Massively parallel visualization: Parallel rendering
Hansen, C.D.; Krogh, M.; White, W.
1995-12-01
This paper presents rendering algorithms, developed for massively parallel processors (MPPs), for polygonal, spheres, and volumetric data. The polygon algorithm uses a data parallel approach whereas the sphere and volume renderer use a MIMD approach. Implementations for these algorithms are presented for the Thinking Machines Corporation CM-5 MPP.
Newman, G.A.; Commer, M.
2009-06-01
Three-dimensional (3D) geophysical imaging is now receiving considerable attention for electrical conductivity mapping of potential offshore oil and gas reservoirs. The imaging technology employs controlled source electromagnetic (CSEM) and magnetotelluric (MT) fields and treats geological media exhibiting transverse anisotropy. Moreover when combined with established seismic methods, direct imaging of reservoir fluids is possible. Because of the size of the 3D conductivity imaging problem, strategies are required exploiting computational parallelism and optimal meshing. The algorithm thus developed has been shown to scale to tens of thousands of processors. In one imaging experiment, 32,768 tasks/processors on the IBM Watson Research Blue Gene/L supercomputer were successfully utilized. Over a 24 hour period we were able to image a large scale field data set that previously required over four months of processing time on distributed clusters based on Intel or AMD processors utilizing 1024 tasks on an InfiniBand fabric. Electrical conductivity imaging using massively parallel computational resources produces results that cannot be obtained otherwise and are consistent with timeframes required for practical exploration problems.
NASA Astrophysics Data System (ADS)
Newman, Gregory A.; Commer, Michael
2009-07-01
Three-dimensional (3D) geophysical imaging is now receiving considerable attention for electrical conductivity mapping of potential offshore oil and gas reservoirs. The imaging technology employs controlled source electromagnetic (CSEM) and magnetotelluric (MT) fields and treats geological media exhibiting transverse anisotropy. Moreover when combined with established seismic methods, direct imaging of reservoir fluids is possible. Because of the size of the 3D conductivity imaging problem, strategies are required exploiting computational parallelism and optimal meshing. The algorithm thus developed has been shown to scale to tens of thousands of processors. In one imaging experiment, 32,768 tasks/processors on the IBM Watson Research Blue Gene/L supercomputer were successfully utilized. Over a 24 hour period we were able to image a large scale field data set that previously required over four months of processing time on distributed clusters based on Intel or AMD processors utilizing 1024 tasks on an InfiniBand fabric. Electrical conductivity imaging using massively parallel computational resources produces results that cannot be obtained otherwise and are consistent with timeframes required for practical exploration problems.
Massively parallel mathematical sieves
Montry, G.R.
1989-01-01
The Sieve of Eratosthenes is a well-known algorithm for finding all prime numbers in a given subset of integers. A parallel version of the Sieve is described that produces computational speedups over 800 on a hypercube with 1,024 processing elements for problems of fixed size. Computational speedups as high as 980 are achieved when the problem size per processor is fixed. The method of parallelization generalizes to other sieves and will be efficient on any ensemble architecture. We investigate two highly parallel sieves using scattered decomposition and compare their performance on a hypercube multiprocessor. A comparison of different parallelization techniques for the sieve illustrates the trade-offs necessary in the design and implementation of massively parallel algorithms for large ensemble computers.
Soltz, R; Vranas, P; Blumrich, M; Chen, D; Gara, A; Giampap, M; Heidelberger, P; Salapura, V; Sexton, J; Bhanot, G
2007-04-11
The theory of the strong nuclear force, Quantum Chromodynamics (QCD), can be numerically simulated from first principles on massively-parallel supercomputers using the method of Lattice Gauge Theory. We describe the special programming requirements of lattice QCD (LQCD) as well as the optimal supercomputer hardware architectures that it suggests. We demonstrate these methods on the BlueGene massively-parallel supercomputer and argue that LQCD and the BlueGene architecture are a natural match. This can be traced to the simple fact that LQCD is a regular lattice discretization of space into lattice sites while the BlueGene supercomputer is a discretization of space into compute nodes, and that both are constrained by requirements of locality. This simple relation is both technologically important and theoretically intriguing. The main result of this paper is the speedup of LQCD using up to 131,072 CPUs on the largest BlueGene/L supercomputer. The speedup is perfect with sustained performance of about 20% of peak. This corresponds to a maximum of 70.5 sustained TFlop/s. At these speeds LQCD and BlueGene are poised to produce the next generation of strong interaction physics theoretical results.
