accelerate the search of interesting biclusters on binary datasets, which are very popular on different fields such as genetics, marketing or text mining. It is based on the state-of-the-art sequential Java tool BiBit, which has been proved accurate by several studies, especially on scenarios that result on many large biclusters. ParBiBit uses the same methodology as BiBit (grouping the binary information into patterns) and provides the same results. Nevertheless, our tool significantly improves performance thanks to an efficient implementation based on C++11 that includes support for threads and MPI processes in order to exploit the compute capabilities of modern distributed-memory systems, which provide several multicore CPU nodes interconnected through a network. Our performance evaluation with 18 representative input datasets on two different eight-node systems shows that our tool is significantly faster than the original BiBit. Source code in C++ and MPI running on Linux systems as well as a reference manual are available at https://sourceforge.net/projects/parbibit/. PMID:29608567

ParBiBit: Parallel tool for binary biclustering on modern distributed-memory systems.

PubMed

González-Domínguez, Jorge; Expósito, Roberto R

2018-01-01

Biclustering techniques are gaining attention in the analysis of large-scale datasets as they identify two-dimensional submatrices where both rows and columns are correlated. In this work we present ParBiBit, a parallel tool to accelerate the search of interesting biclusters on binary datasets, which are very popular on different fields such as genetics, marketing or text mining. It is based on the state-of-the-art sequential Java tool BiBit, which has been proved accurate by several studies, especially on scenarios that result on many large biclusters. ParBiBit uses the same methodology as BiBit (grouping the binary information into patterns) and provides the same results. Nevertheless, our tool significantly improves performance thanks to an efficient implementation based on C++11 that includes support for threads and MPI processes in order to exploit the compute capabilities of modern distributed-memory systems, which provide several multicore CPU nodes interconnected through a network. Our performance evaluation with 18 representative input datasets on two different eight-node systems shows that our tool is significantly faster than the original BiBit. Source code in C++ and MPI running on Linux systems as well as a reference manual are available at https://sourceforge.net/projects/parbibit/.

Scalable Metropolis Monte Carlo for simulation of hard shapes

NASA Astrophysics Data System (ADS)

Anderson, Joshua A.; Eric Irrgang, M.; Glotzer, Sharon C.

2016-07-01

We design and implement a scalable hard particle Monte Carlo simulation toolkit (HPMC), and release it open source as part of HOOMD-blue. HPMC runs in parallel on many CPUs and many GPUs using domain decomposition. We employ BVH trees instead of cell lists on the CPU for fast performance, especially with large particle size disparity, and optimize inner loops with SIMD vector intrinsics on the CPU. Our GPU kernel proposes many trial moves in parallel on a checkerboard and uses a block-level queue to redistribute work among threads and avoid divergence. HPMC supports a wide variety of shape classes, including spheres/disks, unions of spheres, convex polygons, convex spheropolygons, concave polygons, ellipsoids/ellipses, convex polyhedra, convex spheropolyhedra, spheres cut by planes, and concave polyhedra. NVT and NPT ensembles can be run in 2D or 3D triclinic boxes. Additional integration schemes permit Frenkel-Ladd free energy computations and implicit depletant simulations. In a benchmark system of a fluid of 4096 pentagons, HPMC performs 10 million sweeps in 10 min on 96 CPU cores on XSEDE Comet. The same simulation would take 7.6 h in serial. HPMC also scales to large system sizes, and the same benchmark with 16.8 million particles runs in 1.4 h on 2048 GPUs on OLCF Titan.

Strategies for Large Scale Implementation of a Multiscale, Multiprocess Integrated Hydrologic Model

NASA Astrophysics Data System (ADS)

Kumar, M.; Duffy, C.

2006-05-01

Distributed models simulate hydrologic state variables in space and time while taking into account the heterogeneities in terrain, surface, subsurface properties and meteorological forcings. Computational cost and complexity associated with these model increases with its tendency to accurately simulate the large number of interacting physical processes at fine spatio-temporal resolution in a large basin. A hydrologic model run on a coarse spatial discretization of the watershed with limited number of physical processes needs lesser computational load. But this negatively affects the accuracy of model results and restricts physical realization of the problem. So it is imperative to have an integrated modeling strategy (a) which can be universally applied at various scales in order to study the tradeoffs between computational complexity (determined by spatio- temporal resolution), accuracy and predictive uncertainty in relation to various approximations of physical processes (b) which can be applied at adaptively different spatial scales in the same domain by taking into account the local heterogeneity of topography and hydrogeologic variables c) which is flexible enough to incorporate different number and approximation of process equations depending on model purpose and computational constraint. An efficient implementation of this strategy becomes all the more important for Great Salt Lake river basin which is relatively large (~89000 sq. km) and complex in terms of hydrologic and geomorphic conditions. Also the types and the time scales of hydrologic processes which are dominant in different parts of basin are different. Part of snow melt runoff generated in the Uinta Mountains infiltrates and contributes as base flow to the Great Salt Lake over a time scale of decades to centuries. The adaptive strategy helps capture the steep topographic and climatic gradient along the Wasatch front. Here we present the aforesaid modeling strategy along with an associated hydrologic modeling framework which facilitates a seamless, computationally efficient and accurate integration of the process model with the data model. The flexibility of this framework leads to implementation of multiscale, multiresolution, adaptive refinement/de-refinement and nested modeling simulations with least computational burden. However, performing these simulations and related calibration of these models over a large basin at higher spatio- temporal resolutions is computationally intensive and requires use of increasing computing power. With the advent of parallel processing architectures, high computing performance can be achieved by parallelization of existing serial integrated-hydrologic-model code. This translates to running the same model simulation on a network of large number of processors thereby reducing the time needed to obtain solution. The paper also discusses the implementation of the integrated model on parallel processors. Also will be discussed the mapping of the problem on multi-processor environment, method to incorporate coupling between hydrologic processes using interprocessor communication models, model data structure and parallel numerical algorithms to obtain high performance.

A Discretization Algorithm for Meteorological Data and its Parallelization Based on Hadoop

NASA Astrophysics Data System (ADS)

Liu, Chao; Jin, Wen; Yu, Yuting; Qiu, Taorong; Bai, Xiaoming; Zou, Shuilong

2017-10-01

In view of the large amount of meteorological observation data, the property is more and the attribute values are continuous values, the correlation between the elements is the need for the application of meteorological data, this paper is devoted to solving the problem of how to better discretize large meteorological data to more effectively dig out the hidden knowledge in meteorological data and research on the improvement of discretization algorithm for large scale data, in order to achieve data in the large meteorological data discretization for the follow-up to better provide knowledge to provide protection, a discretization algorithm based on information entropy and inconsistency of meteorological attributes is proposed and the algorithm is parallelized under Hadoop platform. Finally, the comparison test validates the effectiveness of the proposed algorithm for discretization in the area of meteorological large data.

Parallel Computing Strategies for Irregular Algorithms

NASA Technical Reports Server (NTRS)

Biswas, Rupak; Oliker, Leonid; Shan, Hongzhang; Biegel, Bryan (Technical Monitor)

2002-01-01

Parallel computing promises several orders of magnitude increase in our ability to solve realistic computationally-intensive problems, but relies on their efficient mapping and execution on large-scale multiprocessor architectures. Unfortunately, many important applications are irregular and dynamic in nature, making their effective parallel implementation a daunting task. Moreover, with the proliferation of parallel architectures and programming paradigms, the typical scientist is faced with a plethora of questions that must be answered in order to obtain an acceptable parallel implementation of the solution algorithm. In this paper, we consider three representative irregular applications: unstructured remeshing, sparse matrix computations, and N-body problems, and parallelize them using various popular programming paradigms on a wide spectrum of computer platforms ranging from state-of-the-art supercomputers to PC clusters. We present the underlying problems, the solution algorithms, and the parallel implementation strategies. Smart load-balancing, partitioning, and ordering techniques are used to enhance parallel performance. Overall results demonstrate the complexity of efficiently parallelizing irregular algorithms.

A high-performance model for shallow-water simulations in distributed and heterogeneous architectures

NASA Astrophysics Data System (ADS)

Conde, Daniel; Canelas, Ricardo B.; Ferreira, Rui M. L.

2017-04-01

One of the most common challenges in hydrodynamic modelling is the trade off one must make between highly resolved simulations and the time required for their computation. In the particular case of urban floods, modelers are often forced to simplify the complex geometries of the problem, or to implicitly include some of its hydrodynamic effects, due to the typically very large spatial scales involved and limited computational resources. At CEris - Instituto Superior Técnico, Universidade de Lisboa - the STAV-2D shallow-water model, particularly suited for strong transient flows in complex and dynamic geometries, has been under development for the past recent years (Canelas et al., 2013 & Conde et al., 2013). The model is based on an explicit, first-order 2DH finite-volume discretization scheme for unstructured triangular meshes, in which a flux-splitting technique is paired with a reviewed Roe-Riemann solver, yielding a model applicable to discontinuous flows over time-evolving geometries. STAV-2D features solid transport in both Euleran and Lagrangian forms, with the first aiming at describing the transport of fine natural sediments and the latter aimed at large individual debris. The model has been validated with theoretical solutions and laboratory experiments (Canelas et al., 2013 & Conde et al., 2015). This work presents our most recent effort in STAV-2D: the re-design of the code in a modern Object-Oriented parallel framework for heterogeneous computations in CPUs and GPUs. The programming language of choice for this re-design was C++, due to its wide support of established and emerging parallel programming interfaces. The current implementation of STAV-2D provides two different levels of parallel granularity: inter-node and intra-node. Inter-node parallelism is achieved by distributing a simulation across a set of worker nodes, with communication between nodes being explicitly managed through MPI. At this level, the main difficulty is associated with the unstructured nature of the mesh topology with the corresponding employed solution, based on space-filling curves, being analyzed and discussed. Intra-node parallelism is achieved through OpenMP for CPUs and CUDA for GPUs, depending on which kind of device the process is running. Here the main difficulty is associated with the Object-Oriented approach, where the presence of complex data structures can degrade model performance considerably. STAV-2D now supports fully distributed and heterogeneous simulations where multiple different devices can be used to accelerate computation time. The advantages, short-comings and specific solutions for the employed unified Object-Oriented approach, where the source code for CPU and GPU has the same compilation units (no device specific branches like seen in available models), are discussed and quantified with a thorough scalability and performance analysis. The assembled parallel model is expected to achieve faster than real-time simulations for high resolutions (from meters to sub-meter) in large scaled problems (from cities to watersheds), effectively bridging the gap between detailed and timely simulation results. Acknowledgements This research as partially supported by Portuguese and European funds, within programs COMPETE2020 and PORL-FEDER, through project PTDC/ECM-HID/6387/2014 and Doctoral Grant SFRH/BD/97933/2013 granted by the National Foundation for Science and Technology (FCT). References Canelas, R.; Murillo, J. & Ferreira, R.M.L. (2013), Two-dimensional depth-averaged modelling of dam-break flows over mobile beds. Journal of Hydraulic Research, 51(4), 392-407. Conde, D. A. S.; Baptista, M. A. V.; Sousa Oliveira, C. & Ferreira, R. M. L. (2013), A shallow-flow model for the propagation of tsunamis over complex geometries and mobile beds, Nat. Hazards and Earth Syst. Sci., 13, 2533-2542. Conde, D. A. S.; Telhado, M. J.; Viana Baptista, M. A. & Ferreira, R. M. L. (2015) Severity and exposure associated with tsunami actions in urban waterfronts: the case of Lisbon, Portugal. Natural Hazards, Springer, 79, 2125, DOI:10.1007/s11069-015-1951-z

A parallel architecture of interpolated timing recovery for high- speed data transfer rate and wide capture-range

NASA Astrophysics Data System (ADS)

Higashino, Satoru; Kobayashi, Shoei; Yamagami, Tamotsu

2007-06-01

High data transfer rate has been demanded for data storage devices along increasing the storage capacity. In order to increase the transfer rate, high-speed data processing techniques in read-channel devices are required. Generally, parallel architecture is utilized for the high-speed digital processing. We have developed a new architecture of Interpolated Timing Recovery (ITR) to achieve high-speed data transfer rate and wide capture-range in read-channel devices for the information storage channels. It facilitates the parallel implementation on large-scale-integration (LSI) devices.

A giant, submarine creep zone as a precursor of large-scale slope instability offshore the Dongsha Islands (South China Sea)

NASA Astrophysics Data System (ADS)

Li, Wei; Alves, Tiago M.; Wu, Shiguo; Rebesco, Michele; Zhao, Fang; Mi, Lijun; Ma, Benjun

2016-10-01

A giant submarine creep zone exceeding 800 km2 on the continental slope offshore the Dongsha Islands, South China Sea, is investigated using bathymetric and 3D seismic data tied to borehole information. The submarine creep zone is identified as a wide area of seafloor undulations with ridges and troughs. The troughs form NW- and WNW-trending elongated depressions separating distinct seafloor ridges, which are parallel or sub-parallel to the continental slope. The troughs are 0.8-4.7 km-long and 0.4 to 2.1 km-wide. The ridges have wavelengths of 1-4 km and vertical relief of 10-30 m. Slope strata are characterised by the presence of vertically stacked ridges and troughs at different stratigraphic depths, but remaining relatively stationary in their position. The interpreted ridges and troughs are associated with large-scale submarine creep, and the troughs can be divided into three types based on their different internal characters and formation processes. The large-scale listric faults trending downslope below MTD 1 and horizon T0 may be the potential glide planes for the submarine creep movement. High sedimentation rates, local fault activity and the frequent earthquakes recorded on the margin are considered as the main factors controlling the formation of this giant submarine creep zone. Our results are important to the understanding of sediment instability on continental slopes as: a) the interpreted submarine creep is young, or even active at present, and b) areas of creeping may evolve into large-scale slope instabilities, as recorded by similar large-scale events in the past.

Dynamic load balancing of applications

DOEpatents

Wheat, Stephen R.

1997-01-01

An application-level method for dynamically maintaining global load balance on a parallel computer, particularly on massively parallel MIMD computers. Global load balancing is achieved by overlapping neighborhoods of processors, where each neighborhood performs local load balancing. The method supports a large class of finite element and finite difference based applications and provides an automatic element management system to which applications are easily integrated.

Range-wide parallel climate-associated genomic clines in Atlantic salmon

PubMed Central

Stanley, Ryan R. E.; Wringe, Brendan F.; Guijarro-Sabaniel, Javier; Bourret, Vincent; Bernatchez, Louis; Bentzen, Paul; Beiko, Robert G.; Gilbey, John; Clément, Marie; Bradbury, Ian R.

2017-01-01

Clinal variation across replicated environmental gradients can reveal evidence of local adaptation, providing insight into the demographic and evolutionary processes that shape intraspecific diversity. Using 1773 genome-wide single nucleotide polymorphisms we evaluated latitudinal variation in allele frequency for 134 populations of North American and European Atlantic salmon (Salmo salar). We detected 84 (4.74%) and 195 (11%) loci showing clinal patterns in North America and Europe, respectively, with 12 clinal loci in common between continents. Clinal single nucleotide polymorphisms were evenly distributed across the salmon genome and logistic regression revealed significant associations with latitude and seasonal temperatures, particularly average spring temperature in both continents. Loci displaying parallel clines were associated with several metabolic and immune functions, suggesting a potential basis for climate-associated adaptive differentiation. These climate-based clines collectively suggest evidence of large-scale environmental associated differences on either side of the North Atlantic. Our results support patterns of parallel evolution on both sides of the North Atlantic, with evidence of both similar and divergent underlying genetic architecture. The identification of climate-associated genomic clines illuminates the role of selection and demographic processes on intraspecific diversity in this species and provides a context in which to evaluate the impacts of climate change. PMID:29291123

PLUM: Parallel Load Balancing for Unstructured Adaptive Meshes. Degree awarded by Colorado Univ.

NASA Technical Reports Server (NTRS)

Oliker, Leonid

1998-01-01

Dynamic mesh adaption on unstructured grids is a powerful tool for computing large-scale problems that require grid modifications to efficiently resolve solution features. By locally refining and coarsening the mesh to capture physical phenomena of interest, such procedures make standard computational methods more cost effective. Unfortunately, an efficient parallel implementation of these adaptive methods is rather difficult to achieve, primarily due to the load imbalance created by the dynamically-changing nonuniform grid. This requires significant communication at runtime, leading to idle processors and adversely affecting the total execution time. Nonetheless, it is generally thought that unstructured adaptive- grid techniques will constitute a significant fraction of future high-performance supercomputing. Various dynamic load balancing methods have been reported to date; however, most of them either lack a global view of loads across processors or do not apply their techniques to realistic large-scale applications.

Dust Dynamics in Protoplanetary Disks: Parallel Computing with PVM

NASA Astrophysics Data System (ADS)

de La Fuente Marcos, Carlos; Barge, Pierre; de La Fuente Marcos, Raúl

2002-03-01

We describe a parallel version of our high-order-accuracy particle-mesh code for the simulation of collisionless protoplanetary disks. We use this code to carry out a massively parallel, two-dimensional, time-dependent, numerical simulation, which includes dust particles, to study the potential role of large-scale, gaseous vortices in protoplanetary disks. This noncollisional problem is easy to parallelize on message-passing multicomputer architectures. We performed the simulations on a cache-coherent nonuniform memory access Origin 2000 machine, using both the parallel virtual machine (PVM) and message-passing interface (MPI) message-passing libraries. Our performance analysis suggests that, for our problem, PVM is about 25% faster than MPI. Using PVM and MPI made it possible to reduce CPU time and increase code performance. This allows for simulations with a large number of particles (N ~ 105-106) in reasonable CPU times. The performances of our implementation of the pa! rallel code on an Origin 2000 supercomputer are presented and discussed. They exhibit very good speedup behavior and low load unbalancing. Our results confirm that giant gaseous vortices can play a dominant role in giant planet formation.

Scalable Performance Measurement and Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gamblin, Todd

2009-01-01

Concurrency levels in large-scale, distributed-memory supercomputers are rising exponentially. Modern machines may contain 100,000 or more microprocessor cores, and the largest of these, IBM's Blue Gene/L, contains over 200,000 cores. Future systems are expected to support millions of concurrent tasks. In this dissertation, we focus on efficient techniques for measuring and analyzing the performance of applications running on very large parallel machines. Tuning the performance of large-scale applications can be a subtle and time-consuming task because application developers must measure and interpret data from many independent processes. While the volume of the raw data scales linearly with the number ofmore » tasks in the running system, the number of tasks is growing exponentially, and data for even small systems quickly becomes unmanageable. Transporting performance data from so many processes over a network can perturb application performance and make measurements inaccurate, and storing such data would require a prohibitive amount of space. Moreover, even if it were stored, analyzing the data would be extremely time-consuming. In this dissertation, we present novel methods for reducing performance data volume. The first draws on multi-scale wavelet techniques from signal processing to compress systemwide, time-varying load-balance data. The second uses statistical sampling to select a small subset of running processes to generate low-volume traces. A third approach combines sampling and wavelet compression to stratify performance data adaptively at run-time and to reduce further the cost of sampled tracing. We have integrated these approaches into Libra, a toolset for scalable load-balance analysis. We present Libra and show how it can be used to analyze data from large scientific applications scalably.« less

Planning and executing complex large-scale exercises.

PubMed

McCormick, Lisa C; Hites, Lisle; Wakelee, Jessica F; Rucks, Andrew C; Ginter, Peter M

2014-01-01

Increasingly, public health departments are designing and engaging in complex operations-based full-scale exercises to test multiple public health preparedness response functions. The Department of Homeland Security's Homeland Security Exercise and Evaluation Program (HSEEP) supplies benchmark guidelines that provide a framework for both the design and the evaluation of drills and exercises; however, the HSEEP framework does not seem to have been designed to manage the development and evaluation of multiple, operations-based, parallel exercises combined into 1 complex large-scale event. Lessons learned from the planning of the Mississippi State Department of Health Emergency Support Function--8 involvement in National Level Exercise 2011 were used to develop an expanded exercise planning model that is HSEEP compliant but accounts for increased exercise complexity and is more functional for public health. The Expanded HSEEP (E-HSEEP) model was developed through changes in the HSEEP exercise planning process in areas of Exercise Plan, Controller/Evaluator Handbook, Evaluation Plan, and After Action Report and Improvement Plan development. The E-HSEEP model was tested and refined during the planning and evaluation of Mississippi's State-level Emergency Support Function-8 exercises in 2012 and 2013. As a result of using the E-HSEEP model, Mississippi State Department of Health was able to capture strengths, lessons learned, and areas for improvement, and identify microlevel issues that may have been missed using the traditional HSEEP framework. The South Central Preparedness and Emergency Response Learning Center is working to create an Excel-based E-HSEEP tool that will allow practice partners to build a database to track corrective actions and conduct many different types of analyses and comparisons.

Flexible language constructs for large parallel programs

NASA Technical Reports Server (NTRS)

Rosing, Matthew; Schnabel, Robert

1993-01-01

The goal of the research described is to develop flexible language constructs for writing large data parallel numerical programs for distributed memory (MIMD) multiprocessors. Previously, several models have been developed to support synchronization and communication. Models for global synchronization include SIMD (Single Instruction Multiple Data), SPMD (Single Program Multiple Data), and sequential programs annotated with data distribution statements. The two primary models for communication include implicit communication based on shared memory and explicit communication based on messages. None of these models by themselves seem sufficient to permit the natural and efficient expression of the variety of algorithms that occur in large scientific computations. An overview of a new language that combines many of these programming models in a clean manner is given. This is done in a modular fashion such that different models can be combined to support large programs. Within a module, the selection of a model depends on the algorithm and its efficiency requirements. An overview of the language and discussion of some of the critical implementation details is given.

Electron Currents and Heating in the Ion Diffusion Region of Asymmetric Reconnection

NASA Technical Reports Server (NTRS)

Graham, D. B.; Khotyaintsev, Yu. V.; Norgren, C.; Vaivads, A.; Andre, M.; Lindqvist, P. A.; Marklund, G. T.; Ergun, R. E.; Paterson, W. R.; Gershman, D. J.;

Large-Scale Hybrid Density Functional Theory Calculations in the Condensed-Phase: Ab Initio Molecular Dynamics in the Isobaric-Isothermal Ensemble

NASA Astrophysics Data System (ADS)

Ko, Hsin-Yu; Santra, Biswajit; Distasio, Robert A., Jr.; Wu, Xifan; Car, Roberto

Hybrid functionals are known to alleviate the self-interaction error in density functional theory (DFT) and provide a more accurate description of the electronic structure of molecules and materials. However, hybrid DFT in the condensed-phase has a prohibitively high associated computational cost which limits their applicability to large systems of interest. In this work, we present a general-purpose order(N) implementation of hybrid DFT in the condensed-phase using Maximally localized Wannier function; this implementation is optimized for massively parallel computing architectures. This algorithm is used to perform large-scale ab initio molecular dynamics simulations of liquid water, ice, and aqueous ionic solutions. We have performed simulations in the isothermal-isobaric ensemble to quantify the effects of exact exchange on the equilibrium density properties of water at different thermodynamic conditions. We find that the anomalous density difference between ice I h and liquid water at ambient conditions as well as the enthalpy differences between ice I h, II, and III phases at the experimental triple point (238 K and 20 Kbar) are significantly improved using hybrid DFT over previous estimates using the lower rungs of DFT This work has been supported by the Department of Energy under Grants No. DE-FG02-05ER46201 and DE-SC0008626.

Parallel Dynamics Simulation Using a Krylov-Schwarz Linear Solution Scheme

DOE PAGES

Abhyankar, Shrirang; Constantinescu, Emil M.; Smith, Barry F.; ...