Parallel rendering techniques for massively parallel visualization
Hansen, C.; Krogh, M.; Painter, J.
1995-07-01
As the resolution of simulation models increases, scientific visualization algorithms which take advantage of the large memory. and parallelism of Massively Parallel Processors (MPPs) are becoming increasingly important. For large applications rendering on the MPP tends to be preferable to rendering on a graphics workstation due to the MPP`s abundant resources: memory, disk, and numerous processors. The challenge becomes developing algorithms that can exploit these resources while minimizing overhead, typically communication costs. This paper will describe recent efforts in parallel rendering for polygonal primitives as well as parallel volumetric techniques. This paper presents rendering algorithms, developed for massively parallel processors (MPPs), for polygonal, spheres, and volumetric data. The polygon algorithm uses a data parallel approach whereas the sphere and volume render use a MIMD approach. Implementations for these algorithms are presented for the Thinking Ma.chines Corporation CM-5 MPP.
Commer, M.; Newman, G.A.; Carazzone, J.J.; Dickens, T.A.; Green,K.E.; Wahrmund, L.A.; Willen, D.E.; Shiu, J.
2007-05-16
Large-scale controlled source electromagnetic (CSEM)three-dimensional (3D) geophysical imaging is now receiving considerableattention for electrical conductivity mapping of potential offshore oiland gas reservoirs. To cope with the typically large computationalrequirements of the 3D CSEM imaging problem, our strategies exploitcomputational parallelism and optimized finite-difference meshing. Wereport on an imaging experiment, utilizing 32,768 tasks/processors on theIBM Watson Research Blue Gene/L (BG/L) supercomputer. Over a 24-hourperiod, we were able to image a large scale marine CSEM field data setthat previously required over four months of computing time ondistributed clusters utilizing 1024 tasks on an Infiniband fabric. Thetotal initial data misfit could be decreased by 67 percent within 72completed inversion iterations, indicating an electrically resistiveregion in the southern survey area below a depth of 1500 m below theseafloor. The major part of the residual misfit stems from transmitterparallel receiver components that have an offset from the transmittersail line (broadside configuration). Modeling confirms that improvedbroadside data fits can be achieved by considering anisotropic electricalconductivities. While delivering a satisfactory gross scale image for thedepths of interest, the experiment provides important evidence for thenecessity of discriminating between horizontal and verticalconductivities for maximally consistent 3D CSEM inversions.
Efficient, massively parallel eigenvalue computation
NASA Technical Reports Server (NTRS)
Huo, Yan; Schreiber, Robert
1993-01-01
In numerical simulations of disordered electronic systems, one of the most common approaches is to diagonalize random Hamiltonian matrices and to study the eigenvalues and eigenfunctions of a single electron in the presence of a random potential. An effort to implement a matrix diagonalization routine for real symmetric dense matrices on massively parallel SIMD computers, the Maspar MP-1 and MP-2 systems, is described. Results of numerical tests and timings are also presented.
Massively parallel MRI detector arrays
NASA Astrophysics Data System (ADS)
Keil, Boris; Wald, Lawrence L.
2013-04-01
Originally proposed as a method to increase sensitivity by extending the locally high-sensitivity of small surface coil elements to larger areas via reception, the term parallel imaging now includes the use of array coils to perform image encoding. This methodology has impacted clinical imaging to the point where many examinations are performed with an array comprising multiple smaller surface coil elements as the detector of the MR signal. This article reviews the theoretical and experimental basis for the trend towards higher channel counts relying on insights gained from modeling and experimental studies as well as the theoretical analysis of the so-called “ultimate” SNR and g-factor. We also review the methods for optimally combining array data and changes in RF methodology needed to construct massively parallel MRI detector arrays and show some examples of state-of-the-art for highly accelerated imaging with the resulting highly parallel arrays.