2016-11-07

Fast dynamics simulation of large-scale power systems is a computational challenge because of the need to solve a large set of stiff, nonlinear differential-algebraic equations at every time step. The main bottleneck in dynamic simulations is the solution of a linear system during each nonlinear iteration of Newton’s method. In this paper, we present a parallel Krylov- Schwarz linear solution scheme that uses the Krylov subspacebased iterative linear solver GMRES with an overlapping restricted additive Schwarz preconditioner. As a result, performance tests of the proposed Krylov-Schwarz scheme for several large test cases ranging from 2,000 to 20,000 buses, including amore » real utility network, show good scalability on different computing architectures.« less

Parallel Dynamics Simulation Using a Krylov-Schwarz Linear Solution Scheme

DOE Office of Scientific and Technical Information (OSTI.GOV)

Abhyankar, Shrirang; Constantinescu, Emil M.; Smith, Barry F.

Fast dynamics simulation of large-scale power systems is a computational challenge because of the need to solve a large set of stiff, nonlinear differential-algebraic equations at every time step. The main bottleneck in dynamic simulations is the solution of a linear system during each nonlinear iteration of Newton’s method. In this paper, we present a parallel Krylov- Schwarz linear solution scheme that uses the Krylov subspacebased iterative linear solver GMRES with an overlapping restricted additive Schwarz preconditioner. As a result, performance tests of the proposed Krylov-Schwarz scheme for several large test cases ranging from 2,000 to 20,000 buses, including amore » real utility network, show good scalability on different computing architectures.« less

Magnetospheric Multiscale Observations of Large-Amplitude Parallel, Electrostatic Waves Associated with Magnetic Reconnection at the Magnetopause

NASA Technical Reports Server (NTRS)

Ergun, R. E.; Holmes, J. C.; Goodrich, K. A.; Wilder, F. D.; Stawarz, J. E.; Eriksson, S.; Newman, D. L.; Schwartz, S. J.; Goldman, M. V.; Sturner, A. P.;

Onset of a Large Ejective Solar Eruption from a Typical Coronal-jet-base Field Configuration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Joshi, Navin Chandra; Magara, Tetsuya; Moon, Yong-Jae

Utilizing multiwavelength observations and magnetic field data from the Solar Dynamics Observatory ( SDO )/Atmospheric Imaging Assembly (AIA), SDO /Helioseismic and Magnetic Imager (HMI), the Geostationary Operational Environmental Satellite ( GOES ), and RHESSI , we investigate a large-scale ejective solar eruption of 2014 December 18 from active region NOAA 12241. This event produced a distinctive “three-ribbon” flare, having two parallel ribbons corresponding to the ribbons of a standard two-ribbon flare, and a larger-scale third quasi-circular ribbon offset from the other two. There are two components to this eruptive event. First, a flux rope forms above a strong-field polarity inversionmore » line and erupts and grows as the parallel ribbons turn on, grow, and spread apart from that polarity inversion line; this evolution is consistent with the mechanism of tether-cutting reconnection for eruptions. Second, the eruption of the arcade that has the erupting flux rope in its core undergoes magnetic reconnection at the null point of a fan dome that envelops the erupting arcade, resulting in formation of the quasi-circular ribbon; this is consistent with the breakout reconnection mechanism for eruptions. We find that the parallel ribbons begin well before (∼12 minutes) the onset of the circular ribbon, indicating that tether-cutting reconnection (or a non-ideal MHD instability) initiated this event, rather than breakout reconnection. The overall setup for this large-scale eruption (diameter of the circular ribbon ∼10{sup 5} km) is analogous to that of coronal jets (base size ∼10{sup 4} km), many of which, according to recent findings, result from eruptions of small-scale “minifilaments.” Thus these findings confirm that eruptions of sheared-core magnetic arcades seated in fan–spine null-point magnetic topology happen on a wide range of size scales on the Sun.« less

Parallel Optimization of Polynomials for Large-scale Problems in Stability and Control

NASA Astrophysics Data System (ADS)

Kamyar, Reza

In this thesis, we focus on some of the NP-hard problems in control theory. Thanks to the converse Lyapunov theory, these problems can often be modeled as optimization over polynomials. To avoid the problem of intractability, we establish a trade off between accuracy and complexity. In particular, we develop a sequence of tractable optimization problems --- in the form of Linear Programs (LPs) and/or Semi-Definite Programs (SDPs) --- whose solutions converge to the exact solution of the NP-hard problem. However, the computational and memory complexity of these LPs and SDPs grow exponentially with the progress of the sequence - meaning that improving the accuracy of the solutions requires solving SDPs with tens of thousands of decision variables and constraints. Setting up and solving such problems is a significant challenge. The existing optimization algorithms and software are only designed to use desktop computers or small cluster computers --- machines which do not have sufficient memory for solving such large SDPs. Moreover, the speed-up of these algorithms does not scale beyond dozens of processors. This in fact is the reason we seek parallel algorithms for setting-up and solving large SDPs on large cluster- and/or super-computers. We propose parallel algorithms for stability analysis of two classes of systems: 1) Linear systems with a large number of uncertain parameters; 2) Nonlinear systems defined by polynomial vector fields. First, we develop a distributed parallel algorithm which applies Polya's and/or Handelman's theorems to some variants of parameter-dependent Lyapunov inequalities with parameters defined over the standard simplex. The result is a sequence of SDPs which possess a block-diagonal structure. We then develop a parallel SDP solver which exploits this structure in order to map the computation, memory and communication to a distributed parallel environment. Numerical tests on a supercomputer demonstrate the ability of the algorithm to efficiently utilize hundreds and potentially thousands of processors, and analyze systems with 100+ dimensional state-space. Furthermore, we extend our algorithms to analyze robust stability over more complicated geometries such as hypercubes and arbitrary convex polytopes. Our algorithms can be readily extended to address a wide variety of problems in control such as Hinfinity synthesis for systems with parametric uncertainty and computing control Lyapunov functions.

A method for data handling numerical results in parallel OpenFOAM simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Anton, Alin; Muntean, Sebastian

Parallel computational fluid dynamics simulations produce vast amount of numerical result data. This paper introduces a method for reducing the size of the data by replaying the interprocessor traffic. The results are recovered only in certain regions of interest configured by the user. A known test case is used for several mesh partitioning scenarios using the OpenFOAM toolkit{sup ®}[1]. The space savings obtained with classic algorithms remain constant for more than 60 Gb of floating point data. Our method is most efficient on large simulation meshes and is much better suited for compressing large scale simulation results than the regular algorithms.

Processing large remote sensing image data sets on Beowulf clusters

USGS Publications Warehouse

Steinwand, Daniel R.; Maddox, Brian; Beckmann, Tim; Schmidt, Gail

2003-01-01

High-performance computing is often concerned with the speed at which floating- point calculations can be performed. The architectures of many parallel computers and/or their network topologies are based on these investigations. Often, benchmarks resulting from these investigations are compiled with little regard to how a large dataset would move about in these systems. This part of the Beowulf study addresses that concern by looking at specific applications software and system-level modifications. Applications include an implementation of a smoothing filter for time-series data, a parallel implementation of the decision tree algorithm used in the Landcover Characterization project, a parallel Kriging algorithm used to fit point data collected in the field on invasive species to a regular grid, and modifications to the Beowulf project's resampling algorithm to handle larger, higher resolution datasets at a national scale. Systems-level investigations include a feasibility study on Flat Neighborhood Networks and modifications of that concept with Parallel File Systems.

Integrated Joule switches for the control of current dynamics in parallel superconducting strips

NASA Astrophysics Data System (ADS)

Casaburi, A.; Heath, R. M.; Cristiano, R.; Ejrnaes, M.; Zen, N.; Ohkubo, M.; Hadfield, R. H.

2018-06-01

Understanding and harnessing the physics of the dynamic current distribution in parallel superconducting strips holds the key to creating next generation sensors for single molecule and single photon detection. Non-uniformity in the current distribution in parallel superconducting strips leads to low detection efficiency and unstable operation, preventing the scale up to large area sensors. Recent studies indicate that non-uniform current distributions occurring in parallel strips can be understood and modeled in the framework of the generalized London model. Here we build on this important physical insight, investigating an innovative design with integrated superconducting-to-resistive Joule switches to break the superconducting loops between the strips and thus control the current dynamics. Employing precision low temperature nano-optical techniques, we map the uniformity of the current distribution before- and after the resistive strip switching event, confirming the effectiveness of our design. These results provide important insights for the development of next generation large area superconducting strip-based sensors.

Optimizing a realistic large-scale frequency assignment problem using a new parallel evolutionary approach

NASA Astrophysics Data System (ADS)

Chaves-González, José M.; Vega-Rodríguez, Miguel A.; Gómez-Pulido, Juan A.; Sánchez-Pérez, Juan M.

2011-08-01

This article analyses the use of a novel parallel evolutionary strategy to solve complex optimization problems. The work developed here has been focused on a relevant real-world problem from the telecommunication domain to verify the effectiveness of the approach. The problem, known as frequency assignment problem (FAP), basically consists of assigning a very small number of frequencies to a very large set of transceivers used in a cellular phone network. Real data FAP instances are very difficult to solve due to the NP-hard nature of the problem, therefore using an efficient parallel approach which makes the most of different evolutionary strategies can be considered as a good way to obtain high-quality solutions in short periods of time. Specifically, a parallel hyper-heuristic based on several meta-heuristics has been developed. After a complete experimental evaluation, results prove that the proposed approach obtains very high-quality solutions for the FAP and beats any other result published.

Multi-source Geospatial Data Analysis with Google Earth Engine

NASA Astrophysics Data System (ADS)

Erickson, T.

2014-12-01

The Google Earth Engine platform is a cloud computing environment for data analysis that combines a public data catalog with a large-scale computational facility optimized for parallel processing of geospatial data. The data catalog is a multi-petabyte archive of georeferenced datasets that include images from Earth observing satellite and airborne sensors (examples: USGS Landsat, NASA MODIS, USDA NAIP), weather and climate datasets, and digital elevation models. Earth Engine supports both a just-in-time computation model that enables real-time preview and debugging during algorithm development for open-ended data exploration, and a batch computation mode for applying algorithms over large spatial and temporal extents. The platform automatically handles many traditionally-onerous data management tasks, such as data format conversion, reprojection, and resampling, which facilitates writing algorithms that combine data from multiple sensors and/or models. Although the primary use of Earth Engine, to date, has been the analysis of large Earth observing satellite datasets, the computational platform is generally applicable to a wide variety of use cases that require large-scale geospatial data analyses. This presentation will focus on how Earth Engine facilitates the analysis of geospatial data streams that originate from multiple separate sources (and often communities) and how it enables collaboration during algorithm development and data exploration. The talk will highlight current projects/analyses that are enabled by this functionality.https://earthengine.google.org

Linux OS Jitter Measurements at Large Node Counts using a BlueGene/L

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jones, Terry R; Tauferner, Mr. Andrew; Inglett, Mr. Todd

2010-01-01

We present experimental results for a coordinated scheduling implementation of the Linux operating system. Results were collected on an IBM Blue Gene/L machine at scales up to 16K nodes. Our results indicate coordinated scheduling was able to provide a dramatic improvement in scaling performance for two applications characterized as bulk synchronous parallel programs.

Magnetic anomaly map of the central Cayman Trough, northwestern Caribbean Sea

USGS Publications Warehouse

Dillon, William P.; Edgar, N. Terence; Parson, Lindsay M.; Scanlon, Kathryn M.; Driscoll, George R.; Jacobs, Colin L.

1993-01-01

This is the first large-scale published map of magnetic anomalies in the central Cayman Trough area. Two previously published very small scale maps based on much less data are a regional map (Gough and Heirtzler, 1969) and a map compiled from several tracklines running parallel to the axis of the Cayman Trough (MacDonald and Holcombe, 1978).

The earth's foreshock, bow shock, and magnetosheath

NASA Technical Reports Server (NTRS)

Onsager, T. G.; Thomsen, M. F.

1991-01-01

Studies directly pertaining to the earth's foreshock, bow shock, and magnetosheath are reviewed, and some comparisons are made with data on other planets. Topics considered in detail include the electron foreshock, the ion foreshock, the quasi-parallel shock, the quasi-perpendicular shock, and the magnetosheath. Information discussed spans a broad range of disciplines, from large-scale macroscopic plasma phenomena to small-scale microphysical interactions.

High performance cellular level agent-based simulation with FLAME for the GPU.

PubMed

Richmond, Paul; Walker, Dawn; Coakley, Simon; Romano, Daniela

2010-05-01

Driven by the availability of experimental data and ability to simulate a biological scale which is of immediate interest, the cellular scale is fast emerging as an ideal candidate for middle-out modelling. As with 'bottom-up' simulation approaches, cellular level simulations demand a high degree of computational power, which in large-scale simulations can only be achieved through parallel computing. The flexible large-scale agent modelling environment (FLAME) is a template driven framework for agent-based modelling (ABM) on parallel architectures ideally suited to the simulation of cellular systems. It is available for both high performance computing clusters (www.flame.ac.uk) and GPU hardware (www.flamegpu.com) and uses a formal specification technique that acts as a universal modelling format. This not only creates an abstraction from the underlying hardware architectures, but avoids the steep learning curve associated with programming them. In benchmarking tests and simulations of advanced cellular systems, FLAME GPU has reported massive improvement in performance over more traditional ABM frameworks. This allows the time spent in the development and testing stages of modelling to be drastically reduced and creates the possibility of real-time visualisation for simple visual face-validation.

LAMMPS strong scaling performance optimization on Blue Gene/Q

DOE Office of Scientific and Technical Information (OSTI.GOV)

Coffman, Paul; Jiang, Wei; Romero, Nichols A.

2014-11-12

LAMMPS "Large-scale Atomic/Molecular Massively Parallel Simulator" is an open-source molecular dynamics package from Sandia National Laboratories. Significant performance improvements in strong-scaling and time-to-solution for this application on IBM's Blue Gene/Q have been achieved through computational optimizations of the OpenMP versions of the short-range Lennard-Jones term of the CHARMM force field and the long-range Coulombic interaction implemented with the PPPM (particle-particle-particle mesh) algorithm, enhanced by runtime parameter settings controlling thread utilization. Additionally, MPI communication performance improvements were made to the PPPM calculation by re-engineering the parallel 3D FFT to use MPICH collectives instead of point-to-point. Performance testing was done using anmore » 8.4-million atom simulation scaling up to 16 racks on the Mira system at Argonne Leadership Computing Facility (ALCF). Speedups resulting from this effort were in some cases over 2x.« less

Multiscale asymmetric orthogonal wavelet kernel for linear programming support vector learning and nonlinear dynamic systems identification.

PubMed

Lu, Zhao; Sun, Jing; Butts, Kenneth

2014-05-01

Support vector regression for approximating nonlinear dynamic systems is more delicate than the approximation of indicator functions in support vector classification, particularly for systems that involve multitudes of time scales in their sampled data. The kernel used for support vector learning determines the class of functions from which a support vector machine can draw its solution, and the choice of kernel significantly influences the performance of a support vector machine. In this paper, to bridge the gap between wavelet multiresolution analysis and kernel learning, the closed-form orthogonal wavelet is exploited to construct new multiscale asymmetric orthogonal wavelet kernels for linear programming support vector learning. The closed-form multiscale orthogonal wavelet kernel provides a systematic framework to implement multiscale kernel learning via dyadic dilations and also enables us to represent complex nonlinear dynamics effectively. To demonstrate the superiority of the proposed multiscale wavelet kernel in identifying complex nonlinear dynamic systems, two case studies are presented that aim at building parallel models on benchmark datasets. The development of parallel models that address the long-term/mid-term prediction issue is more intricate and challenging than the identification of series-parallel models where only one-step ahead prediction is required. Simulation results illustrate the effectiveness of the proposed multiscale kernel learning.

Hi-Corrector: a fast, scalable and memory-efficient package for normalizing large-scale Hi-C data.

PubMed

Li, Wenyuan; Gong, Ke; Li, Qingjiao; Alber, Frank; Zhou, Xianghong Jasmine

2015-03-15

Genome-wide proximity ligation assays, e.g. Hi-C and its variant TCC, have recently become important tools to study spatial genome organization. Removing biases from chromatin contact matrices generated by such techniques is a critical preprocessing step of subsequent analyses. The continuing decline of sequencing costs has led to an ever-improving resolution of the Hi-C data, resulting in very large matrices of chromatin contacts. Such large-size matrices, however, pose a great challenge on the memory usage and speed of its normalization. Therefore, there is an urgent need for fast and memory-efficient methods for normalization of Hi-C data. We developed Hi-Corrector, an easy-to-use, open source implementation of the Hi-C data normalization algorithm. Its salient features are (i) scalability-the software is capable of normalizing Hi-C data of any size in reasonable times; (ii) memory efficiency-the sequential version can run on any single computer with very limited memory, no matter how little; (iii) fast speed-the parallel version can run very fast on multiple computing nodes with limited local memory. The sequential version is implemented in ANSI C and can be easily compiled on any system; the parallel version is implemented in ANSI C with the MPI library (a standardized and portable parallel environment designed for solving large-scale scientific problems). The package is freely available at http://zhoulab.usc.edu/Hi-Corrector/. © The Author 2014. Published by Oxford University Press.

Secure web-based invocation of large-scale plasma simulation codes

NASA Astrophysics Data System (ADS)

Dimitrov, D. A.; Busby, R.; Exby, J.; Bruhwiler, D. L.; Cary, J. R.

2004-12-01

We present our design and initial implementation of a web-based system for running, both in parallel and serial, Particle-In-Cell (PIC) codes for plasma simulations with automatic post processing and generation of visual diagnostics.

An Overview of Mesoscale Modeling Software for Energetic Materials Research

DTIC Science & Technology

2010-03-01

12 2.9 Large-scale Atomic/Molecular Massively Parallel Simulator ( LAMMPS ...13 Table 10. LAMMPS summary...extensive reviews, lectures and workshops are available on multiscale modeling of materials applications (76-78). • Multi-phase mixtures of

Scalable Triadic Analysis of Large-Scale Graphs: Multi-Core vs. Multi-Processor vs. Multi-Threaded Shared Memory Architectures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chin, George; Marquez, Andres; Choudhury, Sutanay

2012-09-01

Triadic analysis encompasses a useful set of graph mining methods that is centered on the concept of a triad, which is a subgraph of three nodes and the configuration of directed edges across the nodes. Such methods are often applied in the social sciences as well as many other diverse fields. Triadic methods commonly operate on a triad census that counts the number of triads of every possible edge configuration in a graph. Like other graph algorithms, triadic census algorithms do not scale well when graphs reach tens of millions to billions of nodes. To enable the triadic analysis ofmore » large-scale graphs, we developed and optimized a triad census algorithm to efficiently execute on shared memory architectures. We will retrace the development and evolution of a parallel triad census algorithm. Over the course of several versions, we continually adapted the code’s data structures and program logic to expose more opportunities to exploit parallelism on shared memory that would translate into improved computational performance. We will recall the critical steps and modifications that occurred during code development and optimization. Furthermore, we will compare the performances of triad census algorithm versions on three specific systems: Cray XMT, HP Superdome, and AMD multi-core NUMA machine. These three systems have shared memory architectures but with markedly different hardware capabilities to manage parallelism.« less

Fine grained event processing on HPCs with the ATLAS Yoda system

NASA Astrophysics Data System (ADS)

Calafiura, Paolo; De, Kaushik; Guan, Wen; Maeno, Tadashi; Nilsson, Paul; Oleynik, Danila; Panitkin, Sergey; Tsulaia, Vakhtang; Van Gemmeren, Peter; Wenaus, Torre

2015-12-01

High performance computing facilities present unique challenges and opportunities for HEP event processing. The massive scale of many HPC systems means that fractionally small utilization can yield large returns in processing throughput. Parallel applications which can dynamically and efficiently fill any scheduling opportunities the resource presents benefit both the facility (maximal utilization) and the (compute-limited) science. The ATLAS Yoda system provides this capability to HEP-like event processing applications by implementing event-level processing in an MPI-based master-client model that integrates seamlessly with the more broadly scoped ATLAS Event Service. Fine grained, event level work assignments are intelligently dispatched to parallel workers to sustain full utilization on all cores, with outputs streamed off to destination object stores in near real time with similarly fine granularity, such that processing can proceed until termination with full utilization. The system offers the efficiency and scheduling flexibility of preemption without requiring the application actually support or employ check-pointing. We will present the new Yoda system, its motivations, architecture, implementation, and applications in ATLAS data processing at several US HPC centers.

Parallel Multivariate Spatio-Temporal Clustering of Large Ecological Datasets on Hybrid Supercomputers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sreepathi, Sarat; Kumar, Jitendra; Mills, Richard T.

A proliferation of data from vast networks of remote sensing platforms (satellites, unmanned aircraft systems (UAS), airborne etc.), observational facilities (meteorological, eddy covariance etc.), state-of-the-art sensors, and simulation models offer unprecedented opportunities for scientific discovery. Unsupervised classification is a widely applied data mining approach to derive insights from such data. However, classification of very large data sets is a complex computational problem that requires efficient numerical algorithms and implementations on high performance computing (HPC) platforms. Additionally, increasing power, space, cooling and efficiency requirements has led to the deployment of hybrid supercomputing platforms with complex architectures and memory hierarchies like themore » Titan system at Oak Ridge National Laboratory. The advent of such accelerated computing architectures offers new challenges and opportunities for big data analytics in general and specifically, large scale cluster analysis in our case. Although there is an existing body of work on parallel cluster analysis, those approaches do not fully meet the needs imposed by the nature and size of our large data sets. Moreover, they had scaling limitations and were mostly limited to traditional distributed memory computing platforms. We present a parallel Multivariate Spatio-Temporal Clustering (MSTC) technique based on k-means cluster analysis that can target hybrid supercomputers like Titan. We developed a hybrid MPI, CUDA and OpenACC implementation that can utilize both CPU and GPU resources on computational nodes. We describe performance results on Titan that demonstrate the scalability and efficacy of our approach in processing large ecological data sets.« less

Formation of Electrostatic Potential Drops in the Auroral Zone

NASA Technical Reports Server (NTRS)

Schriver, D.; Ashour-Abdalla, M.; Richard, R. L.

2001-01-01

In order to examine the self-consistent formation of large-scale quasi-static parallel electric fields in the auroral zone on a micro/meso scale, a particle in cell simulation has been developed. The code resolves electron Debye length scales so that electron micro-processes are included and a variable grid scheme is used such that the overall length scale of the simulation is of the order of an Earth radii along the magnetic field. The simulation is electrostatic and includes the magnetic mirror force, as well as two types of plasmas, a cold dense ionospheric plasma and a warm tenuous magnetospheric plasma. In order to study the formation of parallel electric fields in the auroral zone, different magnetospheric ion and electron inflow boundary conditions are used to drive the system. It has been found that for conditions in the primary (upward) current region an upward directed quasi-static electric field can form across the system due to magnetic mirroring of the magnetospheric ions and electrons at different altitudes. For conditions in the return (downward) current region it is shown that a quasi-static parallel electric field in the opposite sense of that in the primary current region is formed, i.e., the parallel electric field is directed earthward. The conditions for how these different electric fields can be formed are discussed using satellite observations and numerical simulations.

MAGNETIC BRAIDING AND PARALLEL ELECTRIC FIELDS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wilmot-Smith, A. L.; Hornig, G.; Pontin, D. I.

2009-05-10

The braiding of the solar coronal magnetic field via photospheric motions-with subsequent relaxation and magnetic reconnection-is one of the most widely debated ideas of solar physics. We readdress the theory in light of developments in three-dimensional magnetic reconnection theory. It is known that the integrated parallel electric field along field lines is the key quantity determining the rate of reconnection, in contrast with the two-dimensional case where the electric field itself is the important quantity. We demonstrate that this difference becomes crucial for sufficiently complex magnetic field structures. A numerical method is used to relax a braided magnetic field towardmore » an ideal force-free equilibrium; the field is found to remain smooth throughout the relaxation, with only large-scale current structures. However, a highly filamentary integrated parallel current structure with extremely short length-scales is found in the field, with the associated gradients intensifying during the relaxation process. An analytical model is developed to show that, in a coronal situation, the length scales associated with the integrated parallel current structures will rapidly decrease with increasing complexity, or degree of braiding, of the magnetic field. Analysis shows the decrease in these length scales will, for any finite resistivity, eventually become inconsistent with the stability of the coronal field. Thus the inevitable consequence of the magnetic braiding process is a loss of equilibrium of the magnetic field, probably via magnetic reconnection events.« less

Large-Scale, Parallel, Multi-Sensor Data Fusion in the Cloud

NASA Astrophysics Data System (ADS)

Wilson, B. D.; Manipon, G.; Hua, H.

2012-12-01

NASA's Earth Observing System (EOS) is an ambitious facility for studying global climate change. The mandate now is to combine measurements from the instruments on the "A-Train" platforms (AIRS, AMSR-E, MODIS, MISR, MLS, and CloudSat) and other Earth probes to enable large-scale studies of climate change over periods of years to decades. However, moving from predominantly single-instrument studies to a multi-sensor, measurement-based model for long-duration analysis of important climate variables presents serious challenges for large-scale data mining and data fusion. For example, one might want to compare temperature and water vapor retrievals from one instrument (AIRS) to another instrument (MODIS), and to a model (ECMWF), stratify the comparisons using a classification of the "cloud scenes" from CloudSat, and repeat the entire analysis over years of AIRS data. To perform such an analysis, one must discover & access multiple datasets from remote sites, find the space/time "matchups" between instruments swaths and model grids, understand the quality flags and uncertainties for retrieved physical variables, assemble merged datasets, and compute fused products for further scientific and statistical analysis. To efficiently assemble such decade-scale datasets in a timely manner, we are utilizing Elastic Computing in the Cloud and parallel map/reduce-based algorithms. "SciReduce" is a Hadoop-like parallel analysis system, programmed in parallel python, that is designed from the ground up for Earth science. SciReduce executes inside VMWare images and scales to any number of nodes in the Cloud. Unlike Hadoop, in which simple tuples (keys & values) are passed between the map and reduce functions, SciReduce operates on bundles of named numeric arrays, which can be passed in memory or serialized to disk in netCDF4 or HDF5. Thus, SciReduce uses the native datatypes (geolocated grids, swaths, and points) that geo-scientists are familiar with. We are deploying within SciReduce a versatile set of python operators for data lookup, access, subsetting, co-registration, mining, fusion, and statistical analysis. All operators take in sets of geo-located arrays and generate more arrays. Large, multi-year satellite and model datasets are automatically "sharded" by time and space across a cluster of nodes so that years of data (millions of granules) can be compared or fused in a massively parallel way. Input variables (arrays) are pulled on-demand into the Cloud using OPeNDAP or webification URLs, thereby minimizing the size of the stored input and intermediate datasets. A typical map function might assemble and quality control AIRS Level-2 water vapor profiles for a year of data in parallel, then a reduce function would average the profiles in lat/lon bins (again, in parallel), and a final reduce would aggregate the climatology and write it to output files. We are using SciReduce to automate the production of multiple versions of a multi-year water vapor climatology (AIRS & MODIS), stratified by Cloudsat cloud classification, and compare it to models (ECMWF & MERRA reanalysis). We will present the architecture of SciReduce, describe the achieved "clock time" speedups in fusing huge datasets on our own nodes and in the Amazon Cloud, and discuss the Cloud cost tradeoffs for storage, compute, and data transfer.

Large-Scale, Parallel, Multi-Sensor Data Fusion in the Cloud

NASA Astrophysics Data System (ADS)

Wilson, B.; Manipon, G.; Hua, H.

2012-04-01

NASA's Earth Observing System (EOS) is an ambitious facility for studying global climate change. The mandate now is to combine measurements from the instruments on the "A-Train" platforms (AIRS, AMSR-E, MODIS, MISR, MLS, and CloudSat) and other Earth probes to enable large-scale studies of climate change over periods of years to decades. However, moving from predominantly single-instrument studies to a multi-sensor, measurement-based model for long-duration analysis of important climate variables presents serious challenges for large-scale data mining and data fusion. For example, one might want to compare temperature and water vapor retrievals from one instrument (AIRS) to another instrument (MODIS), and to a model (ECMWF), stratify the comparisons using a classification of the "cloud scenes" from CloudSat, and repeat the entire analysis over years of AIRS data. To perform such an analysis, one must discover & access multiple datasets from remote sites, find the space/time "matchups" between instruments swaths and model grids, understand the quality flags and uncertainties for retrieved physical variables, assemble merged datasets, and compute fused products for further scientific and statistical analysis. To efficiently assemble such decade-scale datasets in a timely manner, we are utilizing Elastic Computing in the Cloud and parallel map/reduce-based algorithms. "SciReduce" is a Hadoop-like parallel analysis system, programmed in parallel python, that is designed from the ground up for Earth science. SciReduce executes inside VMWare images and scales to any number of nodes in the Cloud. Unlike Hadoop, in which simple tuples (keys & values) are passed between the map and reduce functions, SciReduce operates on bundles of named numeric arrays, which can be passed in memory or serialized to disk in netCDF4 or HDF5. Thus, SciReduce uses the native datatypes (geolocated grids, swaths, and points) that geo-scientists are familiar with. We are deploying within SciReduce a versatile set of python operators for data lookup, access, subsetting, co-registration, mining, fusion, and statistical analysis. All operators take in sets of geo-arrays and generate more arrays. Large, multi-year satellite and model datasets are automatically "sharded" by time and space across a cluster of nodes so that years of data (millions of granules) can be compared or fused in a massively parallel way. Input variables (arrays) are pulled on-demand into the Cloud using OPeNDAP or webification URLs, thereby minimizing the size of the stored input and intermediate datasets. A typical map function might assemble and quality control AIRS Level-2 water vapor profiles for a year of data in parallel, then a reduce function would average the profiles in bins (again, in parallel), and a final reduce would aggregate the climatology and write it to output files. We are using SciReduce to automate the production of multiple versions of a multi-year water vapor climatology (AIRS & MODIS), stratified by Cloudsat cloud classification, and compare it to models (ECMWF & MERRA reanalysis). We will present the architecture of SciReduce, describe the achieved "clock time" speedups in fusing huge datasets on our own nodes and in the Amazon Cloud, and discuss the Cloud cost tradeoffs for storage, compute, and data transfer.

Optimization by nonhierarchical asynchronous decomposition

NASA Technical Reports Server (NTRS)

Shankar, Jayashree; Ribbens, Calvin J.; Haftka, Raphael T.; Watson, Layne T.

1992-01-01

Large scale optimization problems are tractable only if they are somehow decomposed. Hierarchical decompositions are inappropriate for some types of problems and do not parallelize well. Sobieszczanski-Sobieski has proposed a nonhierarchical decomposition strategy for nonlinear constrained optimization that is naturally parallel. Despite some successes on engineering problems, the algorithm as originally proposed fails on simple two dimensional quadratic programs. The algorithm is carefully analyzed for quadratic programs, and a number of modifications are suggested to improve its robustness.

Large-Scale Parallel Simulations of Turbulent Combustion using Combined Dimension Reduction and Tabulation of Chemistry

DTIC Science & Technology

2012-05-22

tabulation of the reduced space is performed using the In Situ Adaptive Tabulation ( ISAT ) algorithm. In addition, we use x2f mpi – a Fortran library...for parallel vector-valued function evaluation (used with ISAT in this context) – to efficiently redistribute the chemistry workload among the...Constrained-Equilibrium (RCCE) method, and tabulation of the reduced space is performed using the In Situ Adaptive Tabulation ( ISAT ) algorithm. In addition

Parallel Visualization Co-Processing of Overnight CFD Propulsion Applications

NASA Technical Reports Server (NTRS)

Edwards, David E.; Haimes, Robert

1999-01-01

An interactive visualization system pV3 is being developed for the investigation of advanced computational methodologies employing visualization and parallel processing for the extraction of information contained in large-scale transient engineering simulations. Visual techniques for extracting information from the data in terms of cutting planes, iso-surfaces, particle tracing and vector fields are included in this system. This paper discusses improvements to the pV3 system developed under NASA's Affordable High Performance Computing project.

Parallel computing works

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

An account of the Caltech Concurrent Computation Program (C{sup 3}P), a five year project that focused on answering the question: Can parallel computers be used to do large-scale scientific computations '' As the title indicates, the question is answered in the affirmative, by implementing numerous scientific applications on real parallel computers and doing computations that produced new scientific results. In the process of doing so, C{sup 3}P helped design and build several new computers, designed and implemented basic system software, developed algorithms for frequently used mathematical computations on massively parallel machines, devised performance models and measured the performance of manymore » computers, and created a high performance computing facility based exclusively on parallel computers. While the initial focus of C{sup 3}P was the hypercube architecture developed by C. Seitz, many of the methods developed and lessons learned have been applied successfully on other massively parallel architectures.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gamblin, T; de Supinski, B R; Schulz, M

Good load balance is crucial on very large parallel systems, but the most sophisticated algorithms introduce dynamic imbalances through adaptation in domain decomposition or use of adaptive solvers. To observe and diagnose imbalance, developers need system-wide, temporally-ordered measurements from full-scale runs. This potentially requires data collection from multiple code regions on all processors over the entire execution. Doing this instrumentation naively can, in combination with the application itself, exceed available I/O bandwidth and storage capacity, and can induce severe behavioral perturbations. We present and evaluate a novel technique for scalable, low-error load balance measurement. This uses a parallel wavelet transformmore » and other parallel encoding methods. We show that our technique collects and reconstructs system-wide measurements with low error. Compression time scales sublinearly with system size and data volume is several orders of magnitude smaller than the raw data. The overhead is low enough for online use in a production environment.« less

A Parallel, Multi-Scale Watershed-Hydrologic-Inundation Model with Adaptively Switching Mesh for Capturing Flooding and Lake Dynamics

NASA Astrophysics Data System (ADS)

Ji, X.; Shen, C.

2017-12-01

Flood inundation presents substantial societal hazards and also changes biogeochemistry for systems like the Amazon. It is often expensive to simulate high-resolution flood inundation and propagation in a long-term watershed-scale model. Due to the Courant-Friedrichs-Lewy (CFL) restriction, high resolution and large local flow velocity both demand prohibitively small time steps even for parallel codes. Here we develop a parallel surface-subsurface process-based model enhanced by multi-resolution meshes that are adaptively switched on or off. The high-resolution overland flow meshes are enabled only when the flood wave invades to floodplains. This model applies semi-implicit, semi-Lagrangian (SISL) scheme in solving dynamic wave equations, and with the assistant of the multi-mesh method, it also adaptively chooses the dynamic wave equation only in the area of deep inundation. Therefore, the model achieves a balance between accuracy and computational cost.

Neurite, a Finite Difference Large Scale Parallel Program for the Simulation of Electrical Signal Propagation in Neurites under Mechanical Loading

PubMed Central

García-Grajales, Julián A.; Rucabado, Gabriel; García-Dopico, Antonio; Peña, José-María; Jérusalem, Antoine

2015-01-01

With the growing body of research on traumatic brain injury and spinal cord injury, computational neuroscience has recently focused its modeling efforts on neuronal functional deficits following mechanical loading. However, in most of these efforts, cell damage is generally only characterized by purely mechanistic criteria, functions of quantities such as stress, strain or their corresponding rates. The modeling of functional deficits in neurites as a consequence of macroscopic mechanical insults has been rarely explored. In particular, a quantitative mechanically based model of electrophysiological impairment in neuronal cells, Neurite, has only very recently been proposed. In this paper, we present the implementation details of this model: a finite difference parallel program for simulating electrical signal propagation along neurites under mechanical loading. Following the application of a macroscopic strain at a given strain rate produced by a mechanical insult, Neurite is able to simulate the resulting neuronal electrical signal propagation, and thus the corresponding functional deficits. The simulation of the coupled mechanical and electrophysiological behaviors requires computational expensive calculations that increase in complexity as the network of the simulated cells grows. The solvers implemented in Neurite—explicit and implicit—were therefore parallelized using graphics processing units in order to reduce the burden of the simulation costs of large scale scenarios. Cable Theory and Hodgkin-Huxley models were implemented to account for the electrophysiological passive and active regions of a neurite, respectively, whereas a coupled mechanical model accounting for the neurite mechanical behavior within its surrounding medium was adopted as a link between electrophysiology and mechanics. This paper provides the details of the parallel implementation of Neurite, along with three different application examples: a long myelinated axon, a segmented dendritic tree, and a damaged axon. The capabilities of the program to deal with large scale scenarios, segmented neuronal structures, and functional deficits under mechanical loading are specifically highlighted. PMID:25680098

Final Scientific Report: A Scalable Development Environment for Peta-Scale Computing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Karbach, Carsten; Frings, Wolfgang

2013-02-22

This document is the final scientific report of the project DE-SC000120 (A scalable Development Environment for Peta-Scale Computing). The objective of this project is the extension of the Parallel Tools Platform (PTP) for applying it to peta-scale systems. PTP is an integrated development environment for parallel applications. It comprises code analysis, performance tuning, parallel debugging and system monitoring. The contribution of the Juelich Supercomputing Centre (JSC) aims to provide a scalable solution for system monitoring of supercomputers. This includes the development of a new communication protocol for exchanging status data between the target remote system and the client running PTP.more » The communication has to work for high latency. PTP needs to be implemented robustly and should hide the complexity of the supercomputer's architecture in order to provide a transparent access to various remote systems via a uniform user interface. This simplifies the porting of applications to different systems, because PTP functions as abstraction layer between parallel application developer and compute resources. The common requirement for all PTP components is that they have to interact with the remote supercomputer. E.g. applications are built remotely and performance tools are attached to job submissions and their output data resides on the remote system. Status data has to be collected by evaluating outputs of the remote job scheduler and the parallel debugger needs to control an application executed on the supercomputer. The challenge is to provide this functionality for peta-scale systems in real-time. The client server architecture of the established monitoring application LLview, developed by the JSC, can be applied to PTP's system monitoring. LLview provides a well-arranged overview of the supercomputer's current status. A set of statistics, a list of running and queued jobs as well as a node display mapping running jobs to their compute resources form the user display of LLview. These monitoring features have to be integrated into the development environment. Besides showing the current status PTP's monitoring also needs to allow for submitting and canceling user jobs. Monitoring peta-scale systems especially deals with presenting the large amount of status data in a useful manner. Users require to select arbitrary levels of detail. The monitoring views have to provide a quick overview of the system state, but also need to allow for zooming into specific parts of the system, into which the user is interested in. At present, the major batch systems running on supercomputers are PBS, TORQUE, ALPS and LoadLeveler, which have to be supported by both the monitoring and the job controlling component. Finally, PTP needs to be designed as generic as possible, so that it can be extended for future batch systems.« less

Fine-scale characteristics of interplanetary sector

NASA Technical Reports Server (NTRS)

Behannon, K. W.; Neubauer, F. M.; Barnstoff, H.

1980-01-01

The structure of the interplanetary sector boundaries observed by Helios 1 within sector transition regions was studied. Such regions consist of intermediate (nonspiral) average field orientations in some cases, as well as a number of large angle directional discontinuities (DD's) on the fine scale (time scales 1 hour). Such DD's are found to be more similar to tangential than rotational discontinuities, to be oriented on average more nearly perpendicular than parallel to the ecliptic plane to be accompanied usually by a large dip ( 80%) in B and, with a most probable thickness of 3 x 10 to the 4th power km, significantly thicker previously studied. It is hypothesized that the observed structures represent multiple traversals of the global heliospheric current sheet due to local fluctuations in the position of the sheet. There is evidence that such fluctuations are sometimes produced by wavelike motions or surface corrugations of scale length 0.05 - 0.1 AU superimposed on the large scale structure.

Parallel Optimization of 3D Cardiac Electrophysiological Model Using GPU

PubMed Central

Xia, Yong; Zhang, Henggui

2015-01-01

Large-scale 3D virtual heart model simulations are highly demanding in computational resources. This imposes a big challenge to the traditional computation resources based on CPU environment, which already cannot meet the requirement of the whole computation demands or are not easily available due to expensive costs. GPU as a parallel computing environment therefore provides an alternative to solve the large-scale computational problems of whole heart modeling. In this study, using a 3D sheep atrial model as a test bed, we developed a GPU-based simulation algorithm to simulate the conduction of electrical excitation waves in the 3D atria. In the GPU algorithm, a multicellular tissue model was split into two components: one is the single cell model (ordinary differential equation) and the other is the diffusion term of the monodomain model (partial differential equation). Such a decoupling enabled realization of the GPU parallel algorithm. Furthermore, several optimization strategies were proposed based on the features of the virtual heart model, which enabled a 200-fold speedup as compared to a CPU implementation. In conclusion, an optimized GPU algorithm has been developed that provides an economic and powerful platform for 3D whole heart simulations. PMID:26581957

Parallel Optimization of 3D Cardiac Electrophysiological Model Using GPU.

PubMed

Xia, Yong; Wang, Kuanquan; Zhang, Henggui

2015-01-01

Large-scale 3D virtual heart model simulations are highly demanding in computational resources. This imposes a big challenge to the traditional computation resources based on CPU environment, which already cannot meet the requirement of the whole computation demands or are not easily available due to expensive costs. GPU as a parallel computing environment therefore provides an alternative to solve the large-scale computational problems of whole heart modeling. In this study, using a 3D sheep atrial model as a test bed, we developed a GPU-based simulation algorithm to simulate the conduction of electrical excitation waves in the 3D atria. In the GPU algorithm, a multicellular tissue model was split into two components: one is the single cell model (ordinary differential equation) and the other is the diffusion term of the monodomain model (partial differential equation). Such a decoupling enabled realization of the GPU parallel algorithm. Furthermore, several optimization strategies were proposed based on the features of the virtual heart model, which enabled a 200-fold speedup as compared to a CPU implementation. In conclusion, an optimized GPU algorithm has been developed that provides an economic and powerful platform for 3D whole heart simulations.

PEP Support: Laboratory Scale Leaching and Permeate Stability Tests

DOE Office of Scientific and Technical Information (OSTI.GOV)

Russell, Renee L.; Peterson, Reid A.; Rinehart, Donald E.

2010-05-21

This report documents results from a variety of activities requested by the Hanford Tank Waste Treatment and Immobilization Plant (WTP). The activities related to caustic leaching, oxidative leaching, permeate precipitation behavior of waste as well as chromium (Cr) leaching are: • Model Input Boehmite Leaching Tests • Pretreatment Engineering Platform (PEP) Support Leaching Tests • PEP Parallel Leaching Tests • Precipitation Study Results • Cr Caustic and Oxidative Leaching Tests. Leaching test activities using the PEP simulant provided input to a boehmite dissolution model and determined the effect of temperature on mass loss during caustic leaching, the reaction rate constantmore » for the boehmite dissolution, and the effect of aeration in enhancing the chromium dissolution during caustic leaching. Other tests were performed in parallel with the PEP tests to support the development of scaling factors for caustic and oxidative leaching. Another study determined if precipitate formed in the wash solution after the caustic leach in the PEP. Finally, the leaching characteristics of different chromium compounds under different conditions were examined to determine the best one to use in further testing.« less

Dynamic load balancing of applications

DOEpatents

Wheat, S.R.

1997-05-13

An application-level method for dynamically maintaining global load balance on a parallel computer, particularly on massively parallel MIMD computers is disclosed. Global load balancing is achieved by overlapping neighborhoods of processors, where each neighborhood performs local load balancing. The method supports a large class of finite element and finite difference based applications and provides an automatic element management system to which applications are easily integrated. 13 figs.

Neuromorphic Hardware Architecture Using the Neural Engineering Framework for Pattern Recognition.

PubMed

Wang, Runchun; Thakur, Chetan Singh; Cohen, Gregory; Hamilton, Tara Julia; Tapson, Jonathan; van Schaik, Andre

2017-06-01

We present a hardware architecture that uses the neural engineering framework (NEF) to implement large-scale neural networks on field programmable gate arrays (FPGAs) for performing massively parallel real-time pattern recognition. NEF is a framework that is capable of synthesising large-scale cognitive systems from subnetworks and we have previously presented an FPGA implementation of the NEF that successfully performs nonlinear mathematical computations. That work was developed based on a compact digital neural core, which consists of 64 neurons that are instantiated by a single physical neuron using a time-multiplexing approach. We have now scaled this approach up to build a pattern recognition system by combining identical neural cores together. As a proof of concept, we have developed a handwritten digit recognition system using the MNIST database and achieved a recognition rate of 96.55%. The system is implemented on a state-of-the-art FPGA and can process 5.12 million digits per second. The architecture and hardware optimisations presented offer high-speed and resource-efficient means for performing high-speed, neuromorphic, and massively parallel pattern recognition and classification tasks.

Parallel STEPS: Large Scale Stochastic Spatial Reaction-Diffusion Simulation with High Performance Computers

PubMed Central

Chen, Weiliang; De Schutter, Erik

2017-01-01

Stochastic, spatial reaction-diffusion simulations have been widely used in systems biology and computational neuroscience. However, the increasing scale and complexity of models and morphologies have exceeded the capacity of any serial implementation. This led to the development of parallel solutions that benefit from the boost in performance of modern supercomputers. In this paper, we describe an MPI-based, parallel operator-splitting implementation for stochastic spatial reaction-diffusion simulations with irregular tetrahedral meshes. The performance of our implementation is first examined and analyzed with simulations of a simple model. We then demonstrate its application to real-world research by simulating the reaction-diffusion components of a published calcium burst model in both Purkinje neuron sub-branch and full dendrite morphologies. Simulation results indicate that our implementation is capable of achieving super-linear speedup for balanced loading simulations with reasonable molecule density and mesh quality. In the best scenario, a parallel simulation with 2,000 processes runs more than 3,600 times faster than its serial SSA counterpart, and achieves more than 20-fold speedup relative to parallel simulation with 100 processes. In a more realistic scenario with dynamic calcium influx and data recording, the parallel simulation with 1,000 processes and no load balancing is still 500 times faster than the conventional serial SSA simulation. PMID:28239346

Parallel STEPS: Large Scale Stochastic Spatial Reaction-Diffusion Simulation with High Performance Computers.

PubMed

Chen, Weiliang; De Schutter, Erik

2017-01-01

Stochastic, spatial reaction-diffusion simulations have been widely used in systems biology and computational neuroscience. However, the increasing scale and complexity of models and morphologies have exceeded the capacity of any serial implementation. This led to the development of parallel solutions that benefit from the boost in performance of modern supercomputers. In this paper, we describe an MPI-based, parallel operator-splitting implementation for stochastic spatial reaction-diffusion simulations with irregular tetrahedral meshes. The performance of our implementation is first examined and analyzed with simulations of a simple model. We then demonstrate its application to real-world research by simulating the reaction-diffusion components of a published calcium burst model in both Purkinje neuron sub-branch and full dendrite morphologies. Simulation results indicate that our implementation is capable of achieving super-linear speedup for balanced loading simulations with reasonable molecule density and mesh quality. In the best scenario, a parallel simulation with 2,000 processes runs more than 3,600 times faster than its serial SSA counterpart, and achieves more than 20-fold speedup relative to parallel simulation with 100 processes. In a more realistic scenario with dynamic calcium influx and data recording, the parallel simulation with 1,000 processes and no load balancing is still 500 times faster than the conventional serial SSA simulation.

Efficient partitioning and assignment on programs for multiprocessor execution

NASA Technical Reports Server (NTRS)

Standley, Hilda M.

1993-01-01

The general problem studied is that of segmenting or partitioning programs for distribution across a multiprocessor system. Efficient partitioning and the assignment of program elements are of great importance since the time consumed in this overhead activity may easily dominate the computation, effectively eliminating any gains made by the use of the parallelism. In this study, the partitioning of sequentially structured programs (written in FORTRAN) is evaluated. Heuristics, developed for similar applications are examined. Finally, a model for queueing networks with finite queues is developed which may be used to analyze multiprocessor system architectures with a shared memory approach to the problem of partitioning. The properties of sequentially written programs form obstacles to large scale (at the procedure or subroutine level) parallelization. Data dependencies of even the minutest nature, reflecting the sequential development of the program, severely limit parallelism. The design of heuristic algorithms is tied to the experience gained in the parallel splitting. Parallelism obtained through the physical separation of data has seen some success, especially at the data element level. Data parallelism on a grander scale requires models that accurately reflect the effects of blocking caused by finite queues. A model for the approximation of the performance of finite queueing networks is developed. This model makes use of the decomposition approach combined with the efficiency of product form solutions.