Massively Parallel MRI Detector Arrays
Keil, Boris; Wald, Lawrence L
2013-01-01
Originally proposed as a method to increase sensitivity by extending the locally high-sensitivity of small surface coil elements to larger areas, the term parallel imaging now includes the use of array coils to perform image encoding. This methodology has impacted clinical imaging to the point where many examinations are performed with an array comprising multiple smaller surface coil elements as the detector of the MR signal. This article reviews the theoretical and experimental basis for the trend towards higher channel counts relying on insights gained from modeling and experimental studies as well as the theoretical analysis of the so-called “ultimate” SNR and g-factor. We also review the methods for optimally combining array data and changes in RF methodology needed to construct massively parallel MRI detector arrays and show some examples of state-of-the-art for highly accelerated imaging with the resulting highly parallel arrays. PMID:23453758
Massively parallel MRI detector arrays.
Keil, Boris; Wald, Lawrence L
2013-04-01
Originally proposed as a method to increase sensitivity by extending the locally high-sensitivity of small surface coil elements to larger areas via reception, the term parallel imaging now includes the use of array coils to perform image encoding. This methodology has impacted clinical imaging to the point where many examinations are performed with an array comprising multiple smaller surface coil elements as the detector of the MR signal. This article reviews the theoretical and experimental basis for the trend towards higher channel counts relying on insights gained from modeling and experimental studies as well as the theoretical analysis of the so-called "ultimate" SNR and g-factor. We also review the methods for optimally combining array data and changes in RF methodology needed to construct massively parallel MRI detector arrays and show some examples of state-of-the-art for highly accelerated imaging with the resulting highly parallel arrays. PMID:23453758
Massively parallel quantum computer simulator
NASA Astrophysics Data System (ADS)
De Raedt, K.; Michielsen, K.; De Raedt, H.; Trieu, B.; Arnold, G.; Richter, M.; Lippert, Th.; Watanabe, H.; Ito, N.
2007-01-01
We describe portable software to simulate universal quantum computers on massive parallel computers. We illustrate the use of the simulation software by running various quantum algorithms on different computer architectures, such as a IBM BlueGene/L, a IBM Regatta p690+, a Hitachi SR11000/J1, a Cray X1E, a SGI Altix 3700 and clusters of PCs running Windows XP. We study the performance of the software by simulating quantum computers containing up to 36 qubits, using up to 4096 processors and up to 1 TB of memory. Our results demonstrate that the simulator exhibits nearly ideal scaling as a function of the number of processors and suggest that the simulation software described in this paper may also serve as benchmark for testing high-end parallel computers.
Merlin - Massively parallel heterogeneous computing
NASA Technical Reports Server (NTRS)
Wittie, Larry; Maples, Creve
1989-01-01
Hardware and software for Merlin, a new kind of massively parallel computing system, are described. Eight computers are linked as a 300-MIPS prototype to develop system software for a larger Merlin network with 16 to 64 nodes, totaling 600 to 3000 MIPS. These working prototypes help refine a mapped reflective memory technique that offers a new, very general way of linking many types of computer to form supercomputers. Processors share data selectively and rapidly on a word-by-word basis. Fast firmware virtual circuits are reconfigured to match topological needs of individual application programs. Merlin's low-latency memory-sharing interfaces solve many problems in the design of high-performance computing systems. The Merlin prototypes are intended to run parallel programs for scientific applications and to determine hardware and software needs for a future Teraflops Merlin network.
Massively parallel femtosecond laser processing.