Tigres Workflow Library: Supporting Scientific Pipelines on HPC Systems

DOE PAGES

Hendrix, Valerie; Fox, James; Ghoshal, Devarshi; ...

2016-07-21

The growth in scientific data volumes has resulted in the need for new tools that enable users to operate on and analyze data on large-scale resources. In the last decade, a number of scientific workflow tools have emerged. These tools often target distributed environments, and often need expert help to compose and execute the workflows. Data-intensive workflows are often ad-hoc, they involve an iterative development process that includes users composing and testing their workflows on desktops, and scaling up to larger systems. In this paper, we present the design and implementation of Tigres, a workflow library that supports the iterativemore » workflow development cycle of data-intensive workflows. Tigres provides an application programming interface to a set of programming templates i.e., sequence, parallel, split, merge, that can be used to compose and execute computational and data pipelines. We discuss the results of our evaluation of scientific and synthetic workflows showing Tigres performs with minimal template overheads (mean of 13 seconds over all experiments). We also discuss various factors (e.g., I/O performance, execution mechanisms) that affect the performance of scientific workflows on HPC systems.« less

Tigres Workflow Library: Supporting Scientific Pipelines on HPC Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hendrix, Valerie; Fox, James; Ghoshal, Devarshi

The growth in scientific data volumes has resulted in the need for new tools that enable users to operate on and analyze data on large-scale resources. In the last decade, a number of scientific workflow tools have emerged. These tools often target distributed environments, and often need expert help to compose and execute the workflows. Data-intensive workflows are often ad-hoc, they involve an iterative development process that includes users composing and testing their workflows on desktops, and scaling up to larger systems. In this paper, we present the design and implementation of Tigres, a workflow library that supports the iterativemore » workflow development cycle of data-intensive workflows. Tigres provides an application programming interface to a set of programming templates i.e., sequence, parallel, split, merge, that can be used to compose and execute computational and data pipelines. We discuss the results of our evaluation of scientific and synthetic workflows showing Tigres performs with minimal template overheads (mean of 13 seconds over all experiments). We also discuss various factors (e.g., I/O performance, execution mechanisms) that affect the performance of scientific workflows on HPC systems.« less

Imprint of non-linear effects on HI intensity mapping on large scales

DOE Office of Scientific and Technical Information (OSTI.GOV)

Umeh, Obinna, E-mail: umeobinna@gmail.com

Intensity mapping of the HI brightness temperature provides a unique way of tracing large-scale structures of the Universe up to the largest possible scales. This is achieved by using a low angular resolution radio telescopes to detect emission line from cosmic neutral Hydrogen in the post-reionization Universe. We use general relativistic perturbation theory techniques to derive for the first time the full expression for the HI brightness temperature up to third order in perturbation theory without making any plane-parallel approximation. We use this result and the renormalization prescription for biased tracers to study the impact of nonlinear effects on themore » power spectrum of HI brightness temperature both in real and redshift space. We show how mode coupling at nonlinear order due to nonlinear bias parameters and redshift space distortion terms modulate the power spectrum on large scales. The large scale modulation may be understood to be due to the effective bias parameter and effective shot noise.« less

Imprint of non-linear effects on HI intensity mapping on large scales

NASA Astrophysics Data System (ADS)

Umeh, Obinna

2017-06-01

Intensity mapping of the HI brightness temperature provides a unique way of tracing large-scale structures of the Universe up to the largest possible scales. This is achieved by using a low angular resolution radio telescopes to detect emission line from cosmic neutral Hydrogen in the post-reionization Universe. We use general relativistic perturbation theory techniques to derive for the first time the full expression for the HI brightness temperature up to third order in perturbation theory without making any plane-parallel approximation. We use this result and the renormalization prescription for biased tracers to study the impact of nonlinear effects on the power spectrum of HI brightness temperature both in real and redshift space. We show how mode coupling at nonlinear order due to nonlinear bias parameters and redshift space distortion terms modulate the power spectrum on large scales. The large scale modulation may be understood to be due to the effective bias parameter and effective shot noise.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Chao; Pouransari, Hadi; Rajamanickam, Sivasankaran

We present a parallel hierarchical solver for general sparse linear systems on distributed-memory machines. For large-scale problems, this fully algebraic algorithm is faster and more memory-efficient than sparse direct solvers because it exploits the low-rank structure of fill-in blocks. Depending on the accuracy of low-rank approximations, the hierarchical solver can be used either as a direct solver or as a preconditioner. The parallel algorithm is based on data decomposition and requires only local communication for updating boundary data on every processor. Moreover, the computation-to-communication ratio of the parallel algorithm is approximately the volume-to-surface-area ratio of the subdomain owned by everymore » processor. We also provide various numerical results to demonstrate the versatility and scalability of the parallel algorithm.« less

78 FR 11632 - Record of Decision for Land Acquisition and Airspace Establishment To Support Large-Scale Marine...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-02-19

... Establishment To Support Large-Scale Marine Air Ground Task Force Live- Fire and Maneuver Training at the Marine...), announces its decision to establish a large-scale Marine Air Ground Task Force (MAGTF) training facility at... through the Federal Aviation Administration the establishment and modification of military Special Use...

Implementing a Parallel Image Edge Detection Algorithm Based on the Otsu-Canny Operator on the Hadoop Platform.

PubMed

Cao, Jianfang; Chen, Lichao; Wang, Min; Tian, Yun

2018-01-01

The Canny operator is widely used to detect edges in images. However, as the size of the image dataset increases, the edge detection performance of the Canny operator decreases and its runtime becomes excessive. To improve the runtime and edge detection performance of the Canny operator, in this paper, we propose a parallel design and implementation for an Otsu-optimized Canny operator using a MapReduce parallel programming model that runs on the Hadoop platform. The Otsu algorithm is used to optimize the Canny operator's dual threshold and improve the edge detection performance, while the MapReduce parallel programming model facilitates parallel processing for the Canny operator to solve the processing speed and communication cost problems that occur when the Canny edge detection algorithm is applied to big data. For the experiments, we constructed datasets of different scales from the Pascal VOC2012 image database. The proposed parallel Otsu-Canny edge detection algorithm performs better than other traditional edge detection algorithms. The parallel approach reduced the running time by approximately 67.2% on a Hadoop cluster architecture consisting of 5 nodes with a dataset of 60,000 images. Overall, our approach system speeds up the system by approximately 3.4 times when processing large-scale datasets, which demonstrates the obvious superiority of our method. The proposed algorithm in this study demonstrates both better edge detection performance and improved time performance.

Kinetic-MHD simulations of gyroresonance instability driven by CR pressure anisotropy

NASA Astrophysics Data System (ADS)

Lebiga, O.; Santos-Lima, R.; Yan, H.

2018-05-01

The transport of cosmic rays (CRs) is crucial for the understanding of almost all high-energy phenomena. Both pre-existing large-scale magnetohydrodynamic (MHD) turbulence and locally generated turbulence through plasma instabilities are important for the CR propagation in astrophysical media. The potential role of the resonant instability triggered by CR pressure anisotropy to regulate the parallel spatial diffusion of low-energy CRs (≲100 GeV) in the interstellar and intracluster medium of galaxies has been shown in previous theoretical works. This work aims to study the gyroresonance instability via direct numerical simulations, in order to access quantitatively the wave-particle scattering rates. For this, we employ a 1D PIC-MHD code to follow the growth and saturation of the gyroresonance instability. We extract from the simulations the pitch-angle diffusion coefficient Dμμ produced by the instability during the linear and saturation phases, and a very good agreement (within a factor of 3) is found with the values predicted by the quasi-linear theory (QLT). Our results support the applicability of the QLT for modelling the scattering of low-energy CRs by the gyroresonance instability in the complex interplay between this instability and the large-scale MHD turbulence.

Caltech water-ice dusty plasma: preliminary results

NASA Astrophysics Data System (ADS)

Bellan, Paul; Chai, Kilbyoung

2013-10-01

A water-ice dusty plasma laboratory experiment has begun operation at Caltech. As in Ref., a 1-5 watt parallel-plate 13.56 MHz rf discharge plasma has LN2-cooled electrodes that cool the neutral background gas to cryogenic temperatures. However, instead of creating water vapor by in-situ deuterium-oxygen bonding, here the neutral gas is argon and water vapor is added in a controlled fashion. Ice grains spontaneously form after a few seconds. Photography with a HeNe line filter of a sheet of HeNe laser light sheet illuminating a cross section of dust grains shows a large scale whorl pattern composed of concentric sub-whorls having wave-like spatially varying intensity. Each sub-whorl is composed of very evenly separated fine-scale stream-lines indicating that the ice grains move in self-organized lanes like automobiles on a multi-line highway. HeNe laser extinction together with an estimate of dust density from the intergrain spacing in photographs indicates a 5 micron nominal dust grain radius. HeNe laser diffraction patterns indicate the ice dust grains are large and ellipsoidal at low pressure (200 mT) but small and spheroidal at high pressure (>600 mT). Supported by USDOE.

Parallel electric fields detected via conjugate electron echoes during the Echo 7 sounding rocket flight

NASA Technical Reports Server (NTRS)

Nemzek, R. J.; Winckler, J. R.

1991-01-01

Electron detectors on the Echo 7 active sounding rocket experiment measured 'conjugate echoes' resulting from artificial electron beam injections. Analysis of the drift motion of the electrons after a complete bounce leads to measurements of the magnetospheric convection electric field mapped to ionospheric altitudes. The magnetospheric field was highly variable, changing by tens of mV/m on time scales of as little as hundreds of millisec. While the smallest-scale magnetospheric field irregularities were mapped out by ionospheric conductivity, larger-scale features were enhanced by up to 50 mV/m in the ionosphere. The mismatch between magnetospheric and ionspheric convection fields indicates a violation of the equipotential field line condition. The parallel fields occurred in regions roughly 10 km across and probably supported a total potential drop of 10-100 V.

Topology-dependent density optima for efficient simultaneous network exploration

NASA Astrophysics Data System (ADS)

Wilson, Daniel B.; Baker, Ruth E.; Woodhouse, Francis G.

2018-06-01

A random search process in a networked environment is governed by the time it takes to visit every node, termed the cover time. Often, a networked process does not proceed in isolation but competes with many instances of itself within the same environment. A key unanswered question is how to optimize this process: How many concurrent searchers can a topology support before the benefits of parallelism are outweighed by competition for space? Here, we introduce the searcher-averaged parallel cover time (APCT) to quantify these economies of scale. We show that the APCT of the networked symmetric exclusion process is optimized at a searcher density that is well predicted by the spectral gap. Furthermore, we find that nonequilibrium processes, realized through the addition of bias, can support significantly increased density optima. Our results suggest alternative hybrid strategies of serial and parallel search for efficient information gathering in social interaction and biological transport networks.

GENESIS: a hybrid-parallel and multi-scale molecular dynamics simulator with enhanced sampling algorithms for biomolecular and cellular simulations.

PubMed

Jung, Jaewoon; Mori, Takaharu; Kobayashi, Chigusa; Matsunaga, Yasuhiro; Yoda, Takao; Feig, Michael; Sugita, Yuji

2015-07-01

GENESIS (Generalized-Ensemble Simulation System) is a new software package for molecular dynamics (MD) simulations of macromolecules. It has two MD simulators, called ATDYN and SPDYN. ATDYN is parallelized based on an atomic decomposition algorithm for the simulations of all-atom force-field models as well as coarse-grained Go-like models. SPDYN is highly parallelized based on a domain decomposition scheme, allowing large-scale MD simulations on supercomputers. Hybrid schemes combining OpenMP and MPI are used in both simulators to target modern multicore computer architectures. Key advantages of GENESIS are (1) the highly parallel performance of SPDYN for very large biological systems consisting of more than one million atoms and (2) the availability of various REMD algorithms (T-REMD, REUS, multi-dimensional REMD for both all-atom and Go-like models under the NVT, NPT, NPAT, and NPγT ensembles). The former is achieved by a combination of the midpoint cell method and the efficient three-dimensional Fast Fourier Transform algorithm, where the domain decomposition space is shared in real-space and reciprocal-space calculations. Other features in SPDYN, such as avoiding concurrent memory access, reducing communication times, and usage of parallel input/output files, also contribute to the performance. We show the REMD simulation results of a mixed (POPC/DMPC) lipid bilayer as a real application using GENESIS. GENESIS is released as free software under the GPLv2 licence and can be easily modified for the development of new algorithms and molecular models. WIREs Comput Mol Sci 2015, 5:310-323. doi: 10.1002/wcms.1220.

Resolutions of the Coulomb operator: VIII. Parallel implementation using the modern programming language X10.

PubMed

Limpanuparb, Taweetham; Milthorpe, Josh; Rendell, Alistair P

2014-10-30

Use of the modern parallel programming language X10 for computing long-range Coulomb and exchange interactions is presented. By using X10, a partitioned global address space language with support for task parallelism and the explicit representation of data locality, the resolution of the Ewald operator can be parallelized in a straightforward manner including use of both intranode and internode parallelism. We evaluate four different schemes for dynamic load balancing of integral calculation using X10's work stealing runtime, and report performance results for long-range HF energy calculation of large molecule/high quality basis running on up to 1024 cores of a high performance cluster machine. Copyright © 2014 Wiley Periodicals, Inc.

Avoiding and tolerating latency in large-scale next-generation shared-memory multiprocessors

NASA Technical Reports Server (NTRS)

Probst, David K.

1993-01-01

A scalable solution to the memory-latency problem is necessary to prevent the large latencies of synchronization and memory operations inherent in large-scale shared-memory multiprocessors from reducing high performance. We distinguish latency avoidance and latency tolerance. Latency is avoided when data is brought to nearby locales for future reference. Latency is tolerated when references are overlapped with other computation. Latency-avoiding locales include: processor registers, data caches used temporally, and nearby memory modules. Tolerating communication latency requires parallelism, allowing the overlap of communication and computation. Latency-tolerating techniques include: vector pipelining, data caches used spatially, prefetching in various forms, and multithreading in various forms. Relaxing the consistency model permits increased use of avoidance and tolerance techniques. Each model is a mapping from the program text to sets of partial orders on program operations; it is a convention about which temporal precedences among program operations are necessary. Information about temporal locality and parallelism constrains the use of avoidance and tolerance techniques. Suitable architectural primitives and compiler technology are required to exploit the increased freedom to reorder and overlap operations in relaxed models.

Wakefield Computations for the CLIC PETS using the Parallel Finite Element Time-Domain Code T3P

DOE Office of Scientific and Technical Information (OSTI.GOV)

Candel, A; Kabel, A.; Lee, L.

In recent years, SLAC's Advanced Computations Department (ACD) has developed the high-performance parallel 3D electromagnetic time-domain code, T3P, for simulations of wakefields and transients in complex accelerator structures. T3P is based on advanced higher-order Finite Element methods on unstructured grids with quadratic surface approximation. Optimized for large-scale parallel processing on leadership supercomputing facilities, T3P allows simulations of realistic 3D structures with unprecedented accuracy, aiding the design of the next generation of accelerator facilities. Applications to the Compact Linear Collider (CLIC) Power Extraction and Transfer Structure (PETS) are presented.

Computations on Wings With Full-Span Oscillating Control Surfaces Using Navier-Stokes Equations

NASA Technical Reports Server (NTRS)

Guruswamy, Guru P.

2013-01-01

A dual-level parallel procedure is presented for computing large databases to support aerospace vehicle design. This procedure has been developed as a single Unix script within the Parallel Batch Submission environment utilizing MPIexec and runs MPI based analysis software. It has been developed to provide a process for aerospace designers to generate data for large numbers of cases with the highest possible fidelity and reasonable wall clock time. A single job submission environment has been created to avoid keeping track of multiple jobs and the associated system administration overhead. The process has been demonstrated for computing large databases for the design of typical aerospace configurations, a launch vehicle and a rotorcraft.

Parallelization and Visual Analysis of Multidimensional Fields: Application to Ozone Production, Destruction, and Transport in Three Dimensions

NASA Technical Reports Server (NTRS)

Schwan, Karsten; Alyea, Fred; Ribarsky, M. William; Trauner, Mary; Eisenhauer, Greg; Jean, Yves; Gu, Weiming; Wang, Ray; Waldrop, Jeffrey; Schroeder, Beth;

On mechanics and material length scales of failure in heterogeneous interfaces using a finite strain high performance solver

NASA Astrophysics Data System (ADS)

Mosby, Matthew; Matouš, Karel

2015-12-01

Three-dimensional simulations capable of resolving the large range of spatial scales, from the failure-zone thickness up to the size of the representative unit cell, in damage mechanics problems of particle reinforced adhesives are presented. We show that resolving this wide range of scales in complex three-dimensional heterogeneous morphologies is essential in order to apprehend fracture characteristics, such as strength, fracture toughness and shape of the softening profile. Moreover, we show that computations that resolve essential physical length scales capture the particle size-effect in fracture toughness, for example. In the vein of image-based computational materials science, we construct statistically optimal unit cells containing hundreds to thousands of particles. We show that these statistically representative unit cells are capable of capturing the first- and second-order probability functions of a given data-source with better accuracy than traditional inclusion packing techniques. In order to accomplish these large computations, we use a parallel multiscale cohesive formulation and extend it to finite strains including damage mechanics. The high-performance parallel computational framework is executed on up to 1024 processing cores. A mesh convergence and a representative unit cell study are performed. Quantifying the complex damage patterns in simulations consisting of tens of millions of computational cells and millions of highly nonlinear equations requires data-mining the parallel simulations, and we propose two damage metrics to quantify the damage patterns. A detailed study of volume fraction and filler size on the macroscopic traction-separation response of heterogeneous adhesives is presented.

HipMCL: a high-performance parallel implementation of the Markov clustering algorithm for large-scale networks

PubMed Central

Azad, Ariful; Ouzounis, Christos A; Kyrpides, Nikos C; Buluç, Aydin

2018-01-01

Abstract Biological networks capture structural or functional properties of relevant entities such as molecules, proteins or genes. Characteristic examples are gene expression networks or protein–protein interaction networks, which hold information about functional affinities or structural similarities. Such networks have been expanding in size due to increasing scale and abundance of biological data. While various clustering algorithms have been proposed to find highly connected regions, Markov Clustering (MCL) has been one of the most successful approaches to cluster sequence similarity or expression networks. Despite its popularity, MCL’s scalability to cluster large datasets still remains a bottleneck due to high running times and memory demands. Here, we present High-performance MCL (HipMCL), a parallel implementation of the original MCL algorithm that can run on distributed-memory computers. We show that HipMCL can efficiently utilize 2000 compute nodes and cluster a network of ∼70 million nodes with ∼68 billion edges in ∼2.4 h. By exploiting distributed-memory environments, HipMCL clusters large-scale networks several orders of magnitude faster than MCL and enables clustering of even bigger networks. HipMCL is based on MPI and OpenMP and is freely available under a modified BSD license. PMID:29315405

HipMCL: a high-performance parallel implementation of the Markov clustering algorithm for large-scale networks

DOE PAGES

Azad, Ariful; Pavlopoulos, Georgios A.; Ouzounis, Christos A.; ...

2018-01-05

Biological networks capture structural or functional properties of relevant entities such as molecules, proteins or genes. Characteristic examples are gene expression networks or protein–protein interaction networks, which hold information about functional affinities or structural similarities. Such networks have been expanding in size due to increasing scale and abundance of biological data. While various clustering algorithms have been proposed to find highly connected regions, Markov Clustering (MCL) has been one of the most successful approaches to cluster sequence similarity or expression networks. Despite its popularity, MCL’s scalability to cluster large datasets still remains a bottleneck due to high running times andmore » memory demands. In this paper, we present High-performance MCL (HipMCL), a parallel implementation of the original MCL algorithm that can run on distributed-memory computers. We show that HipMCL can efficiently utilize 2000 compute nodes and cluster a network of ~70 million nodes with ~68 billion edges in ~2.4 h. By exploiting distributed-memory environments, HipMCL clusters large-scale networks several orders of magnitude faster than MCL and enables clustering of even bigger networks. Finally, HipMCL is based on MPI and OpenMP and is freely available under a modified BSD license.« less

HipMCL: a high-performance parallel implementation of the Markov clustering algorithm for large-scale networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Azad, Ariful; Pavlopoulos, Georgios A.; Ouzounis, Christos A.

Biological networks capture structural or functional properties of relevant entities such as molecules, proteins or genes. Characteristic examples are gene expression networks or protein–protein interaction networks, which hold information about functional affinities or structural similarities. Such networks have been expanding in size due to increasing scale and abundance of biological data. While various clustering algorithms have been proposed to find highly connected regions, Markov Clustering (MCL) has been one of the most successful approaches to cluster sequence similarity or expression networks. Despite its popularity, MCL’s scalability to cluster large datasets still remains a bottleneck due to high running times andmore » memory demands. In this paper, we present High-performance MCL (HipMCL), a parallel implementation of the original MCL algorithm that can run on distributed-memory computers. We show that HipMCL can efficiently utilize 2000 compute nodes and cluster a network of ~70 million nodes with ~68 billion edges in ~2.4 h. By exploiting distributed-memory environments, HipMCL clusters large-scale networks several orders of magnitude faster than MCL and enables clustering of even bigger networks. Finally, HipMCL is based on MPI and OpenMP and is freely available under a modified BSD license.« less

P-Hint-Hunt: a deep parallelized whole genome DNA methylation detection tool.

PubMed

Peng, Shaoliang; Yang, Shunyun; Gao, Ming; Liao, Xiangke; Liu, Jie; Yang, Canqun; Wu, Chengkun; Yu, Wenqiang

2017-03-14

The increasing studies have been conducted using whole genome DNA methylation detection as one of the most important part of epigenetics research to find the significant relationships among DNA methylation and several typical diseases, such as cancers and diabetes. In many of those studies, mapping the bisulfite treated sequence to the whole genome has been the main method to study DNA cytosine methylation. However, today's relative tools almost suffer from inaccuracies and time-consuming problems. In our study, we designed a new DNA methylation prediction tool ("Hint-Hunt") to solve the problem. By having an optimal complex alignment computation and Smith-Waterman matrix dynamic programming, Hint-Hunt could analyze and predict the DNA methylation status. But when Hint-Hunt tried to predict DNA methylation status with large-scale dataset, there are still slow speed and low temporal-spatial efficiency problems. In order to solve the problems of Smith-Waterman dynamic programming and low temporal-spatial efficiency, we further design a deep parallelized whole genome DNA methylation detection tool ("P-Hint-Hunt") on Tianhe-2 (TH-2) supercomputer. To the best of our knowledge, P-Hint-Hunt is the first parallel DNA methylation detection tool with a high speed-up to process large-scale dataset, and could run both on CPU and Intel Xeon Phi coprocessors. Moreover, we deploy and evaluate Hint-Hunt and P-Hint-Hunt on TH-2 supercomputer in different scales. The experimental results illuminate our tools eliminate the deviation caused by bisulfite treatment in mapping procedure and the multi-level parallel program yields a 48 times speed-up with 64 threads. P-Hint-Hunt gain a deep acceleration on CPU and Intel Xeon Phi heterogeneous platform, which gives full play of the advantages of multi-cores (CPU) and many-cores (Phi).

Direct kinematics solution architectures for industrial robot manipulators: Bit-serial versus parallel

NASA Astrophysics Data System (ADS)

Lee, J.; Kim, K.

A Very Large Scale Integration (VLSI) architecture for robot direct kinematic computation suitable for industrial robot manipulators was investigated. The Denavit-Hartenberg transformations are reviewed to exploit a proper processing element, namely an augmented CORDIC. Specifically, two distinct implementations are elaborated on, such as the bit-serial and parallel. Performance of each scheme is analyzed with respect to the time to compute one location of the end-effector of a 6-links manipulator, and the number of transistors required.

A Linked-Cell Domain Decomposition Method for Molecular Dynamics Simulation on a Scalable Multiprocessor

DOE PAGES

Yang, L. H.; Brooks III, E. D.; Belak, J.

1992-01-01

A molecular dynamics algorithm for performing large-scale simulations using the Parallel C Preprocessor (PCP) programming paradigm on the BBN TC2000, a massively parallel computer, is discussed. The algorithm uses a linked-cell data structure to obtain the near neighbors of each atom as time evoles. Each processor is assigned to a geometric domain containing many subcells and the storage for that domain is private to the processor. Within this scheme, the interdomain (i.e., interprocessor) communication is minimized.

Towards the Teraflop CFD

NASA Technical Reports Server (NTRS)

Schreiber, Robert; Simon, Horst D.

1992-01-01

We are surveying current projects in the area of parallel supercomputers. The machines considered here will become commercially available in the 1990 - 1992 time frame. All are suitable for exploring the critical issues in applying parallel processors to large scale scientific computations, in particular CFD calculations. This chapter presents an overview of the surveyed machines, and a detailed analysis of the various architectural and technology approaches taken. Particular emphasis is placed on the feasibility of a Teraflops capability following the paths proposed by various developers.

Direct kinematics solution architectures for industrial robot manipulators: Bit-serial versus parallel

NASA Technical Reports Server (NTRS)

Lee, J.; Kim, K.

1991-01-01

A Very Large Scale Integration (VLSI) architecture for robot direct kinematic computation suitable for industrial robot manipulators was investigated. The Denavit-Hartenberg transformations are reviewed to exploit a proper processing element, namely an augmented CORDIC. Specifically, two distinct implementations are elaborated on, such as the bit-serial and parallel. Performance of each scheme is analyzed with respect to the time to compute one location of the end-effector of a 6-links manipulator, and the number of transistors required.

Parallel Finite Element Domain Decomposition for Structural/Acoustic Analysis

NASA Technical Reports Server (NTRS)

Nguyen, Duc T.; Tungkahotara, Siroj; Watson, Willie R.; Rajan, Subramaniam D.

2005-01-01

A domain decomposition (DD) formulation for solving sparse linear systems of equations resulting from finite element analysis is presented. The formulation incorporates mixed direct and iterative equation solving strategics and other novel algorithmic ideas that are optimized to take advantage of sparsity and exploit modern computer architecture, such as memory and parallel computing. The most time consuming part of the formulation is identified and the critical roles of direct sparse and iterative solvers within the framework of the formulation are discussed. Experiments on several computer platforms using several complex test matrices are conducted using software based on the formulation. Small-scale structural examples are used to validate thc steps in the formulation and large-scale (l,000,000+ unknowns) duct acoustic examples are used to evaluate the ORIGIN 2000 processors, and a duster of 6 PCs (running under the Windows environment). Statistics show that the formulation is efficient in both sequential and parallel computing environmental and that the formulation is significantly faster and consumes less memory than that based on one of the best available commercialized parallel sparse solvers.

Active Storage with Analytics Capabilities and I/O Runtime System for Petascale Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Choudhary, Alok

Computational scientists must understand results from experimental, observational and computational simulation generated data to gain insights and perform knowledge discovery. As systems approach the petascale range, problems that were unimaginable a few years ago are within reach. With the increasing volume and complexity of data produced by ultra-scale simulations and high-throughput experiments, understanding the science is largely hampered by the lack of comprehensive I/O, storage, acceleration of data manipulation, analysis, and mining tools. Scientists require techniques, tools and infrastructure to facilitate better understanding of their data, in particular the ability to effectively perform complex data analysis, statistical analysis and knowledgemore » discovery. The goal of this work is to enable more effective analysis of scientific datasets through the integration of enhancements in the I/O stack, from active storage support at the file system layer to MPI-IO and high-level I/O library layers. We propose to provide software components to accelerate data analytics, mining, I/O, and knowledge discovery for large-scale scientific applications, thereby increasing productivity of both scientists and the systems. Our approaches include 1) design the interfaces in high-level I/O libraries, such as parallel netCDF, for applications to activate data mining operations at the lower I/O layers; 2) Enhance MPI-IO runtime systems to incorporate the functionality developed as a part of the runtime system design; 3) Develop parallel data mining programs as part of runtime library for server-side file system in PVFS file system; and 4) Prototype an active storage cluster, which will utilize multicore CPUs, GPUs, and FPGAs to carry out the data mining workload.« less

LSD: Large Survey Database framework

NASA Astrophysics Data System (ADS)

Juric, Mario

2012-09-01

The Large Survey Database (LSD) is a Python framework and DBMS for distributed storage, cross-matching and querying of large survey catalogs (>10^9 rows, >1 TB). The primary driver behind its development is the analysis of Pan-STARRS PS1 data. It is specifically optimized for fast queries and parallel sweeps of positionally and temporally indexed datasets. It transparently scales to more than >10^2 nodes, and can be made to function in "shared nothing" architectures.

Testing New Programming Paradigms with NAS Parallel Benchmarks

NASA Technical Reports Server (NTRS)

Jin, H.; Frumkin, M.; Schultz, M.; Yan, J.

2000-01-01

Over the past decade, high performance computing has evolved rapidly, not only in hardware architectures but also with increasing complexity of real applications. Technologies have been developing to aim at scaling up to thousands of processors on both distributed and shared memory systems. Development of parallel programs on these computers is always a challenging task. Today, writing parallel programs with message passing (e.g. MPI) is the most popular way of achieving scalability and high performance. However, writing message passing programs is difficult and error prone. Recent years new effort has been made in defining new parallel programming paradigms. The best examples are: HPF (based on data parallelism) and OpenMP (based on shared memory parallelism). Both provide simple and clear extensions to sequential programs, thus greatly simplify the tedious tasks encountered in writing message passing programs. HPF is independent of memory hierarchy, however, due to the immaturity of compiler technology its performance is still questionable. Although use of parallel compiler directives is not new, OpenMP offers a portable solution in the shared-memory domain. Another important development involves the tremendous progress in the internet and its associated technology. Although still in its infancy, Java promisses portability in a heterogeneous environment and offers possibility to "compile once and run anywhere." In light of testing these new technologies, we implemented new parallel versions of the NAS Parallel Benchmarks (NPBs) with HPF and OpenMP directives, and extended the work with Java and Java-threads. The purpose of this study is to examine the effectiveness of alternative programming paradigms. NPBs consist of five kernels and three simulated applications that mimic the computation and data movement of large scale computational fluid dynamics (CFD) applications. We started with the serial version included in NPB2.3. Optimization of memory and cache usage was applied to several benchmarks, noticeably BT and SP, resulting in better sequential performance. In order to overcome the lack of an HPF performance model and guide the development of the HPF codes, we employed an empirical performance model for several primitives found in the benchmarks. We encountered a few limitations of HPF, such as lack of supporting the "REDISTRIBUTION" directive and no easy way to handle irregular computation. The parallelization with OpenMP directives was done at the outer-most loop level to achieve the largest granularity. The performance of six HPF and OpenMP benchmarks is compared with their MPI counterparts for the Class-A problem size in the figure in next page. These results were obtained on an SGI Origin2000 (195MHz) with MIPSpro-f77 compiler 7.2.1 for OpenMP and MPI codes and PGI pghpf-2.4.3 compiler with MPI interface for HPF programs.

HIV scale-up in Mozambique: Exceptionalism, normalisation and global health

PubMed Central

Høg, Erling

2014-01-01

The large-scale introduction of HIV and AIDS services in Mozambique from 2000 onwards occurred in the context of deep political commitment to sovereign nation-building and an important transition in the nation's health system. Simultaneously, the international community encountered a willing state partner that recognised the need to take action against the HIV epidemic. This article examines two critical policy shifts: sustained international funding and public health system integration (the move from parallel to integrated HIV services). The Mozambican government struggles to support its national health system against privatisation, NGO competition and internal brain drain. This is a sovereignty issue. However, the dominant discourse on self-determination shows a contradictory twist: it is part of the political rhetoric to keep the sovereignty discourse alive, while the real challenge is coordination, not partnerships. Nevertheless, we need more anthropological studies to understand the political implications of global health funding and governance. Other studies need to examine the consequences of public health system integration for the quality of access to health care. PMID:24499102

Experimental design, operation, and results of a 4 kW high temperature steam electrolysis experiment

DOE PAGES

Zhang, Xiaoyu; O'Brien, James E.; Tao, Greg; ...

2015-08-06

High temperature steam electrolysis (HTSE) is a promising technology for large-scale hydrogen production. However, research on HTSE performance above the kW level is limited. This paper presents the results of 4 kW HTSE long-term test completed in a multi-kW test facility recently developed at the Idaho National Laboratory (INL). The 4 kW HTSE unit included two solid oxide electrolysis stacks operating in parallel, each of which included 40 electrode-supported planar cells. A current density of 0.41 A/cm2 was used for the long-term operation, resulting in a hydrogen production rate about 25 slpm. A demonstration of 920 hours stable operation wasmore » achieved. The paper also includes detailed descriptions of the piping layout, steam generation and delivery system, test fixture, heat recuperation system, hot zone, instrumentation, and operating conditions. As a result, this successful demonstration of multi-kW scale HTSE unit will help to advance the technology toward near-term commercialization.« less

HIV scale-up in Mozambique: exceptionalism, normalisation and global health.

PubMed

Høg, Erling

2014-01-01

The large-scale introduction of HIV and AIDS services in Mozambique from 2000 onwards occurred in the context of deep political commitment to sovereign nation-building and an important transition in the nation's health system. Simultaneously, the international community encountered a willing state partner that recognised the need to take action against the HIV epidemic. This article examines two critical policy shifts: sustained international funding and public health system integration (the move from parallel to integrated HIV services). The Mozambican government struggles to support its national health system against privatisation, NGO competition and internal brain drain. This is a sovereignty issue. However, the dominant discourse on self-determination shows a contradictory twist: it is part of the political rhetoric to keep the sovereignty discourse alive, while the real challenge is coordination, not partnerships. Nevertheless, we need more anthropological studies to understand the political implications of global health funding and governance. Other studies need to examine the consequences of public health system integration for the quality of access to health care.

Large-scale Parallel Unstructured Mesh Computations for 3D High-lift Analysis

NASA Technical Reports Server (NTRS)

Mavriplis, Dimitri J.; Pirzadeh, S.

1999-01-01

A complete "geometry to drag-polar" analysis capability for the three-dimensional high-lift configurations is described. The approach is based on the use of unstructured meshes in order to enable rapid turnaround for complicated geometries that arise in high-lift configurations. Special attention is devoted to creating a capability for enabling analyses on highly resolved grids. Unstructured meshes of several million vertices are initially generated on a work-station, and subsequently refined on a supercomputer. The flow is solved on these refined meshes on large parallel computers using an unstructured agglomeration multigrid algorithm. Good prediction of lift and drag throughout the range of incidences is demonstrated on a transport take-off configuration using up to 24.7 million grid points. The feasibility of using this approach in a production environment on existing parallel machines is demonstrated, as well as the scalability of the solver on machines using up to 1450 processors.

Probabilistic structural mechanics research for parallel processing computers

NASA Technical Reports Server (NTRS)

Sues, Robert H.; Chen, Heh-Chyun; Twisdale, Lawrence A.; Martin, William R.

1991-01-01

Aerospace structures and spacecraft are a complex assemblage of structural components that are subjected to a variety of complex, cyclic, and transient loading conditions. Significant modeling uncertainties are present in these structures, in addition to the inherent randomness of material properties and loads. To properly account for these uncertainties in evaluating and assessing the reliability of these components and structures, probabilistic structural mechanics (PSM) procedures must be used. Much research has focused on basic theory development and the development of approximate analytic solution methods in random vibrations and structural reliability. Practical application of PSM methods was hampered by their computationally intense nature. Solution of PSM problems requires repeated analyses of structures that are often large, and exhibit nonlinear and/or dynamic response behavior. These methods are all inherently parallel and ideally suited to implementation on parallel processing computers. New hardware architectures and innovative control software and solution methodologies are needed to make solution of large scale PSM problems practical.

Massive parallelization of serial inference algorithms for a complex generalized linear model

PubMed Central

Suchard, Marc A.; Simpson, Shawn E.; Zorych, Ivan; Ryan, Patrick; Madigan, David

2014-01-01

Following a series of high-profile drug safety disasters in recent years, many countries are redoubling their efforts to ensure the safety of licensed medical products. Large-scale observational databases such as claims databases or electronic health record systems are attracting particular attention in this regard, but present significant methodological and computational concerns. In this paper we show how high-performance statistical computation, including graphics processing units, relatively inexpensive highly parallel computing devices, can enable complex methods in large databases. We focus on optimization and massive parallelization of cyclic coordinate descent approaches to fit a conditioned generalized linear model involving tens of millions of observations and thousands of predictors in a Bayesian context. We find orders-of-magnitude improvement in overall run-time. Coordinate descent approaches are ubiquitous in high-dimensional statistics and the algorithms we propose open up exciting new methodological possibilities with the potential to significantly improve drug safety. PMID:25328363

Are trait-scaling relationships invariant across contrasting elevations in the widely distributed treeline species Nothofagus pumilio?

PubMed

Fajardo, Alex

2016-05-01

The study of scaling examines the relative dimensions of diverse organismal traits. Understanding whether global scaling patterns are paralleled within species is key to identify causal factors of universal scaling. I examined whether the foliage-stem (Corner's rules), the leaf size-number, and the leaf mass-leaf area scaling relationships remained invariant and isometric with elevation in a wide-distributed treeline species in the southern Chilean Andes. Mean leaf area, leaf mass, leafing intensity, and twig cross-sectional area were determined for 1-2 twigs of 8-15 Nothofagus pumilio individuals across four elevations (including treeline elevation) and four locations (from central Chile at 36°S to Tierra del Fuego at 54°S). Mixed effects models were fitted to test whether the interaction term between traits and elevation was nonsignificant (invariant). The leaf-twig cross-sectional area and the leaf mass-leaf area scaling relationships were isometric (slope = 1) and remained invariant with elevation, whereas the leaf size-number (i.e., leafing intensity) scaling was allometric (slope ≠ -1) and showed no variation with elevation. Leaf area and leaf number were consistently negatively correlated across elevation. The scaling relationships examined in the current study parallel those seen across species. It is plausible that the explanation of intraspecific scaling relationships, as trait combinations favored by natural selection, is the same as those invoked to explain across species patterns. Thus, it is very likely that the global interspecific Corner's rules and other leaf-leaf scaling relationships emerge as the aggregate of largely parallel intraspecific patterns. © 2016 Botanical Society of America.

Long waves in parallel flow in Hele-Shaw cells

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zeybek, M.; Yortsos, Y.C.

1991-09-09

The evolution of fluid interfaces in parallel flow in Hele-Shaw cells is studied theoretically and experimentally in the limit of large capillary number. It is shown that such interfaces support wave motion, the amplitude of which for long waves is governed by a set of Korteweg--de Vries and Airy equations. Experiments conducted in a long Hele-Shaw cell validate the theory in the symmetric case.

Designing for Peta-Scale in the LSST Database

NASA Astrophysics Data System (ADS)

Kantor, J.; Axelrod, T.; Becla, J.; Cook, K.; Nikolaev, S.; Gray, J.; Plante, R.; Nieto-Santisteban, M.; Szalay, A.; Thakar, A.

2007-10-01

The Large Synoptic Survey Telescope (LSST), a proposed ground-based 8.4 m telescope with a 10 deg^2 field of view, will generate 15 TB of raw images every observing night. When calibration and processed data are added, the image archive, catalogs, and meta-data will grow 15 PB yr^{-1} on average. The LSST Data Management System (DMS) must capture, process, store, index, replicate, and provide open access to this data. Alerts must be triggered within 30 s of data acquisition. To do this in real-time at these data volumes will require advances in data management, database, and file system techniques. This paper describes the design of the LSST DMS and emphasizes features for peta-scale data. The LSST DMS will employ a combination of distributed database and file systems, with schema, partitioning, and indexing oriented for parallel operations. Image files are stored in a distributed file system with references to, and meta-data from, each file stored in the databases. The schema design supports pipeline processing, rapid ingest, and efficient query. Vertical partitioning reduces disk input/output requirements, horizontal partitioning allows parallel data access using arrays of servers and disks. Indexing is extensive, utilizing both conventional RAM-resident indexes and column-narrow, row-deep tag tables/covering indices that are extracted from tables that contain many more attributes. The DMS Data Access Framework is encapsulated in a middleware framework to provide a uniform service interface to all framework capabilities. This framework will provide the automated work-flow, replication, and data analysis capabilities necessary to make data processing and data quality analysis feasible at this scale.

Xyce Parallel Electronic Simulator Users' Guide Version 6.6.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Keiter, Eric R.; Aadithya, Karthik Venkatraman; Mei, Ting

This manual describes the use of the Xyce Parallel Electronic Simulator. Xyce has been de- signed as a SPICE-compatible, high-performance analog circuit simulator, and has been written to support the simulation needs of the Sandia National Laboratories electrical designers. This development has focused on improving capability over the current state-of-the-art in the following areas: Capability to solve extremely large circuit problems by supporting large-scale parallel com- puting platforms (up to thousands of processors). This includes support for most popular parallel and serial computers. A differential-algebraic-equation (DAE) formulation, which better isolates the device model package from solver algorithms. This allows onemore » to develop new types of analysis without requiring the implementation of analysis-specific device models. Device models that are specifically tailored to meet Sandia's needs, including some radiation- aware devices (for Sandia users only). Object-oriented code design and implementation using modern coding practices. Xyce is a parallel code in the most general sense of the phrase -- a message passing parallel implementation -- which allows it to run efficiently a wide range of computing platforms. These include serial, shared-memory and distributed-memory parallel platforms. Attention has been paid to the specific nature of circuit-simulation problems to ensure that optimal parallel efficiency is achieved as the number of processors grows. The information herein is subject to change without notice. Copyright c 2002-2016 Sandia Corporation. All rights reserved. Acknowledgements The BSIM Group at the University of California, Berkeley developed the BSIM3, BSIM4, BSIM6, BSIM-CMG and BSIM-SOI models. The BSIM3 is Copyright c 1999, Regents of the University of California. The BSIM4 is Copyright c 2006, Regents of the University of California. The BSIM6 is Copyright c 2015, Regents of the University of California. The BSIM-CMG is Copyright c 2012 and 2016, Regents of the University of California. The BSIM-SOI is Copyright c 1990, Regents of the University of California. All rights reserved. The Mextram model has been developed by NXP Semiconductors until 2007, Delft University of Technology from 2007 to 2014, and Auburn University since April 2015. Copyrights c of Mextram are with Delft University of Technology, NXP Semiconductors and Auburn University. The MIT VS Model Research Group developed the MIT Virtual Source (MVS) model. Copyright c 2013 Massachusetts Institute of Technology (MIT). The EKV3 MOSFET model was developed by the EKV Team of the Electronics Laboratory-TUC of the Technical University of Crete. Trademarks Xyce TM Electronic Simulator and Xyce TM are trademarks of Sandia Corporation. Orcad, Orcad Capture, PSpice and Probe are registered trademarks of Cadence Design Systems, Inc. Microsoft, Windows and Windows 7 are registered trademarks of Microsoft Corporation. Medici, DaVinci and Taurus are registered trademarks of Synopsys Corporation. Amtec and TecPlot are trademarks of Amtec Engineering, Inc. All other trademarks are property of their respective owners. Contacts World Wide Web http://xyce.sandia.gov https://info.sandia.gov/xyce (Sandia only) Email xyce@sandia.gov (outside Sandia) xyce-sandia@sandia.gov (Sandia only) Bug Reports (Sandia only) http://joseki-vm.sandia.gov/bugzilla http://morannon.sandia.gov/bugzilla« less

Investigation of the effect of resistivity on scrape off layer filaments using three-dimensional simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Easy, L., E-mail: le590@york.ac.uk; CCFE, Culham Science Centre, Abingdon OX14 3DB; Militello, F.

2016-01-15

The propagation of filaments in the Scrape Off Layer (SOL) of tokamaks largely determines the plasma profiles in the region. In a conduction limited SOL, parallel temperature gradients are expected, such that the resistance to parallel currents is greater at the target than further upstream. Since the perpendicular motion of an isolated filament is largely determined by balance of currents that flow through it, this may be expected to affect filament transport. 3D simulations have thus been used to study the influence of enhanced parallel resistivity on the dynamics of filaments. Filaments with the smallest perpendicular length scales, which weremore » inertially limited at low resistivity (meaning that polarization rather than parallel currents determines their radial velocities), were unaffected by resistivity. For larger filaments, faster velocities were produced at higher resistivities due to two mechanisms. First parallel currents were reduced and polarization currents were enhanced, meaning that the inertial regime extended to larger filaments, and second, a potential difference formed along the parallel direction so that higher potentials were produced in the region of the filament for the same amount of current to flow into the sheath. These results indicate that broader SOL profiles could be produced at higher resistivities.« less

GraphReduce: Processing Large-Scale Graphs on Accelerator-Based Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sengupta, Dipanjan; Song, Shuaiwen; Agarwal, Kapil

2015-11-15

Recent work on real-world graph analytics has sought to leverage the massive amount of parallelism offered by GPU devices, but challenges remain due to the inherent irregularity of graph algorithms and limitations in GPU-resident memory for storing large graphs. We present GraphReduce, a highly efficient and scalable GPU-based framework that operates on graphs that exceed the device’s internal memory capacity. GraphReduce adopts a combination of edge- and vertex-centric implementations of the Gather-Apply-Scatter programming model and operates on multiple asynchronous GPU streams to fully exploit the high degrees of parallelism in GPUs with efficient graph data movement between the host andmore » device.« less

Adapting the serial Alpgen parton-interaction generator to simulate LHC collisions on millions of parallel threads

NASA Astrophysics Data System (ADS)

Childers, J. T.; Uram, T. D.; LeCompte, T. J.; Papka, M. E.; Benjamin, D. P.

2017-01-01

As the LHC moves to higher energies and luminosity, the demand for computing resources increases accordingly and will soon outpace the growth of the Worldwide LHC Computing Grid. To meet this greater demand, event generation Monte Carlo was targeted for adaptation to run on Mira, the supercomputer at the Argonne Leadership Computing Facility. Alpgen is a Monte Carlo event generation application that is used by LHC experiments in the simulation of collisions that take place in the Large Hadron Collider. This paper details the process by which Alpgen was adapted from a single-processor serial-application to a large-scale parallel-application and the performance that was achieved.

Chebyshev polynomial filtered subspace iteration in the discontinuous Galerkin method for large-scale electronic structure calculations

DOE PAGES

Banerjee, Amartya S.; Lin, Lin; Hu, Wei; ...