Hasegawa, Satoshi; Ito, Haruyasu; Toyoda, Haruyoshi; Hayasaki, Yoshio
2016-08-01
Massively parallel femtosecond laser processing with more than 1000 beams was demonstrated. Parallel beams were generated by a computer-generated hologram (CGH) displayed on a spatial light modulator (SLM). The key to this technique is to optimize the CGH in the laser processing system using a scheme called in-system optimization. It was analytically demonstrated that the number of beams is determined by the horizontal number of pixels in the SLM N_{SLM} that is imaged at the pupil plane of an objective lens and a distance parameter p_{d} obtained by dividing the distance between adjacent beams by the diffraction-limited beam diameter. A performance limitation of parallel laser processing in our system was estimated at N_{SLM} of 250 and p_{d} of 7.0. Based on these parameters, the maximum number of beams in a hexagonal close-packed structure was calculated to be 1189 by using an analytical equation. PMID:27505815
Multigrid on massively parallel architectures
Falgout, R D; Jones, J E
1999-09-17
The scalable implementation of multigrid methods for machines with several thousands of processors is investigated. Parallel performance models are presented for three different structured-grid multigrid algorithms, and a description is given of how these models can be used to guide implementation. Potential pitfalls are illustrated when moving from moderate-sized parallelism to large-scale parallelism, and results are given from existing multigrid codes to support the discussion. Finally, the use of mixed programming models is investigated for multigrid codes on clusters of SMPs.
Massively parallel neurocomputing for aerospace applications
NASA Technical Reports Server (NTRS)
Fijany, Amir; Barhen, Jacob; Toomarian, Nikzad
1993-01-01
An innovative hybrid, analog-digital charge-domain technology, for the massively parallel VLSI implementation of certain large scale matrix-vector operations, has recently been introduced. It employs arrays of Charge Coupled/Charge Injection Device cells holding an analog matrix of charge, which process digital vectors in parallel by means of binary, non-destructive charge transfer operations. The impact of this technology on massively parallel processing is discussed. Fundamentally new classes of algorithms, specifically designed for this emerging technology, as applied to signal processing, are derived.
Massively Parallel Computing: A Sandia Perspective
Dosanjh, Sudip S.; Greenberg, David S.; Hendrickson, Bruce; Heroux, Michael A.; Plimpton, Steve J.; Tomkins, James L.; Womble, David E.
1999-05-06
The computing power available to scientists and engineers has increased dramatically in the past decade, due in part to progress in making massively parallel computing practical and available. The expectation for these machines has been great. The reality is that progress has been slower than expected. Nevertheless, massively parallel computing is beginning to realize its potential for enabling significant break-throughs in science and engineering. This paper provides a perspective on the state of the field, colored by the authors' experiences using large scale parallel machines at Sandia National Laboratories. We address trends in hardware, system software and algorithms, and we also offer our view of the forces shaping the parallel computing industry.
Massive parallelism in the future of science
NASA Technical Reports Server (NTRS)
Denning, Peter J.
1988-01-01
Massive parallelism appears in three domains of action of concern to scientists, where it produces collective action that is not possible from any individual agent's behavior. In the domain of data parallelism, computers comprising very large numbers of processing agents, one for each data item in the result will be designed. These agents collectively can solve problems thousands of times faster than current supercomputers. In the domain of distributed parallelism, computations comprising large numbers of resource attached to the world network will be designed. The network will support computations far beyond the power of any one machine. In the domain of people parallelism collaborations among large groups of scientists around the world who participate in projects that endure well past the sojourns of individuals within them will be designed. Computing and telecommunications technology will support the large, long projects that will characterize big science by the turn of the century. Scientists must become masters in these three domains during the coming decade.
Massively parallel sequencing and rare disease
Ng, Sarah B.; Nickerson, Deborah A.; Bamshad, Michael J.; Shendure, Jay
2010-01-01
Massively parallel sequencing has enabled the rapid, systematic identification of variants on a large scale. This has, in turn, accelerated the pace of gene discovery and disease diagnosis on a molecular level and has the potential to revolutionize methods particularly for the analysis of Mendelian disease. Using massively parallel sequencing has enabled investigators to interrogate variants both in the context of linkage intervals and also on a genome-wide scale, in the absence of linkage information entirely. The primary challenge now is to distinguish between background polymorphisms and pathogenic mutations. Recently developed strategies for rare monogenic disorders have met with some early success. These strategies include filtering for potential causal variants based on frequency and function, and also ranking variants based on conservation scores and predicted deleteriousness to protein structure. Here, we review the recent literature in the use of high-throughput sequence data and its analysis in the discovery of causal mutations for rare disorders. PMID:20846941
Associative massively parallel processor for video processing
NASA Astrophysics Data System (ADS)
Krikelis, Argy; Tawiah, T.
1996-03-01
Massively parallel processing architectures have matured primarily through image processing and computer vision application. The similarity of processing requirements between these areas and video processing suggest that they should be very appropriate for video processing applications. This research describes the use of an associative massively parallel processing based system for video compression which includes architectural and system description, discussion of the implementation of compression tasks such as DCT/IDCT, Motion Estimation and Quantization and system evaluation. The core of the processing system is the ASP (Associative String Processor) architecture a modular massively parallel, programmable and inherently fault-tolerant fine-grain SIMD processing architecture incorporating a string of identical APEs (Associative Processing Elements), a reconfigurable inter-processor communication network and a Vector Data Buffer for fully-overlapped data input-output. For video compression applications a prototype system is developed, which is using ASP modules to implement the required compression tasks. This scheme leads to a linear speed up of the computation by simply adding more APEs to the modules.
Template based parallel checkpointing in a massively parallel computer system
Archer, Charles Jens; Inglett, Todd Alan
2009-01-13
A method and apparatus for a template based parallel checkpoint save for a massively parallel super computer system using a parallel variation of the rsync protocol, and network broadcast. In preferred embodiments, the checkpoint data for each node is compared to a template checkpoint file that resides in the storage and that was previously produced. Embodiments herein greatly decrease the amount of data that must be transmitted and stored for faster checkpointing and increased efficiency of the computer system. Embodiments are directed to a parallel computer system with nodes arranged in a cluster with a high speed interconnect that can perform broadcast communication. The checkpoint contains a set of actual small data blocks with their corresponding checksums from all nodes in the system. The data blocks may be compressed using conventional non-lossy data compression algorithms to further reduce the overall checkpoint size.
Efficient communication in massively parallel computers
Cypher, R.E.
1989-01-01
A fundamental operation in parallel computation is sorting. Sorting is important not only because it is required by many algorithms, but also because it can be used to implement irregular, pointer-based communication. The author studies two algorithms for sorting in massively parallel computers. First, he examines Shellsort. Shellsort is a sorting algorithm that is based on a sequence of parameters called increments. Shellsort can be used to create a parallel sorting device known as a sorting network. Researchers have suggested that if the correct increment sequence is used, an optimal size sorting network can be obtained. All published increment sequences have been monotonically decreasing. He shows that no monotonically decreasing increment sequence will yield an optimal size sorting network. Second, he presents a sorting algorithm called Cubesort. Cubesort is the fastest known sorting algorithm for a variety of parallel computers aver a wide range of parameters. He also presents a paradigm for developing parallel algorithms that have efficient communication. The paradigm, called the data reduction paradigm, consists of using a divide-and-conquer strategy. Both the division and combination phases of the divide-and-conquer algorithm may require irregular, pointer-based communication between processors. However, the problem is divided so as to limit the amount of data that must be communicated. As a result the communication can be performed efficiently. He presents data reduction algorithms for the image component labeling problem, the closest pair problem and four versions of the parallel prefix problem.
Massively Parallel Direct Simulation of Multiphase Flow
COOK,BENJAMIN K.; PREECE,DALE S.; WILLIAMS,J.R.
2000-08-10
The authors understanding of multiphase physics and the associated predictive capability for multi-phase systems are severely limited by current continuum modeling methods and experimental approaches. This research will deliver an unprecedented modeling capability to directly simulate three-dimensional multi-phase systems at the particle-scale. The model solves the fully coupled equations of motion governing the fluid phase and the individual particles comprising the solid phase using a newly discovered, highly efficient coupled numerical method based on the discrete-element method and the Lattice-Boltzmann method. A massively parallel implementation will enable the solution of large, physically realistic systems.
Time sharing massively parallel machines. Draft
Gorda, B.; Wolski, R.