2016-10-21

The Discontinuous Galerkin (DG) electronic structure method employs an adaptive local basis (ALB) set to solve the Kohn-Sham equations of density functional theory in a discontinuous Galerkin framework. The adaptive local basis is generated on-the-fly to capture the local material physics and can systematically attain chemical accuracy with only a few tens of degrees of freedom per atom. A central issue for large-scale calculations, however, is the computation of the electron density (and subsequently, ground state properties) from the discretized Hamiltonian in an efficient and scalable manner. We show in this work how Chebyshev polynomial filtered subspace iteration (CheFSI) canmore » be used to address this issue and push the envelope in large-scale materials simulations in a discontinuous Galerkin framework. We describe how the subspace filtering steps can be performed in an efficient and scalable manner using a two-dimensional parallelization scheme, thanks to the orthogonality of the DG basis set and block-sparse structure of the DG Hamiltonian matrix. The on-the-fly nature of the ALB functions requires additional care in carrying out the subspace iterations. We demonstrate the parallel scalability of the DG-CheFSI approach in calculations of large-scale twodimensional graphene sheets and bulk three-dimensional lithium-ion electrolyte systems. In conclusion, employing 55 296 computational cores, the time per self-consistent field iteration for a sample of the bulk 3D electrolyte containing 8586 atoms is 90 s, and the time for a graphene sheet containing 11 520 atoms is 75 s.« less

Visual Data-Analytics of Large-Scale Parallel Discrete-Event Simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ross, Caitlin; Carothers, Christopher D.; Mubarak, Misbah

Parallel discrete-event simulation (PDES) is an important tool in the codesign of extreme-scale systems because PDES provides a cost-effective way to evaluate designs of highperformance computing systems. Optimistic synchronization algorithms for PDES, such as Time Warp, allow events to be processed without global synchronization among the processing elements. A rollback mechanism is provided when events are processed out of timestamp order. Although optimistic synchronization protocols enable the scalability of large-scale PDES, the performance of the simulations must be tuned to reduce the number of rollbacks and provide an improved simulation runtime. To enable efficient large-scale optimistic simulations, one has tomore » gain insight into the factors that affect the rollback behavior and simulation performance. We developed a tool for ROSS model developers that gives them detailed metrics on the performance of their large-scale optimistic simulations at varying levels of simulation granularity. Model developers can use this information for parameter tuning of optimistic simulations in order to achieve better runtime and fewer rollbacks. In this work, we instrument the ROSS optimistic PDES framework to gather detailed statistics about the simulation engine. We have also developed an interactive visualization interface that uses the data collected by the ROSS instrumentation to understand the underlying behavior of the simulation engine. The interface connects real time to virtual time in the simulation and provides the ability to view simulation data at different granularities. We demonstrate the usefulness of our framework by performing a visual analysis of the dragonfly network topology model provided by the CODES simulation framework built on top of ROSS. The instrumentation needs to minimize overhead in order to accurately collect data about the simulation performance. To ensure that the instrumentation does not introduce unnecessary overhead, we perform a scaling study that compares instrumented ROSS simulations with their noninstrumented counterparts in order to determine the amount of perturbation when running at different simulation scales.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bennett, Janine Camille; Thompson, David; Pebay, Philippe Pierre

Statistical analysis is typically used to reduce the dimensionality of and infer meaning from data. A key challenge of any statistical analysis package aimed at large-scale, distributed data is to address the orthogonal issues of parallel scalability and numerical stability. Many statistical techniques, e.g., descriptive statistics or principal component analysis, are based on moments and co-moments and, using robust online update formulas, can be computed in an embarrassingly parallel manner, amenable to a map-reduce style implementation. In this paper we focus on contingency tables, through which numerous derived statistics such as joint and marginal probability, point-wise mutual information, information entropy,more » and {chi}{sup 2} independence statistics can be directly obtained. However, contingency tables can become large as data size increases, requiring a correspondingly large amount of communication between processors. This potential increase in communication prevents optimal parallel speedup and is the main difference with moment-based statistics (which we discussed in [1]) where the amount of inter-processor communication is independent of data size. Here we present the design trade-offs which we made to implement the computation of contingency tables in parallel. We also study the parallel speedup and scalability properties of our open source implementation. In particular, we observe optimal speed-up and scalability when the contingency statistics are used in their appropriate context, namely, when the data input is not quasi-diffuse.« less

Collisionless Isotropization of the Solar-wind Protons by Compressive Fluctuations and Plasma Instabilities

NASA Astrophysics Data System (ADS)

Verscharen, Daniel; Chandran, Benjamin D. G.; Klein, Kristopher G.; Quataert, Eliot

2016-11-01

Compressive fluctuations are a minor yet significant component of astrophysical plasma turbulence. In the solar wind, long-wavelength compressive slow-mode fluctuations lead to changes in {β }\\parallel {{p}}\\equiv 8π {n}{{p}}{k}{{B}}{T}\\parallel {{p}}/{B}2 and in {R}{{p}}\\equiv {T}\\perp {{p}}/{T}\\parallel {{p}}, where {T}\\perp {{p}} and {T}\\parallel {{p}} are the perpendicular and parallel temperatures of the protons, B is the magnetic field strength, and {n}{{p}} is the proton density. If the amplitude of the compressive fluctuations is large enough, {R}{{p}} crosses one or more instability thresholds for anisotropy-driven microinstabilities. The enhanced field fluctuations from these microinstabilities scatter the protons so as to reduce the anisotropy of the pressure tensor. We propose that this scattering drives the average value of {R}{{p}} away from the marginal stability boundary until the fluctuating value of {R}{{p}} stops crossing the boundary. We model this “fluctuating-anisotropy effect” using linear Vlasov-Maxwell theory to describe the large-scale compressive fluctuations. We argue that this effect can explain why, in the nearly collisionless solar wind, the average value of {R}{{p}} is close to unity.

Discovery of DNA repair inhibitors by combinatorial library profiling

PubMed Central

Moeller, Benjamin J.; Sidman, Richard L.; Pasqualini, Renata; Arap, Wadih

2011-01-01

Small molecule inhibitors of DNA repair are emerging as potent and selective anti-cancer therapies, but the sheer magnitude of the protein networks involved in DNA repair processes poses obstacles to discovery of effective candidate drugs. To address this challenge, we used a subtractive combinatorial selection approach to identify a panel of peptide ligands that bind DNA repair complexes. Supporting the concept that these ligands have therapeutic potential, we show that one selected peptide specifically binds and non-competitively inactivates DNA-PKcs, a protein kinase critical in double-strand DNA break repair. In doing so, this ligand sensitizes BRCA-deficient tumor cells to genotoxic therapy. Our findings establish a platform for large-scale parallel screening for ligand-directed DNA repair inhibitors, with immediate applicability to cancer therapy. PMID:21343400

Anticipating the emergence of infectious diseases

PubMed Central

Drake, John M.; Rohani, Pejman

2017-01-01

In spite of medical breakthroughs, the emergence of pathogens continues to pose threats to both human and animal populations. We present candidate approaches for anticipating disease emergence prior to large-scale outbreaks. Through use of ideas from the theories of dynamical systems and stochastic processes we develop approaches which are not specific to a particular disease system or model, but instead have general applicability. The indicators of disease emergence detailed in this paper can be classified into two parallel approaches: a set of early-warning signals based around the theory of critical slowing down and a likelihood-based approach. To test the reliability of these two approaches we contrast theoretical predictions with simulated data. We find good support for our methods across a range of different model structures and parameter values. PMID:28679666

Scaling NASA Applications to 1024 CPUs on Origin 3K

NASA Technical Reports Server (NTRS)

Taft, Jim

2002-01-01

The long and highly successful joint SGI-NASA research effort in ever larger SSI systems was to a large degree the result of the successful development of the MLP scalable parallel programming paradigm developed at ARC: 1) MLP scaling in real production codes justified ever larger systems at NAS; 2) MLP scaling on 256p Origin 2000 gave SGl impetus to productize 256p; 3) MLP scaling on 512 gave SGI courage to build 1024p O3K; and 4) History of MLP success resulted in IBM Star Cluster based MLP effort.

Hadoop-Based Distributed System for Online Prediction of Air Pollution Based on Support Vector Machine

NASA Astrophysics Data System (ADS)

Ghaemi, Z.; Farnaghi, M.; Alimohammadi, A.

2015-12-01

The critical impact of air pollution on human health and environment in one hand and the complexity of pollutant concentration behavior in the other hand lead the scientists to look for advance techniques for monitoring and predicting the urban air quality. Additionally, recent developments in data measurement techniques have led to collection of various types of data about air quality. Such data is extremely voluminous and to be useful it must be processed at high velocity. Due to the complexity of big data analysis especially for dynamic applications, online forecasting of pollutant concentration trends within a reasonable processing time is still an open problem. The purpose of this paper is to present an online forecasting approach based on Support Vector Machine (SVM) to predict the air quality one day in advance. In order to overcome the computational requirements for large-scale data analysis, distributed computing based on the Hadoop platform has been employed to leverage the processing power of multiple processing units. The MapReduce programming model is adopted for massive parallel processing in this study. Based on the online algorithm and Hadoop framework, an online forecasting system is designed to predict the air pollution of Tehran for the next 24 hours. The results have been assessed on the basis of Processing Time and Efficiency. Quite accurate predictions of air pollutant indicator levels within an acceptable processing time prove that the presented approach is very suitable to tackle large scale air pollution prediction problems.

Using Performance Tools to Support Experiments in HPC Resilience

DOE Office of Scientific and Technical Information (OSTI.GOV)

Naughton, III, Thomas J; Boehm, Swen; Engelmann, Christian

2014-01-01

The high performance computing (HPC) community is working to address fault tolerance and resilience concerns for current and future large scale computing platforms. This is driving enhancements in the programming environ- ments, specifically research on enhancing message passing libraries to support fault tolerant computing capabilities. The community has also recognized that tools for resilience experimentation are greatly lacking. However, we argue that there are several parallels between performance tools and resilience tools . As such, we believe the rich set of HPC performance-focused tools can be extended (repurposed) to benefit the resilience community. In this paper, we describe the initialmore » motivation to leverage standard HPC per- formance analysis techniques to aid in developing diagnostic tools to assist fault tolerance experiments for HPC applications. These diagnosis procedures help to provide context for the system when the errors (failures) occurred. We describe our initial work in leveraging an MPI performance trace tool to assist in provid- ing global context during fault injection experiments. Such tools will assist the HPC resilience community as they extend existing and new application codes to support fault tolerances.« less

On Multiple Hall-Like Electron Currents and Tripolar Guide Magnetic Field Perturbations During Kelvin-Helmholtz Waves

NASA Astrophysics Data System (ADS)

Sturner, Andrew P.; Eriksson, Stefan; Nakamura, Takuma; Gershman, Daniel J.; Plaschke, Ferdinand; Ergun, Robert E.; Wilder, Frederick D.; Giles, Barbara; Pollock, Craig; Paterson, William R.; Strangeway, Robert J.; Baumjohann, Wolfgang; Burch, James L.

2018-02-01

Two magnetopause current sheet crossings with tripolar guide magnetic field signatures were observed by multiple Magnetosphere Multiscale (MMS) spacecraft during Kelvin-Helmholtz wave activity. The two out-of-plane magnetic field depressions of the tripolar guide magnetic field are largely supported by the observed in-plane electron currents, which are reminiscent of two clockwise Hall current loop systems. A comparison with a three-dimensional kinetic simulation of Kelvin-Helmholtz waves and vortex-induced reconnection suggests that MMS likely encountered the two Hall magnetic field depressions on either side of a magnetic reconnection X-line. Moreover, MMS observed an out-of-plane current reversal and a corresponding in-plane magnetic field rotation at the center of one of the current sheets, suggesting the presence of two adjacent flux ropes. The region inside one of the ion-scale flux ropes was characterized by an observed decrease of the total magnetic field, a strong axial current, and significant enhancements of electron density and parallel electron temperature. The flux rope boundary was characterized by currents opposite this axial current, strong in-plane and converging electric fields, parallel electric fields, and weak electron-frame Joule dissipation. These return current region observations may reflect a need to support the axial current rather than representing local reconnection signatures in the absence of any exhausts.

Serial and parallel attentive visual searches: evidence from cumulative distribution functions of response times.

PubMed

Sung, Kyongje

2008-12-01

Participants searched a visual display for a target among distractors. Each of 3 experiments tested a condition proposed to require attention and for which certain models propose a serial search. Serial versus parallel processing was tested by examining effects on response time means and cumulative distribution functions. In 2 conditions, the results suggested parallel rather than serial processing, even though the tasks produced significant set-size effects. Serial processing was produced only in a condition with a difficult discrimination and a very large set-size effect. The results support C. Bundesen's (1990) claim that an extreme set-size effect leads to serial processing. Implications for parallel models of visual selection are discussed.

3D hyperpolarized C-13 EPI with calibrationless parallel imaging

NASA Astrophysics Data System (ADS)

Gordon, Jeremy W.; Hansen, Rie B.; Shin, Peter J.; Feng, Yesu; Vigneron, Daniel B.; Larson, Peder E. Z.

2018-04-01

With the translation of metabolic MRI with hyperpolarized 13C agents into the clinic, imaging approaches will require large volumetric FOVs to support clinical applications. Parallel imaging techniques will be crucial to increasing volumetric scan coverage while minimizing RF requirements and temporal resolution. Calibrationless parallel imaging approaches are well-suited for this application because they eliminate the need to acquire coil profile maps or auto-calibration data. In this work, we explored the utility of a calibrationless parallel imaging method (SAKE) and corresponding sampling strategies to accelerate and undersample hyperpolarized 13C data using 3D blipped EPI acquisitions and multichannel receive coils, and demonstrated its application in a human study of [1-13C]pyruvate metabolism.

Influence of the normal modes on the plasma uniformity in large scale CCP reactors

NASA Astrophysics Data System (ADS)

Eremin, Denis; Brinkmann, Ralf Peter; Mussenbrock, Thomas; Lane, Barton; Matsukuma, Masaaki; Ventzek, Peter

2016-09-01

Large scale capacitively coupled plasmas (CCP) driven by sources with high frequency components often exhibit phenomena which are absent in relatively well understood small scale CCPs driven at low frequencies. Of particular interest are such phenomena which affect discharge parameters of direct relevance to the plasma processing applications. One of such parameters is plasma uniformity. By using a self-consistent 2d3v Particle-in-cell/Monte-Carlo (PIC/MCC) code parallelized on GPU we have been able to show that uniformity of the plasma generated is influenced predominantly by two factors, the ionization pattern caused by high-energy electrons and the average temperature of low-energy plasma electrons. The heating mechanisms for these two groups of electrons appear to be different leading to different transversal (radial) profiles of the corresponding factors, which is well captured by the kinetic PIC/MCC code. We find that the heating mechanisms are intrinsically connected with excitation of normal modes inherent to a plasma-filled CCP reactor. In this work we study the wave nature of these phenomena, such as their excitation, propagation, and interaction with electrons. Supported by SFB-TR 87 project of the German Research Foundation and by the ``Experimental and numerical analysis of very high frequency capacitively coupled plasma discharges'' mutual research project between RUB and Tokyo Electron Ltd.

Flexible Language Constructs for Large Parallel Programs

DOE PAGES

Rosing, Matt; Schnabel, Robert

1994-01-01

The goal of the research described in this article is to develop flexible language constructs for writing large data parallel numerical programs for distributed memory (multiple instruction multiple data [MIMD]) multiprocessors. Previously, several models have been developed to support synchronization and communication. Models for global synchronization include single instruction multiple data (SIMD), single program multiple data (SPMD), and sequential programs annotated with data distribution statements. The two primary models for communication include implicit communication based on shared memory and explicit communication based on messages. None of these models by themselves seem sufficient to permit the natural and efficient expression ofmore » the variety of algorithms that occur in large scientific computations. In this article, we give an overview of a new language that combines many of these programming models in a clean manner. This is done in a modular fashion such that different models can be combined to support large programs. Within a module, the selection of a model depends on the algorithm and its efficiency requirements. In this article, we give an overview of the language and discuss some of the critical implementation details.« less

Large Scale Many-Body Perturbation Theory calculations: methodological developments, data collections, validation

NASA Astrophysics Data System (ADS)

Govoni, Marco; Galli, Giulia

Green's function based many-body perturbation theory (MBPT) methods are well established approaches to compute quasiparticle energies and electronic lifetimes. However, their application to large systems - for instance to heterogeneous systems, nanostructured, disordered, and defective materials - has been hindered by high computational costs. We will discuss recent MBPT methodological developments leading to an efficient formulation of electron-electron and electron-phonon interactions, and that can be applied to systems with thousands of electrons. Results using a formulation that does not require the explicit calculation of virtual states, nor the storage and inversion of large dielectric matrices will be presented. We will discuss data collections obtained using the WEST code, the advantages of the algorithms used in WEST over standard techniques, and the parallel performance. Work done in collaboration with I. Hamada, R. McAvoy, P. Scherpelz, and H. Zheng. This work was supported by MICCoM, as part of the Computational Materials Sciences Program funded by the U.S. Department of Energy, Office of Science, Basic Energy Sciences, Materials Sciences and Engineering Division and by ANL.

Massively parallel sparse matrix function calculations with NTPoly

NASA Astrophysics Data System (ADS)

Dawson, William; Nakajima, Takahito

2018-04-01

We present NTPoly, a massively parallel library for computing the functions of sparse, symmetric matrices. The theory of matrix functions is a well developed framework with a wide range of applications including differential equations, graph theory, and electronic structure calculations. One particularly important application area is diagonalization free methods in quantum chemistry. When the input and output of the matrix function are sparse, methods based on polynomial expansions can be used to compute matrix functions in linear time. We present a library based on these methods that can compute a variety of matrix functions. Distributed memory parallelization is based on a communication avoiding sparse matrix multiplication algorithm. OpenMP task parallellization is utilized to implement hybrid parallelization. We describe NTPoly's interface and show how it can be integrated with programs written in many different programming languages. We demonstrate the merits of NTPoly by performing large scale calculations on the K computer.

Analyzing Tropical Waves Using the Parallel Ensemble Empirical Model Decomposition Method: Preliminary Results from Hurricane Sandy

NASA Technical Reports Server (NTRS)

Shen, Bo-Wen; Cheung, Samson; Li, Jui-Lin F.; Wu, Yu-ling

2013-01-01

In this study, we discuss the performance of the parallel ensemble empirical mode decomposition (EMD) in the analysis of tropical waves that are associated with tropical cyclone (TC) formation. To efficiently analyze high-resolution, global, multiple-dimensional data sets, we first implement multilevel parallelism into the ensemble EMD (EEMD) and obtain a parallel speedup of 720 using 200 eight-core processors. We then apply the parallel EEMD (PEEMD) to extract the intrinsic mode functions (IMFs) from preselected data sets that represent (1) idealized tropical waves and (2) large-scale environmental flows associated with Hurricane Sandy (2012). Results indicate that the PEEMD is efficient and effective in revealing the major wave characteristics of the data, such as wavelengths and periods, by sifting out the dominant (wave) components. This approach has a potential for hurricane climate study by examining the statistical relationship between tropical waves and TC formation.

The method of parallel-hierarchical transformation for rapid recognition of dynamic images using GPGPU technology

NASA Astrophysics Data System (ADS)

Timchenko, Leonid; Yarovyi, Andrii; Kokriatskaya, Nataliya; Nakonechna, Svitlana; Abramenko, Ludmila; Ławicki, Tomasz; Popiel, Piotr; Yesmakhanova, Laura

2016-09-01

The paper presents a method of parallel-hierarchical transformations for rapid recognition of dynamic images using GPU technology. Direct parallel-hierarchical transformations based on cluster CPU-and GPU-oriented hardware platform. Mathematic models of training of the parallel hierarchical (PH) network for the transformation are developed, as well as a training method of the PH network for recognition of dynamic images. This research is most topical for problems on organizing high-performance computations of super large arrays of information designed to implement multi-stage sensing and processing as well as compaction and recognition of data in the informational structures and computer devices. This method has such advantages as high performance through the use of recent advances in parallelization, possibility to work with images of ultra dimension, ease of scaling in case of changing the number of nodes in the cluster, auto scan of local network to detect compute nodes.

Scalable multi-objective control for large scale water resources systems under uncertainty

NASA Astrophysics Data System (ADS)

Giuliani, Matteo; Quinn, Julianne; Herman, Jonathan; Castelletti, Andrea; Reed, Patrick

2016-04-01

The use of mathematical models to support the optimal management of environmental systems is rapidly expanding over the last years due to advances in scientific knowledge of the natural processes, efficiency of the optimization techniques, and availability of computational resources. However, undergoing changes in climate and society introduce additional challenges for controlling these systems, ultimately motivating the emergence of complex models to explore key causal relationships and dependencies on uncontrolled sources of variability. In this work, we contribute a novel implementation of the evolutionary multi-objective direct policy search (EMODPS) method for controlling environmental systems under uncertainty. The proposed approach combines direct policy search (DPS) with hierarchical parallelization of multi-objective evolutionary algorithms (MOEAs) and offers a threefold advantage: the DPS simulation-based optimization can be combined with any simulation model and does not add any constraint on modeled information, allowing the use of exogenous information in conditioning the decisions. Moreover, the combination of DPS and MOEAs prompts the generation or Pareto approximate set of solutions for up to 10 objectives, thus overcoming the decision biases produced by cognitive myopia, where narrow or restrictive definitions of optimality strongly limit the discovery of decision relevant alternatives. Finally, the use of large-scale MOEAs parallelization improves the ability of the designed solutions in handling the uncertainty due to severe natural variability. The proposed approach is demonstrated on a challenging water resources management problem represented by the optimal control of a network of four multipurpose water reservoirs in the Red River basin (Vietnam). As part of the medium-long term energy and food security national strategy, four large reservoirs have been constructed on the Red River tributaries, which are mainly operated for hydropower production, flood control, and water supply. Numerical results under historical as well as synthetically generated hydrologic conditions show that our approach is able to discover key system tradeoffs in the operations of the system. The ability of the algorithm to find near-optimal solutions increases with the number of islands in the adopted hierarchical parallelization scheme. In addition, although significant performance degradation is observed when the solutions designed over history are re-evaluated over synthetically generated inflows, we successfully reduced these vulnerabilities by identifying alternative solutions that are more robust to hydrologic uncertainties, while also addressing the tradeoffs across the Red River multi-sector services.

Development of the Large-Scale Statistical Analysis System of Satellites Observations Data with Grid Datafarm Architecture

NASA Astrophysics Data System (ADS)

Yamamoto, K.; Murata, K.; Kimura, E.; Honda, R.

2006-12-01

In the Solar-Terrestrial Physics (STP) field, the amount of satellite observation data has been increasing every year. It is necessary to solve the following three problems to achieve large-scale statistical analyses of plenty of data. (i) More CPU power and larger memory and disk size are required. However, total powers of personal computers are not enough to analyze such amount of data. Super-computers provide a high performance CPU and rich memory area, but they are usually separated from the Internet or connected only for the purpose of programming or data file transfer. (ii) Most of the observation data files are managed at distributed data sites over the Internet. Users have to know where the data files are located. (iii) Since no common data format in the STP field is available now, users have to prepare reading program for each data by themselves. To overcome the problems (i) and (ii), we constructed a parallel and distributed data analysis environment based on the Gfarm reference implementation of the Grid Datafarm architecture. The Gfarm shares both computational resources and perform parallel distributed processings. In addition, the Gfarm provides the Gfarm filesystem which can be as virtual directory tree among nodes. The Gfarm environment is composed of three parts; a metadata server to manage distributed files information, filesystem nodes to provide computational resources and a client to throw a job into metadata server and manages data processing schedulings. In the present study, both data files and data processes are parallelized on the Gfarm with 6 file system nodes: CPU clock frequency of each node is Pentium V 1GHz, 256MB memory and40GB disk. To evaluate performances of the present Gfarm system, we scanned plenty of data files, the size of which is about 300MB for each, in three processing methods: sequential processing in one node, sequential processing by each node and parallel processing by each node. As a result, in comparison between the number of files and the elapsed time, parallel and distributed processing shorten the elapsed time to 1/5 than sequential processing. On the other hand, sequential processing times were shortened in another experiment, whose file size is smaller than 100KB. In this case, the elapsed time to scan one file is within one second. It implies that disk swap took place in case of parallel processing by each node. We note that the operation became unstable when the number of the files exceeded 1000. To overcome the problem (iii), we developed an original data class. This class supports our reading of data files with various data formats since it converts them into an original data format since it defines schemata for every type of data and encapsulates the structure of data files. In addition, since this class provides a function of time re-sampling, users can easily convert multiple data (array) with different time resolution into the same time resolution array. Finally, using the Gfarm, we achieved a high performance environment for large-scale statistical data analyses. It should be noted that the present method is effective only when one data file size is large enough. At present, we are restructuring the new Gfarm environment with 8 nodes: CPU is Athlon 64 x2 Dual Core 2GHz, 2GB memory and 1.2TB disk (using RAID0) for each node. Our original class is to be implemented on the new Gfarm environment. In the present talk, we show the latest results with applying the present system for data analyses with huge number of satellite observation data files.