1995-03-01
As part of the Massively Parallel Computing Initiative (MPCI) at the Lawrence Livermore National Laboratory, the authors have developed a simple, effective and portable time sharing mechanism by scheduling gangs of processes on tightly coupled parallel machines. By time-sharing the resources, the system interleaves production and interactive jobs. Immediate priority is given to interactive use, maintaining good response time. Production jobs are scheduled during idle periods, making use of the otherwise unused resources. In this paper the authors discuss their experience with gang scheduling over the 3 year life-time of the project. In section 2, they motivate the project and discuss some of its details. Section 3.0 describes the general scheduling problem and how gang scheduling addresses it. In section 4.0, they describe the implementation. Section 8.0 presents results culled over the lifetime of the project. They conclude this paper with some observations and possible future directions.
Seismic imaging on massively parallel computers
Ober, C.C.; Oldfield, R.A.; Womble, D.E.; Mosher, C.C.
1997-07-01
A key to reducing the risks and costs associated with oil and gas exploration is the fast, accurate imaging of complex geologies, such as salt domes in the Gulf of Mexico and overthrust regions in US onshore regions. Pre-stack depth migration generally yields the most accurate images, and one approach to this is to solve the scalar-wave equation using finite differences. Current industry computational capabilities are insufficient for the application of finite-difference, 3-D, prestack, depth-migration algorithms. High performance computers and state-of-the-art algorithms and software are required to meet this need. As part of an ongoing ACTI project funded by the US Department of Energy, the authors have developed a finite-difference, 3-D prestack, depth-migration code for massively parallel computer systems. The goal of this work is to demonstrate that massively parallel computers (thousands of processors) can be used efficiently for seismic imaging, and that sufficient computing power exists (or soon will exist) to make finite-difference, prestack, depth migration practical for oil and gas exploration.
MASSIVE HYBRID PARALLELISM FOR FULLY IMPLICIT MULTIPHYSICS
Cody J. Permann; David Andrs; John W. Peterson; Derek R. Gaston
2013-05-01
As hardware advances continue to modify the supercomputing landscape, traditional scientific software development practices will become more outdated, ineffective, and inefficient. The process of rewriting/retooling existing software for new architectures is a Sisyphean task, and results in substantial hours of development time, effort, and money. Software libraries which provide an abstraction of the resources provided by such architectures are therefore essential if the computational engineering and science communities are to continue to flourish in this modern computing environment. The Multiphysics Object Oriented Simulation Environment (MOOSE) framework enables complex multiphysics analysis tools to be built rapidly by scientists, engineers, and domain specialists, while also allowing them to both take advantage of current HPC architectures, and efficiently prepare for future supercomputer designs. MOOSE employs a hybrid shared-memory and distributed-memory parallel model and provides a complete and consistent interface for creating multiphysics analysis tools. In this paper, a brief discussion of the mathematical algorithms underlying the framework and the internal object-oriented hybrid parallel design are given. Representative massively parallel results from several applications areas are presented, and a brief discussion of future areas of research for the framework are provided.
Massive hybrid parallelism for fully implicit multiphysics
Gaston, D. R.; Permann, C. J.; Andrs, D.; Peterson, J. W.
2013-07-01
As hardware advances continue to modify the supercomputing landscape, traditional scientific software development practices will become more outdated, ineffective, and inefficient. The process of rewriting/retooling existing software for new architectures is a Sisyphean task, and results in substantial hours of development time, effort, and money. Software libraries which provide an abstraction of the resources provided by such architectures are therefore essential if the computational engineering and science communities are to continue to flourish in this modern computing environment. The Multiphysics Object Oriented Simulation Environment (MOOSE) framework enables complex multiphysics analysis tools to be built rapidly by scientists, engineers, and domain specialists, while also allowing them to both take advantage of current HPC architectures, and efficiently prepare for future supercomputer designs. MOOSE employs a hybrid shared-memory and distributed-memory parallel model and provides a complete and consistent interface for creating multiphysics analysis tools. In this paper, a brief discussion of the mathematical algorithms underlying the framework and the internal object-oriented hybrid parallel design are given. Representative massively parallel results from several applications areas are presented, and a brief discussion of future areas of research for the framework are provided. (authors)
Solid modeling on a massively parallel processor
Strip, D. ); Karasick, M. )
1992-01-01
Solid modeling underlies many technologies that are key to modern manufacturing. These range from computer-aided design systems to robot simulators, from finite element analysis to integrated circuit process modeling. The accuracy, and hence the utility, of these models is often constrained by the amount of computer time required to perform the desired operations. This paper presents a family of algorithms for solid modeling operations using the Connection Machine, a massively parallel SIMD processor. The authors describe a data structure for representing solid models and algorithms that use the representation to implement efficiently a variety of solid modeling operations. The authors give a sketch of the algorithm for intersecting solids and present computational experience using these algorithms. The data structure and algorithms are contrasted with those of serial architectures, and execution times are compared.
Multiplexed microsatellite recovery using massively parallel sequencing
Jennings, T.N.; Knaus, B.J.; Mullins, T.D.; Haig, S.M.; Cronn, R.C.
2011-01-01
Conservation and management of natural populations requires accurate and inexpensive genotyping methods. Traditional microsatellite, or simple sequence repeat (SSR), marker analysis remains a popular genotyping method because of the comparatively low cost of marker development, ease of analysis and high power of genotype discrimination. With the availability of massively parallel sequencing (MPS), it is now possible to sequence microsatellite-enriched genomic libraries in multiplex pools. To test this approach, we prepared seven microsatellite-enriched, barcoded genomic libraries from diverse taxa (two conifer trees, five birds) and sequenced these on one lane of the Illumina Genome Analyzer using paired-end 80-bp reads. In this experiment, we screened 6.1 million sequences and identified 356958 unique microreads that contained di- or trinucleotide microsatellites. Examination of four species shows that our conversion rate from raw sequences to polymorphic markers compares favourably to Sanger- and 454-based methods. The advantage of multiplexed MPS is that the staggering capacity of modern microread sequencing is spread across many libraries; this reduces sample preparation and sequencing costs to less than $400 (USD) per species. This price is sufficiently low that microsatellite libraries could be prepared and sequenced for all 1373 organisms listed as 'threatened' and 'endangered' in the United States for under $0.5M (USD).
Massively parallel neural network intelligent browse
NASA Astrophysics Data System (ADS)
Maxwell, Thomas P.; Zion, Philip M.
1992-04-01
A massively parallel neural network architecture is currently being developed as a potential component of a distributed information system in support of NASA's Earth Observing System. This architecture can be trained, via an iterative learning process, to recognize objects in images based on texture features, allowing scientists to search for all patterns which are similar to a target pattern in a database of images. It may facilitate scientific inquiry by allowing scientists to automatically search for physical features of interest in a database through computer pattern recognition, alleviating the need for exhaustive visual searches through possibly thousands of images. The architecture is implemented on a Connection Machine such that each physical processor contains a simulated 'neuron' which views a feature vector derived from a subregion of the input image. Each of these neurons is trained, via the perceptron rule, to identify the same pattern. The network output gives a probability distribution over the input image of finding the target pattern in a given region. In initial tests the architecture was trained to separate regions containing clouds from clear regions in 512 by 512 pixel AVHRR images. We found that in about 10 minutes we can train a network to perform with high accuracy in recognizing clouds which were texturally similar to a target cloud group. These promising results suggest that this type of architecture may play a significant role in coping with the forthcoming flood of data from the Earth-monitoring missions of the major space-faring nations.
Seismic imaging on massively parallel computers
Ober, C.C.; Oldfield, R.; Womble, D.E.; VanDyke, J.; Dosanjh, S.