Multi-petascale highly efficient parallel supercomputer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Asaad, Sameh; Bellofatto, Ralph E.; Blocksome, Michael A.

A Multi-Petascale Highly Efficient Parallel Supercomputer of 100 petaflop-scale includes node architectures based upon System-On-a-Chip technology, where each processing node comprises a single Application Specific Integrated Circuit (ASIC). The ASIC nodes are interconnected by a five dimensional torus network that optimally maximize the throughput of packet communications between nodes and minimize latency. The network implements collective network and a global asynchronous network that provides global barrier and notification functions. Integrated in the node design include a list-based prefetcher. The memory system implements transaction memory, thread level speculation, and multiversioning cache that improves soft error rate at the same time andmore » supports DMA functionality allowing for parallel processing message-passing.« less

Simulating neural systems with Xyce.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schiek, Richard Louis; Thornquist, Heidi K.; Mei, Ting

2012-12-01

Sandias parallel circuit simulator, Xyce, can address large scale neuron simulations in a new way extending the range within which one can perform high-fidelity, multi-compartment neuron simulations. This report documents the implementation of neuron devices in Xyce, their use in simulation and analysis of neuron systems.

Large-scale enrichment and discovery of gene-associated SNPs

USDA-ARS?s Scientific Manuscript database

With the recent advent of massively parallel pyrosequencing by 454 Life Sciences it has become feasible to cost-effectively identify numerous single nucleotide polymorphisms (SNPs) within the recombinogenic regions of the maize (Zea mays L.) genome. We developed a modified version of hypomethylated...

RMG An Open Source Electronic Structure Code for Multi-Petaflops Calculations

NASA Astrophysics Data System (ADS)

Briggs, Emil; Lu, Wenchang; Hodak, Miroslav; Bernholc, Jerzy

RMG (Real-space Multigrid) is an open source, density functional theory code for quantum simulations of materials. It solves the Kohn-Sham equations on real-space grids, which allows for natural parallelization via domain decomposition. Either subspace or Davidson diagonalization, coupled with multigrid methods, are used to accelerate convergence. RMG is a cross platform open source package which has been used in the study of a wide range of systems, including semiconductors, biomolecules, and nanoscale electronic devices. It can optionally use GPU accelerators to improve performance on systems where they are available. The recently released versions (>2.0) support multiple GPU's per compute node, have improved performance and scalability, enhanced accuracy and support for additional hardware platforms. New versions of the code are regularly released at http://www.rmgdft.org. The releases include binaries for Linux, Windows and MacIntosh systems, automated builds for clusters using cmake, as well as versions adapted to the major supercomputing installations and platforms. Several recent, large-scale applications of RMG will be discussed.

Project Final Report: The Institute for Sustained Performance, Energy, and Resilience (SUPER)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hollingsworth, Jeffrey K.

This project concentrated on various aspects of creating and applying tool infrastructure to make it easier to effectively use large-scale parallel computers. This project was collaborative with Argonne National Laboratory, Lawrence Berkeley National Laboratory, Lawrence Livermore National Laboratory, Oak Ridge National Laboratory, U.C. San Diego, University of Maryland, University of North Carolina, University of Oregon, University Southern California, University of Tennessee, and University of Utah. The research conducted during this project at the University of Maryland is summarized in this report. The complete details of the work are available in the publications listed at the end of the report. Manymore » of the concepts created during this project have been incorporated into tools and made available as freely downloadable software (www.dyninst.org/harmony). It also supported the studies of six graduate students, one undergraduate student, and two post-docs. The funding also provided summer support for the PI and part of the salary of a research staff member.« less

Static analysis techniques for semiautomatic synthesis of message passing software skeletons

DOE PAGES

Sottile, Matthew; Dagit, Jason; Zhang, Deli; ...

2015-06-29

The design of high-performance computing architectures demands performance analysis of large-scale parallel applications to derive various parameters concerning hardware design and software development. The process of performance analysis and benchmarking an application can be done in several ways with varying degrees of fidelity. One of the most cost-effective ways is to do a coarse-grained study of large-scale parallel applications through the use of program skeletons. The concept of a “program skeleton” that we discuss in this article is an abstracted program that is derived from a larger program where source code that is determined to be irrelevant is removed formore » the purposes of the skeleton. In this work, we develop a semiautomatic approach for extracting program skeletons based on compiler program analysis. Finally, we demonstrate correctness of our skeleton extraction process by comparing details from communication traces, as well as show the performance speedup of using skeletons by running simulations in the SST/macro simulator.« less

Air-cathode microbial fuel cell array: a device for identifying and characterizing electrochemically active microbes.

PubMed

Hou, Huijie; Li, Lei; de Figueiredo, Paul; Han, Arum

2011-01-15

Microbial fuel cells (MFCs) have generated excitement in environmental and bioenergy communities due to their potential for coupling wastewater treatment with energy generation and powering diverse devices. The pursuit of strategies such as improving microbial cultivation practices and optimizing MFC devices has increased power generating capacities of MFCs. However, surprisingly few microbial species with electrochemical activity in MFCs have been identified because current devices do not support parallel analyses or high throughput screening. We have recently demonstrated the feasibility of using advanced microfabrication methods to fabricate an MFC microarray. Here, we extend these studies by demonstrating a microfabricated air-cathode MFC array system. The system contains 24 individual air-cathode MFCs integrated onto a single chip. The device enables the direct and parallel comparison of different microbes loaded onto the array. Environmental samples were used to validate the utility of the air-cathode MFC array system and two previously identified isolates, 7Ca (Shewanella sp.) and 3C (Arthrobacter sp.), were shown to display enhanced electrochemical activities of 2.69 mW/m(2) and 1.86 mW/m(2), respectively. Experiments using a large scale conventional air-cathode MFC validated these findings. The parallel air-cathode MFC array system demonstrated here is expected to promote and accelerate the discovery and characterization of electrochemically active microbes. Copyright © 2010 Elsevier B.V. All rights reserved.

Efficient parallel simulation of CO2 geologic sequestration insaline aquifers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Keni; Doughty, Christine; Wu, Yu-Shu

2007-01-01

An efficient parallel simulator for large-scale, long-termCO2 geologic sequestration in saline aquifers has been developed. Theparallel simulator is a three-dimensional, fully implicit model thatsolves large, sparse linear systems arising from discretization of thepartial differential equations for mass and energy balance in porous andfractured media. The simulator is based on the ECO2N module of the TOUGH2code and inherits all the process capabilities of the single-CPU TOUGH2code, including a comprehensive description of the thermodynamics andthermophysical properties of H2O-NaCl- CO2 mixtures, modeling singleand/or two-phase isothermal or non-isothermal flow processes, two-phasemixtures, fluid phases appearing or disappearing, as well as saltprecipitation or dissolution. The newmore » parallel simulator uses MPI forparallel implementation, the METIS software package for simulation domainpartitioning, and the iterative parallel linear solver package Aztec forsolving linear equations by multiple processors. In addition, theparallel simulator has been implemented with an efficient communicationscheme. Test examples show that a linear or super-linear speedup can beobtained on Linux clusters as well as on supercomputers. Because of thesignificant improvement in both simulation time and memory requirement,the new simulator provides a powerful tool for tackling larger scale andmore complex problems than can be solved by single-CPU codes. Ahigh-resolution simulation example is presented that models buoyantconvection, induced by a small increase in brine density caused bydissolution of CO2.« less

Large-scale molecular dynamics simulation of DNA: implementation and validation of the AMBER98 force field in LAMMPS.

PubMed

Grindon, Christina; Harris, Sarah; Evans, Tom; Novik, Keir; Coveney, Peter; Laughton, Charles

2004-07-15

Molecular modelling played a central role in the discovery of the structure of DNA by Watson and Crick. Today, such modelling is done on computers: the more powerful these computers are, the more detailed and extensive can be the study of the dynamics of such biological macromolecules. To fully harness the power of modern massively parallel computers, however, we need to develop and deploy algorithms which can exploit the structure of such hardware. The Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) is a scalable molecular dynamics code including long-range Coulomb interactions, which has been specifically designed to function efficiently on parallel platforms. Here we describe the implementation of the AMBER98 force field in LAMMPS and its validation for molecular dynamics investigations of DNA structure and flexibility against the benchmark of results obtained with the long-established code AMBER6 (Assisted Model Building with Energy Refinement, version 6). Extended molecular dynamics simulations on the hydrated DNA dodecamer d(CTTTTGCAAAAG)(2), which has previously been the subject of extensive dynamical analysis using AMBER6, show that it is possible to obtain excellent agreement in terms of static, dynamic and thermodynamic parameters between AMBER6 and LAMMPS. In comparison with AMBER6, LAMMPS shows greatly improved scalability in massively parallel environments, opening up the possibility of efficient simulations of order-of-magnitude larger systems and/or for order-of-magnitude greater simulation times.

Interactive Parallel Data Analysis within Data-Centric Cluster Facilities using the IPython Notebook

NASA Astrophysics Data System (ADS)

Pascoe, S.; Lansdowne, J.; Iwi, A.; Stephens, A.; Kershaw, P.

2012-12-01

The data deluge is making traditional analysis workflows for many researchers obsolete. Support for parallelism within popular tools such as matlab, IDL and NCO is not well developed and rarely used. However parallelism is necessary for processing modern data volumes on a timescale conducive to curiosity-driven analysis. Furthermore, for peta-scale datasets such as the CMIP5 archive, it is no longer practical to bring an entire dataset to a researcher's workstation for analysis, or even to their institutional cluster. Therefore, there is an increasing need to develop new analysis platforms which both enable processing at the point of data storage and which provides parallelism. Such an environment should, where possible, maintain the convenience and familiarity of our current analysis environments to encourage curiosity-driven research. We describe how we are combining the interactive python shell (IPython) with our JASMIN data-cluster infrastructure. IPython has been specifically designed to bridge the gap between the HPC-style parallel workflows and the opportunistic curiosity-driven analysis usually carried out using domain specific languages and scriptable tools. IPython offers a web-based interactive environment, the IPython notebook, and a cluster engine for parallelism all underpinned by the well-respected Python/Scipy scientific programming stack. JASMIN is designed to support the data analysis requirements of the UK and European climate and earth system modeling community. JASMIN, with its sister facility CEMS focusing the earth observation community, has 4.5 PB of fast parallel disk storage alongside over 370 computing cores provide local computation. Through the IPython interface to JASMIN, users can make efficient use of JASMIN's multi-core virtual machines to perform interactive analysis on all cores simultaneously or can configure IPython clusters across multiple VMs. Larger-scale clusters can be provisioned through JASMIN's batch scheduling system. Outputs can be summarised and visualised using the full power of Python's many scientific tools, including Scipy, Matplotlib, Pandas and CDAT. This rich user experience is delivered through the user's web browser; maintaining the interactive feel of a workstation-based environment with the parallel power of a remote data-centric processing facility.

Large-scale self-assembled zirconium phosphate smectic layers via a simple spray-coating process

NASA Astrophysics Data System (ADS)

Wong, Minhao; Ishige, Ryohei; White, Kevin L.; Li, Peng; Kim, Daehak; Krishnamoorti, Ramanan; Gunther, Robert; Higuchi, Takeshi; Jinnai, Hiroshi; Takahara, Atsushi; Nishimura, Riichi; Sue, Hung-Jue

2014-04-01

The large-scale assembly of asymmetric colloidal particles is used in creating high-performance fibres. A similar concept is extended to the manufacturing of thin films of self-assembled two-dimensional crystal-type materials with enhanced and tunable properties. Here we present a spray-coating method to manufacture thin, flexible and transparent epoxy films containing zirconium phosphate nanoplatelets self-assembled into a lamellar arrangement aligned parallel to the substrate. The self-assembled mesophase of zirconium phosphate nanoplatelets is stabilized by epoxy pre-polymer and exhibits rheology favourable towards large-scale manufacturing. The thermally cured film forms a mechanically robust coating and shows excellent gas barrier properties at both low- and high humidity levels as a result of the highly aligned and overlapping arrangement of nanoplatelets. This work shows that the large-scale ordering of high aspect ratio nanoplatelets is easier to achieve than previously thought and may have implications in the technological applications for similar materials.

Development of a Distributed Parallel Computing Framework to Facilitate Regional/Global Gridded Crop Modeling with Various Scenarios

NASA Astrophysics Data System (ADS)

Jang, W.; Engda, T. A.; Neff, J. C.; Herrick, J.

2017-12-01

Many crop models are increasingly used to evaluate crop yields at regional and global scales. However, implementation of these models across large areas using fine-scale grids is limited by computational time requirements. In order to facilitate global gridded crop modeling with various scenarios (i.e., different crop, management schedule, fertilizer, and irrigation) using the Environmental Policy Integrated Climate (EPIC) model, we developed a distributed parallel computing framework in Python. Our local desktop with 14 cores (28 threads) was used to test the distributed parallel computing framework in Iringa, Tanzania which has 406,839 grid cells. High-resolution soil data, SoilGrids (250 x 250 m), and climate data, AgMERRA (0.25 x 0.25 deg) were also used as input data for the gridded EPIC model. The framework includes a master file for parallel computing, input database, input data formatters, EPIC model execution, and output analyzers. Through the master file for parallel computing, the user-defined number of threads of CPU divides the EPIC simulation into jobs. Then, Using EPIC input data formatters, the raw database is formatted for EPIC input data and the formatted data moves into EPIC simulation jobs. Then, 28 EPIC jobs run simultaneously and only interesting results files are parsed and moved into output analyzers. We applied various scenarios with seven different slopes and twenty-four fertilizer ranges. Parallelized input generators create different scenarios as a list for distributed parallel computing. After all simulations are completed, parallelized output analyzers are used to analyze all outputs according to the different scenarios. This saves significant computing time and resources, making it possible to conduct gridded modeling at regional to global scales with high-resolution data. For example, serial processing for the Iringa test case would require 113 hours, while using the framework developed in this study requires only approximately 6 hours, a nearly 95% reduction in computing time.

SCORPIO: A Scalable Two-Phase Parallel I/O Library With Application To A Large Scale Subsurface Simulator

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sreepathi, Sarat; Sripathi, Vamsi; Mills, Richard T

2013-01-01

Inefficient parallel I/O is known to be a major bottleneck among scientific applications employed on supercomputers as the number of processor cores grows into the thousands. Our prior experience indicated that parallel I/O libraries such as HDF5 that rely on MPI-IO do not scale well beyond 10K processor cores, especially on parallel file systems (like Lustre) with single point of resource contention. Our previous optimization efforts for a massively parallel multi-phase and multi-component subsurface simulator (PFLOTRAN) led to a two-phase I/O approach at the application level where a set of designated processes participate in the I/O process by splitting themore » I/O operation into a communication phase and a disk I/O phase. The designated I/O processes are created by splitting the MPI global communicator into multiple sub-communicators. The root process in each sub-communicator is responsible for performing the I/O operations for the entire group and then distributing the data to rest of the group. This approach resulted in over 25X speedup in HDF I/O read performance and 3X speedup in write performance for PFLOTRAN at over 100K processor cores on the ORNL Jaguar supercomputer. This research describes the design and development of a general purpose parallel I/O library, SCORPIO (SCalable block-ORiented Parallel I/O) that incorporates our optimized two-phase I/O approach. The library provides a simplified higher level abstraction to the user, sitting atop existing parallel I/O libraries (such as HDF5) and implements optimized I/O access patterns that can scale on larger number of processors. Performance results with standard benchmark problems and PFLOTRAN indicate that our library is able to maintain the same speedups as before with the added flexibility of being applicable to a wider range of I/O intensive applications.« less

High-Performance Signal Detection for Adverse Drug Events using MapReduce Paradigm.

PubMed

Fan, Kai; Sun, Xingzhi; Tao, Ying; Xu, Linhao; Wang, Chen; Mao, Xianling; Peng, Bo; Pan, Yue

2010-11-13

Post-marketing pharmacovigilance is important for public health, as many Adverse Drug Events (ADEs) are unknown when those drugs were approved for marketing. However, due to the large number of reported drugs and drug combinations, detecting ADE signals by mining these reports is becoming a challenging task in terms of computational complexity. Recently, a parallel programming model, MapReduce has been introduced by Google to support large-scale data intensive applications. In this study, we proposed a MapReduce-based algorithm, for common ADE detection approach, Proportional Reporting Ratio (PRR), and tested it in mining spontaneous ADE reports from FDA. The purpose is to investigate the possibility of using MapReduce principle to speed up biomedical data mining tasks using this pharmacovigilance case as one specific example. The results demonstrated that MapReduce programming model could improve the performance of common signal detection algorithm for pharmacovigilance in a distributed computation environment at approximately liner speedup rates.

Implementing a Parallel Image Edge Detection Algorithm Based on the Otsu-Canny Operator on the Hadoop Platform

PubMed Central

Wang, Min; Tian, Yun

2018-01-01

The Canny operator is widely used to detect edges in images. However, as the size of the image dataset increases, the edge detection performance of the Canny operator decreases and its runtime becomes excessive. To improve the runtime and edge detection performance of the Canny operator, in this paper, we propose a parallel design and implementation for an Otsu-optimized Canny operator using a MapReduce parallel programming model that runs on the Hadoop platform. The Otsu algorithm is used to optimize the Canny operator's dual threshold and improve the edge detection performance, while the MapReduce parallel programming model facilitates parallel processing for the Canny operator to solve the processing speed and communication cost problems that occur when the Canny edge detection algorithm is applied to big data. For the experiments, we constructed datasets of different scales from the Pascal VOC2012 image database. The proposed parallel Otsu-Canny edge detection algorithm performs better than other traditional edge detection algorithms. The parallel approach reduced the running time by approximately 67.2% on a Hadoop cluster architecture consisting of 5 nodes with a dataset of 60,000 images. Overall, our approach system speeds up the system by approximately 3.4 times when processing large-scale datasets, which demonstrates the obvious superiority of our method. The proposed algorithm in this study demonstrates both better edge detection performance and improved time performance. PMID:29861711

Proceedings from the Workshop on Large-Grained Parallelism (2nd) Held in Hidden Valley, Pennsylvania on October 11-14, 1987.

DTIC Science & Technology

1987-11-01

The purpose of the workshop was to bring together people whose interests lie in the areas of operating I systems , programming languages, and formal... operating system support, and applications. There were parallel discussions on scheduling and distributed languages, and on real-time and operating ...number of key challenges: * Distributed systems , languages, environments - Make transactions efficient. Integrate them into the operating system

The Role of the Mantle on Structural Reactivation at the Plate Tectonics Scale (Invited)

NASA Astrophysics Data System (ADS)

Vauchez, A. R.; Tommasi, A.

2009-12-01

During orogeny, rifting, and in major strike-slip faults, the lithospheric mantle undergoes solid-state flow to accommodate the imposed strain. This deformation occurs mostly through crystal plasticity processes, like dislocation creep, and results in the development of a crystallographic preferred orientation (CPO) of olivine and pyroxene. Because these minerals, especially olivine, display strongly anisotropic physical properties, their preferred orientation confers anisotropic properties at the scale of the rock. When the deformation event comes to its end, the CPO are "frozen" and remain stable for millions or even billions years if no other deformation subsequently affects the lithospheric mantle. This means that anisotropic properties preserving a memory of previous deformation events may subsist in the continental mantle over very long periods of time. One of the main consequences of a well-developed olivine CPO is an anisotropic mantle viscosity and hence a deformation dependant on the orientation of the tectonic solicitations relative to the orientation of the olivine CPO inherited from the past orogenic events. The most obvious expression of this anisotropic mechanical behaviour is the influence of the inherited tectonic fabric on continental rifting. Most continental rifts that lead to successful continental breakup, like in the early Atlantic or the western Indian systems, formed parallel to ancient collisional belts. Moreover, the early stages of deformation in these systems are characterized by a transtensional strain regime involving a large component of strike-slip shearing parallel to the inherited fabric. The link between the lithospheric mantle fabric and the rift structure is further supported by seismic anisotropy measurements in major rifts (e.g., the East-African Rift) or at passive continental margins (e.g., the Atlantic Ocean) that show fast split S-waves polarized in a direction parallel to both the inherited fabric and the trend of the rift, and by the analysis of the CPO in mantle xenoliths collected in such areas. These observations are consistent with recent multi-scale numerical models showing that olivine CPO frozen in the lithospheric mantle result in an anisotropic mechanical behaviour. In a plate submitted to extension, CPO-induced anisotropy favours the reactivation in transtension of lithospheric-scale strike slip faults that are oblique to the imposed tensional stresses. Further investigation is needed to constrain the role of an inherited mechanical anisotropy of the lithosphere during compressional events and the possible feedbacks between an anisotropic viscous deformation of the lithospheric mantle and the seismic cycle. In both cases, crust-mantle coupling is likely for large-scale structures and mantle CPO may influence the kinematics of tectonic systems, at least during the initial stages of their evolution.

Computational methods and software systems for dynamics and control of large space structures

NASA Technical Reports Server (NTRS)

Park, K. C.; Felippa, C. A.; Farhat, C.; Pramono, E.

1990-01-01

This final report on computational methods and software systems for dynamics and control of large space structures covers progress to date, projected developments in the final months of the grant, and conclusions. Pertinent reports and papers that have not appeared in scientific journals (or have not yet appeared in final form) are enclosed. The grant has supported research in two key areas of crucial importance to the computer-based simulation of large space structure. The first area involves multibody dynamics (MBD) of flexible space structures, with applications directed to deployment, construction, and maneuvering. The second area deals with advanced software systems, with emphasis on parallel processing. The latest research thrust in the second area, as reported here, involves massively parallel computers.

Large Scale Software Building with CMake in ATLAS

NASA Astrophysics Data System (ADS)

Elmsheuser, J.; Krasznahorkay, A.; Obreshkov, E.; Undrus, A.; ATLAS Collaboration

2017-10-01

The offline software of the ATLAS experiment at the Large Hadron Collider (LHC) serves as the platform for detector data reconstruction, simulation and analysis. It is also used in the detector’s trigger system to select LHC collision events during data taking. The ATLAS offline software consists of several million lines of C++ and Python code organized in a modular design of more than 2000 specialized packages. Because of different workflows, many stable numbered releases are in parallel production use. To accommodate specific workflow requests, software patches with modified libraries are distributed on top of existing software releases on a daily basis. The different ATLAS software applications also require a flexible build system that strongly supports unit and integration tests. Within the last year this build system was migrated to CMake. A CMake configuration has been developed that allows one to easily set up and build the above mentioned software packages. This also makes it possible to develop and test new and modified packages on top of existing releases. The system also allows one to detect and execute partial rebuilds of the release based on single package changes. The build system makes use of CPack for building RPM packages out of the software releases, and CTest for running unit and integration tests. We report on the migration and integration of the ATLAS software to CMake and show working examples of this large scale project in production.

NWChem: A comprehensive and scalable open-source solution for large scale molecular simulations

NASA Astrophysics Data System (ADS)

Valiev, M.; Bylaska, E. J.; Govind, N.; Kowalski, K.; Straatsma, T. P.; Van Dam, H. J. J.; Wang, D.; Nieplocha, J.; Apra, E.; Windus, T. L.; de Jong, W. A.

2010-09-01

The latest release of NWChem delivers an open-source computational chemistry package with extensive capabilities for large scale simulations of chemical and biological systems. Utilizing a common computational framework, diverse theoretical descriptions can be used to provide the best solution for a given scientific problem. Scalable parallel implementations and modular software design enable efficient utilization of current computational architectures. This paper provides an overview of NWChem focusing primarily on the core theoretical modules provided by the code and their parallel performance. Program summaryProgram title: NWChem Catalogue identifier: AEGI_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEGI_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Open Source Educational Community License No. of lines in distributed program, including test data, etc.: 11 709 543 No. of bytes in distributed program, including test data, etc.: 680 696 106 Distribution format: tar.gz Programming language: Fortran 77, C Computer: all Linux based workstations and parallel supercomputers, Windows and Apple machines Operating system: Linux, OS X, Windows Has the code been vectorised or parallelized?: Code is parallelized Classification: 2.1, 2.2, 3, 7.3, 7.7, 16.1, 16.2, 16.3, 16.10, 16.13 Nature of problem: Large-scale atomistic simulations of chemical and biological systems require efficient and reliable methods for ground and excited solutions of many-electron Hamiltonian, analysis of the potential energy surface, and dynamics. Solution method: Ground and excited solutions of many-electron Hamiltonian are obtained utilizing density-functional theory, many-body perturbation approach, and coupled cluster expansion. These solutions or a combination thereof with classical descriptions are then used to analyze potential energy surface and perform dynamical simulations. Additional comments: Full documentation is provided in the distribution file. This includes an INSTALL file giving details of how to build the package. A set of test runs is provided in the examples directory. The distribution file for this program is over 90 Mbytes and therefore is not delivered directly when download or Email is requested. Instead a html file giving details of how the program can be obtained is sent. Running time: Running time depends on the size of the chemical system, complexity of the method, number of cpu's and the computational task. It ranges from several seconds for serial DFT energy calculations on a few atoms to several hours for parallel coupled cluster energy calculations on tens of atoms or ab-initio molecular dynamics simulation on hundreds of atoms.

Bilingual parallel programming

DOE Office of Scientific and Technical Information (OSTI.GOV)

Foster, I.; Overbeek, R.

1990-01-01

Numerous experiments have demonstrated that computationally intensive algorithms support adequate parallelism to exploit the potential of large parallel machines. Yet successful parallel implementations of serious applications are rare. The limiting factor is clearly programming technology. None of the approaches to parallel programming that have been proposed to date -- whether parallelizing compilers, language extensions, or new concurrent languages -- seem to adequately address the central problems of portability, expressiveness, efficiency, and compatibility with existing software. In this paper, we advocate an alternative approach to parallel programming based on what we call bilingual programming. We present evidence that this approach providesmore » and effective solution to parallel programming problems. The key idea in bilingual programming is to construct the upper levels of applications in a high-level language while coding selected low-level components in low-level languages. This approach permits the advantages of a high-level notation (expressiveness, elegance, conciseness) to be obtained without the cost in performance normally associated with high-level approaches. In addition, it provides a natural framework for reusing existing code.« less

Construction and comparison of parallel implicit kinetic solvers in three spatial dimensions

NASA Astrophysics Data System (ADS)

Titarev, Vladimir; Dumbser, Michael; Utyuzhnikov, Sergey

2014-01-01

The paper is devoted to the further development and systematic performance evaluation of a recent deterministic framework Nesvetay-3D for modelling three-dimensional rarefied gas flows. Firstly, a review of the existing discretization and parallelization strategies for solving numerically the Boltzmann kinetic equation with various model collision integrals is carried out. Secondly, a new parallelization strategy for the implicit time evolution method is implemented which improves scaling on large CPU clusters. Accuracy and scalability of the methods are demonstrated on a pressure-driven rarefied gas flow through a finite-length circular pipe as well as an external supersonic flow over a three-dimensional re-entry geometry of complicated aerodynamic shape.

Efficient Parallelization of a Dynamic Unstructured Application on the Tera MTA

NASA Technical Reports Server (NTRS)

Oliker, Leonid; Biswas, Rupak

1999-01-01

The success of parallel computing in solving real-life computationally-intensive problems relies on their efficient mapping and execution on large-scale multiprocessor architectures. Many important applications are both unstructured and dynamic in nature, making their efficient parallel implementation a daunting task. This paper presents the parallelization of a dynamic unstructured mesh adaptation algorithm using three popular programming paradigms on three leading supercomputers. We examine an MPI message-passing implementation on the Cray T3E and the SGI Origin2OOO, a shared-memory implementation using cache coherent nonuniform memory access (CC-NUMA) of the Origin2OOO, and a multi-threaded version on the newly-released Tera Multi-threaded Architecture (MTA). We compare several critical factors of this parallel code development, including runtime, scalability, programmability, and memory overhead. Our overall results demonstrate that multi-threaded systems offer tremendous potential for quickly and efficiently solving some of the most challenging real-life problems on parallel computers.

Parallelization of the FLAPW method and comparison with the PPW method

NASA Astrophysics Data System (ADS)

Canning, Andrew; Mannstadt, Wolfgang; Freeman, Arthur

2000-03-01

The FLAPW (full-potential linearized-augmented plane-wave) method is one of the most accurate first-principles methods for determining electronic and magnetic properties of crystals and surfaces. In the past the FLAPW method has been limited to systems of about a hundred atoms due to the lack of an efficient parallel implementation to exploit the power and memory of parallel computers. In this work we present an efficient parallelization of the method by division among the processors of the plane-wave components for each state. The code is also optimized for RISC (reduced instruction set computer) architectures, such as those found on most parallel computers, making full use of BLAS (basic linear algebra subprograms) wherever possible. Scaling results are presented for systems of up to 686 silicon atoms and 343 palladium atoms per unit cell running on up to 512 processors on a Cray T3E parallel supercomputer. Some results will also be presented on a comparison of the plane-wave pseudopotential method and the FLAPW method on large systems.

GENESIS: a hybrid-parallel and multi-scale molecular dynamics simulator with enhanced sampling algorithms for biomolecular and cellular simulations

PubMed Central

Jung, Jaewoon; Mori, Takaharu; Kobayashi, Chigusa; Matsunaga, Yasuhiro; Yoda, Takao; Feig, Michael; Sugita, Yuji

2015-01-01

GENESIS (Generalized-Ensemble Simulation System) is a new software package for molecular dynamics (MD) simulations of macromolecules. It has two MD simulators, called ATDYN and SPDYN. ATDYN is parallelized based on an atomic decomposition algorithm for the simulations of all-atom force-field models as well as coarse-grained Go-like models. SPDYN is highly parallelized based on a domain decomposition scheme, allowing large-scale MD simulations on supercomputers. Hybrid schemes combining OpenMP and MPI are used in both simulators to target modern multicore computer architectures. Key advantages of GENESIS are (1) the highly parallel performance of SPDYN for very large biological systems consisting of more than one million atoms and (2) the availability of various REMD algorithms (T-REMD, REUS, multi-dimensional REMD for both all-atom and Go-like models under the NVT, NPT, NPAT, and NPγT ensembles). The former is achieved by a combination of the midpoint cell method and the efficient three-dimensional Fast Fourier Transform algorithm, where the domain decomposition space is shared in real-space and reciprocal-space calculations. Other features in SPDYN, such as avoiding concurrent memory access, reducing communication times, and usage of parallel input/output files, also contribute to the performance. We show the REMD simulation results of a mixed (POPC/DMPC) lipid bilayer as a real application using GENESIS. GENESIS is released as free software under the GPLv2 licence and can be easily modified for the development of new algorithms and molecular models. WIREs Comput Mol Sci 2015, 5:310–323. doi: 10.1002/wcms.1220 PMID:26753008

A large scale GIS geodatabase of soil parameters supporting the modeling of conservation practice alternatives in the United States

USDA-ARS?s Scientific Manuscript database

Water quality modeling requires across-scale support of combined digital soil elements and simulation parameters. This paper presents the unprecedented development of a large spatial scale (1:250,000) ArcGIS geodatabase coverage designed as a functional repository of soil-parameters for modeling an...

Collaborative visual analytics of radio surveys in the Big Data era

NASA Astrophysics Data System (ADS)

Vohl, Dany; Fluke, Christopher J.; Hassan, Amr H.; Barnes, David G.; Kilborn, Virginia A.

2017-06-01

Radio survey datasets comprise an increasing number of individual observations stored as sets of multidimensional data. In large survey projects, astronomers commonly face limitations regarding: 1) interactive visual analytics of sufficiently large subsets of data; 2) synchronous and asynchronous collaboration; and 3) documentation of the discovery workflow. To support collaborative data inquiry, we present encube, a large-scale comparative visual analytics framework. encube can utilise advanced visualization environments such as the CAVE2 (a hybrid 2D and 3D virtual reality environment powered with a 100 Tflop/s GPU-based supercomputer and 84 million pixels) for collaborative analysis of large subsets of data from radio surveys. It can also run on standard desktops, providing a capable visual analytics experience across the display ecology. encube is composed of four primary units enabling compute-intensive processing, advanced visualisation, dynamic interaction, parallel data query, along with data management. Its modularity will make it simple to incorporate astronomical analysis packages and Virtual Observatory capabilities developed within our community. We discuss how encube builds a bridge between high-end display systems (such as CAVE2) and the classical desktop, preserving all traces of the work completed on either platform - allowing the research process to continue wherever you are.

Three pillars for achieving quantum mechanical molecular dynamics simulations of huge systems: Divide-and-conquer, density-functional tight-binding, and massively parallel computation.

PubMed

Nishizawa, Hiroaki; Nishimura, Yoshifumi; Kobayashi, Masato; Irle, Stephan; Nakai, Hiromi

2016-08-05

The linear-scaling divide-and-conquer (DC) quantum chemical methodology is applied to the density-functional tight-binding (DFTB) theory to develop a massively parallel program that achieves on-the-fly molecular reaction dynamics simulations of huge systems from scratch. The functions to perform large scale geometry optimization and molecular dynamics with DC-DFTB potential energy surface are implemented to the program called DC-DFTB-K. A novel interpolation-based algorithm is developed for parallelizing the determination of the Fermi level in the DC method. The performance of the DC-DFTB-K program is assessed using a laboratory computer and the K computer. Numerical tests show the high efficiency of the DC-DFTB-K program, a single-point energy gradient calculation of a one-million-atom system is completed within 60 s using 7290 nodes of the K computer. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

GROMACS 4:  Algorithms for Highly Efficient, Load-Balanced, and Scalable Molecular Simulation.

PubMed

Hess, Berk; Kutzner, Carsten; van der Spoel, David; Lindahl, Erik

2008-03-01

Molecular simulation is an extremely useful, but computationally very expensive tool for studies of chemical and biomolecular systems. Here, we present a new implementation of our molecular simulation toolkit GROMACS which now both achieves extremely high performance on single processors from algorithmic optimizations and hand-coded routines and simultaneously scales very well on parallel machines. The code encompasses a minimal-communication domain decomposition algorithm, full dynamic load balancing, a state-of-the-art parallel constraint solver, and efficient virtual site algorithms that allow removal of hydrogen atom degrees of freedom to enable integration time steps up to 5 fs for atomistic simulations also in parallel. To improve the scaling properties of the common particle mesh Ewald electrostatics algorithms, we have in addition used a Multiple-Program, Multiple-Data approach, with separate node domains responsible for direct and reciprocal space interactions. Not only does this combination of algorithms enable extremely long simulations of large systems but also it provides that simulation performance on quite modest numbers of standard cluster nodes.

Solvers for $$\\mathcal{O} (N)$$ Electronic Structure in the Strong Scaling Limit

DOE PAGES

Bock, Nicolas; Challacombe, William M.; Kale, Laxmikant

2016-01-26

Here we present a hybrid OpenMP/Charm\\tt++ framework for solving themore » $$\\mathcal{O} (N)$$ self-consistent-field eigenvalue problem with parallelism in the strong scaling regime, $$P\\gg{N}$$, where $P$ is the number of cores, and $N$ is a measure of system size, i.e., the number of matrix rows/columns, basis functions, atoms, molecules, etc. This result is achieved with a nested approach to spectral projection and the sparse approximate matrix multiply [Bock and Challacombe, SIAM J. Sci. Comput., 35 (2013), pp. C72--C98], and involves a recursive, task-parallel algorithm, often employed by generalized $N$-Body solvers, to occlusion and culling of negligible products in the case of matrices with decay. Lastly, employing classic technologies associated with generalized $N$-Body solvers, including overdecomposition, recursive task parallelism, orderings that preserve locality, and persistence-based load balancing, we obtain scaling beyond hundreds of cores per molecule for small water clusters ([H$${}_2$$O]$${}_N$$, $$N \\in \\{ 30, 90, 150 \\}$$, $$P/N \\approx \\{ 819, 273, 164 \\}$$) and find support for an increasingly strong scalability with increasing system size $N$.« less

Pragmatic clinical trials embedded in healthcare systems: generalizable lessons from the NIH Collaboratory.

PubMed

Weinfurt, Kevin P; Hernandez, Adrian F; Coronado, Gloria D; DeBar, Lynn L; Dember, Laura M; Green, Beverly B; Heagerty, Patrick J; Huang, Susan S; James, Kathryn T; Jarvik, Jeffrey G; Larson, Eric B; Mor, Vincent; Platt, Richard; Rosenthal, Gary E; Septimus, Edward J; Simon, Gregory E; Staman, Karen L; Sugarman, Jeremy; Vazquez, Miguel; Zatzick, Douglas; Curtis, Lesley H

2017-09-18

The clinical research enterprise is not producing the evidence decision makers arguably need in a timely and cost effective manner; research currently involves the use of labor-intensive parallel systems that are separate from clinical care. The emergence of pragmatic clinical trials (PCTs) poses a possible solution: these large-scale trials are embedded within routine clinical care and often involve cluster randomization of hospitals, clinics, primary care providers, etc. Interventions can be implemented by health system personnel through usual communication channels and quality improvement infrastructure, and data collected as part of routine clinical care. However, experience with these trials is nascent and best practices regarding design operational, analytic, and reporting methodologies are undeveloped. To strengthen the national capacity to implement cost-effective, large-scale PCTs, the Common Fund of the National Institutes of Health created the Health Care Systems Research Collaboratory (Collaboratory) to support the design, execution, and dissemination of a series of demonstration projects using a pragmatic research design. In this article, we will describe the Collaboratory, highlight some of the challenges encountered and solutions developed thus far, and discuss remaining barriers and opportunities for large-scale evidence generation using PCTs. A planning phase is critical, and even with careful planning, new challenges arise during execution; comparisons between arms can be complicated by unanticipated changes. Early and ongoing engagement with both health care system leaders and front-line clinicians is critical for success. There is also marked uncertainty when applying existing ethical and regulatory frameworks to PCTS, and using existing electronic health records for data capture adds complexity.

A Fine-Grained Pipelined Implementation for Large-Scale Matrix Inversion on FPGA

NASA Astrophysics Data System (ADS)

Zhou, Jie; Dou, Yong; Zhao, Jianxun; Xia, Fei; Lei, Yuanwu; Tang, Yuxing

Large-scale matrix inversion play an important role in many applications. However to the best of our knowledge, there is no FPGA-based implementation. In this paper, we explore the possibility of accelerating large-scale matrix inversion on FPGA. To exploit the computational potential of FPGA, we introduce a fine-grained parallel algorithm for matrix inversion. A scalable linear array processing elements (PEs), which is the core component of the FPGA accelerator, is proposed to implement this algorithm. A total of 12 PEs can be integrated into an Altera StratixII EP2S130F1020C5 FPGA on our self-designed board. Experimental results show that a factor of 2.6 speedup and the maximum power-performance of 41 can be achieved compare to Pentium Dual CPU with double SSE threads.

Large-scale tidal effect on redshift-space power spectrum in a finite-volume survey

NASA Astrophysics Data System (ADS)

Akitsu, Kazuyuki; Takada, Masahiro; Li, Yin

2017-04-01

Long-wavelength matter inhomogeneities contain cleaner information on the nature of primordial perturbations as well as the physics of the early Universe. The large-scale coherent overdensity and tidal force, not directly observable for a finite-volume galaxy survey, are both related to the Hessian of large-scale gravitational potential and therefore are of equal importance. We show that the coherent tidal force causes a homogeneous anisotropic distortion of the observed distribution of galaxies in all three directions, perpendicular and parallel to the line-of-sight direction. This effect mimics the redshift-space distortion signal of galaxy peculiar velocities, as well as a distortion by the Alcock-Paczynski effect. We quantify its impact on the redshift-space power spectrum to the leading order, and discuss its importance for ongoing and upcoming galaxy surveys.

GraphReduce: Large-Scale Graph Analytics on Accelerator-Based HPC Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sengupta, Dipanjan; Agarwal, Kapil; Song, Shuaiwen

2015-09-30

Recent work on real-world graph analytics has sought to leverage the massive amount of parallelism offered by GPU devices, but challenges remain due to the inherent irregularity of graph algorithms and limitations in GPU-resident memory for storing large graphs. We present GraphReduce, a highly efficient and scalable GPU-based framework that operates on graphs that exceed the device’s internal memory capacity. GraphReduce adopts a combination of both edge- and vertex-centric implementations of the Gather-Apply-Scatter programming model and operates on multiple asynchronous GPU streams to fully exploit the high degrees of parallelism in GPUs with efficient graph data movement between the hostmore » and the device.« less

Adapting the serial Alpgen parton-interaction generator to simulate LHC collisions on millions of parallel threads

DOE Office of Scientific and Technical Information (OSTI.GOV)

Childers, J. T.; Uram, T. D.; LeCompte, T. J.

As the LHC moves to higher energies and luminosity, the demand for computing resources increases accordingly and will soon outpace the growth of the World- wide LHC Computing Grid. To meet this greater demand, event generation Monte Carlo was targeted for adaptation to run on Mira, the supercomputer at the Argonne Leadership Computing Facility. Alpgen is a Monte Carlo event generation application that is used by LHC experiments in the simulation of collisions that take place in the Large Hadron Collider. This paper details the process by which Alpgen was adapted from a single-processor serial-application to a large-scale parallel-application andmore » the performance that was achieved.« less

Adapting the serial Alpgen parton-interaction generator to simulate LHC collisions on millions of parallel threads

DOE PAGES

Childers, J. T.; Uram, T. D.; LeCompte, T. J.; ...

2016-09-29

As the LHC moves to higher energies and luminosity, the demand for computing resources increases accordingly and will soon outpace the growth of the Worldwide LHC Computing Grid. To meet this greater demand, event generation Monte Carlo was targeted for adaptation to run on Mira, the supercomputer at the Argonne Leadership Computing Facility. Alpgen is a Monte Carlo event generation application that is used by LHC experiments in the simulation of collisions that take place in the Large Hadron Collider. Finally, this paper details the process by which Alpgen was adapted from a single-processor serial-application to a large-scale parallel-application andmore » the performance that was achieved.« less

Adapting the serial Alpgen parton-interaction generator to simulate LHC collisions on millions of parallel threads

DOE Office of Scientific and Technical Information (OSTI.GOV)

Childers, J. T.; Uram, T. D.; LeCompte, T. J.

As the LHC moves to higher energies and luminosity, the demand for computing resources increases accordingly and will soon outpace the growth of the Worldwide LHC Computing Grid. To meet this greater demand, event generation Monte Carlo was targeted for adaptation to run on Mira, the supercomputer at the Argonne Leadership Computing Facility. Alpgen is a Monte Carlo event generation application that is used by LHC experiments in the simulation of collisions that take place in the Large Hadron Collider. Finally, this paper details the process by which Alpgen was adapted from a single-processor serial-application to a large-scale parallel-application andmore » the performance that was achieved.« less

Software Engineering for Scientific Computer Simulations

NASA Astrophysics Data System (ADS)

Post, Douglass E.; Henderson, Dale B.; Kendall, Richard P.; Whitney, Earl M.

2004-11-01

Computer simulation is becoming a very powerful tool for analyzing and predicting the performance of fusion experiments. Simulation efforts are evolving from including only a few effects to many effects, from small teams with a few people to large teams, and from workstations and small processor count parallel computers to massively parallel platforms. Successfully making this transition requires attention to software engineering issues. We report on the conclusions drawn from a number of case studies of large scale scientific computing projects within DOE, academia and the DoD. The major lessons learned include attention to sound project management including setting reasonable and achievable requirements, building a good code team, enforcing customer focus, carrying out verification and validation and selecting the optimum computational mathematics approaches.

Load Balancing Strategies for Multi-Block Overset Grid Applications

NASA Technical Reports Server (NTRS)

Djomehri, M. Jahed; Biswas, Rupak; Lopez-Benitez, Noe; Biegel, Bryan (Technical Monitor)

2002-01-01

The multi-block overset grid method is a powerful technique for high-fidelity computational fluid dynamics (CFD) simulations about complex aerospace configurations. The solution process uses a grid system that discretizes the problem domain by using separately generated but overlapping structured grids that periodically update and exchange boundary information through interpolation. For efficient high performance computations of large-scale realistic applications using this methodology, the individual grids must be properly partitioned among the parallel processors. Overall performance, therefore, largely depends on the quality of load balancing. In this paper, we present three different load balancing strategies far overset grids and analyze their effects on the parallel efficiency of a Navier-Stokes CFD application running on an SGI Origin2000 machine.

Substructured multibody molecular dynamics.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grest, Gary Stephen; Stevens, Mark Jackson; Plimpton, Steven James

2006-11-01

We have enhanced our parallel molecular dynamics (MD) simulation software LAMMPS (Large-scale Atomic/Molecular Massively Parallel Simulator, lammps.sandia.gov) to include many new features for accelerated simulation including articulated rigid body dynamics via coupling to the Rensselaer Polytechnic Institute code POEMS (Parallelizable Open-source Efficient Multibody Software). We use new features of the LAMMPS software package to investigate rhodopsin photoisomerization, and water model surface tension and capillary waves at the vapor-liquid interface. Finally, we motivate the recipes of MD for practitioners and researchers in numerical analysis and computational mechanics.

Scaling Semantic Graph Databases in Size and Performance

DOE Office of Scientific and Technical Information (OSTI.GOV)

Morari, Alessandro; Castellana, Vito G.; Villa, Oreste

In this paper we present SGEM, a full software system for accelerating large-scale semantic graph databases on commodity clusters. Unlike current approaches, SGEM addresses semantic graph databases by only employing graph methods at all the levels of the stack. On one hand, this allows exploiting the space efficiency of graph data structures and the inherent parallelism of graph algorithms. These features adapt well to the increasing system memory and core counts of modern commodity clusters. On the other hand, however, these systems are optimized for regular computation and batched data transfers, while graph methods usually are irregular and generate fine-grainedmore » data accesses with poor spatial and temporal locality. Our framework comprises a SPARQL to data parallel C compiler, a library of parallel graph methods and a custom, multithreaded runtime system. We introduce our stack, motivate its advantages with respect to other solutions and show how we solved the challenges posed by irregular behaviors. We present the result of our software stack on the Berlin SPARQL benchmarks with datasets up to 10 billion triples (a triple corresponds to a graph edge), demonstrating scaling in dataset size and in performance as more nodes are added to the cluster.« less

Parallelization of the TRIGRS model for rainfall-induced landslides using the message passing interface

USGS Publications Warehouse

Alvioli, M.; Baum, R.L.

2016-01-01

We describe a parallel implementation of TRIGRS, the Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability Model for the timing and distribution of rainfall-induced shallow landslides. We have parallelized the four time-demanding execution modes of TRIGRS, namely both the saturated and unsaturated model with finite and infinite soil depth options, within the Message Passing Interface framework. In addition to new features of the code, we outline details of the parallel implementation and show the performance gain with respect to the serial code. Results are obtained both on commercial hardware and on a high-performance multi-node machine, showing the different limits of applicability of the new code. We also discuss the implications for the application of the model on large-scale areas and as a tool for real-time landslide hazard monitoring.

Satisfiability Test with Synchronous Simulated Annealing on the Fujitsu AP1000 Massively-Parallel Multiprocessor

NASA Technical Reports Server (NTRS)

Sohn, Andrew; Biswas, Rupak

1996-01-01

Solving the hard Satisfiability Problem is time consuming even for modest-sized problem instances. Solving the Random L-SAT Problem is especially difficult due to the ratio of clauses to variables. This report presents a parallel synchronous simulated annealing method for solving the Random L-SAT Problem on a large-scale distributed-memory multiprocessor. In particular, we use a parallel synchronous simulated annealing procedure, called Generalized Speculative Computation, which guarantees the same decision sequence as sequential simulated annealing. To demonstrate the performance of the parallel method, we have selected problem instances varying in size from 100-variables/425-clauses to 5000-variables/21,250-clauses. Experimental results on the AP1000 multiprocessor indicate that our approach can satisfy 99.9 percent of the clauses while giving almost a 70-fold speedup on 500 processors.