1996-03-01
Fast, accurate imaging of complex, oil-bearing geologies, such as overthrusts and salt domes, is the key to reducing the costs of domestic oil and gas exploration. Geophysicists say that the known oil reserves in the Gulf of Mexico could be significantly increased if accurate seismic imaging beneath salt domes was possible. A range of techniques exist for imaging these regions, but the highly accurate techniques involve the solution of the wave equation and are characterized by large data sets and large computational demands. Massively parallel computers can provide the computational power for these highly accurate imaging techniques. A brief introduction to seismic processing will be presented, and the implementation of a seismic-imaging code for distributed memory computers will be discussed. The portable code, Salvo, performs a wave equation-based, 3-D, prestack, depth imaging and currently runs on the Intel Paragon and the Cray T3D. It used MPI for portability, and has sustained 22 Mflops/sec/proc (compiled FORTRAN) on the Intel Paragon.
Fault tolerant massively parallel processing architecture
Balasubramanian, V.; Banerjee, P.
1987-08-01
This paper presents two massively parallel processing architectures suitable for solving a wide variety of algorithms of divide-and-conquer type for problems such as the discrete Fourier transform, production systems, design automation, and others. The first architecture, called the Chain-structured Butterfly ARchitecture (CBAR), consists of a two-dimensional array of N-L . (log/sub 2/(L)+1) processing elements (PE) organized as L levels of log/sub 2/(L)+1 stages, and which has the butterfly connection between PEs in consecutive stages with straight-through feedback between PEs in the last and first stages. This connection system has the desirable property of allowing thousands of PEs to be connected with O(N) connection cost, O(log/sub 2/(N/log/sub 2/N)) communication paths, and a small number (=4) of I/O ports per PE. However, this architecture is not fault tolerant. The authors, therefore, propose a second architecture, called the REconfigurable Chain-structured Butterfly ARchitecture (RECBAR), which is a modified version of the CBAR. The RECBAR possesses all the desirable features of the CBAR, with the number of I/O ports per PE increased to six, and uses O(log/sub 2/N)/N) overhead in PEs and approximately 50% overhead in links to achieve single-level fault tolerance. Reliability improvements of the RECBAR over the CBAR are studied. This paper also presents a distributed diagnostic and structuring algorithm for the RECBAR that enables the architecture to detect faults and structure itself accordingly within 2 . log/sub 2/(L)+1 time steps, thus making it a truly fault tolerant architecture.
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.
Visualization on massively parallel computers using CM/AVS
Krogh, M.F.; Hansen, C.D.
1993-09-01
CM/AVS is a visualization environment for the massively parallel CM-5 from Thinking Machines. It provides a backend to the standard commercially available AVS visualization product. At the Advanced Computing Laboratory at Los Alamos National Laboratory, we have been experimenting and utilizing this software within our visualization environment. This paper describes our experiences with CM/AVS. The conclusions reached are applicable to any implimentation of visualization software within a massively parallel computing environment.
Experimental free-space optical network for massively parallel computers
NASA Astrophysics Data System (ADS)
Araki, S.; Kajita, M.; Kasahara, K.; Kubota, K.; Kurihara, K.; Redmond, I.; Schenfeld, E.; Suzaki, T.
1996-03-01
A free-space optical interconnection scheme is described for massively parallel processors based on the interconnection-cached network architecture. The optical network operates in a circuit-switching mode. Combined with a packet-switching operation among the circuit-switched optical channels, a high-bandwidth, low-latency network for massively parallel processing results. The design and assembly of a 64-channel experimental prototype is discussed, and operational results are presented.
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.
IMPAIR: massively parallel deconvolution on the GPU
NASA Astrophysics Data System (ADS)
Sherry, Michael; Shearer, Andy
2013-02-01
The IMPAIR software is a high throughput image deconvolution tool for processing large out-of-core datasets of images, varying from large images with spatially varying PSFs to large numbers of images with spatially invariant PSFs. IMPAIR implements a parallel version of the tried and tested Richardson-Lucy deconvolution algorithm regularised via a custom wavelet thresholding library. It exploits the inherently parallel nature of the convolution operation to achieve quality results on consumer grade hardware: through the NVIDIA Tesla GPU implementation, the multi-core OpenMP implementation, and the cluster computing MPI implementation of the software. IMPAIR aims to address the problem of parallel processing in both top-down and bottom-up approaches: by managing the input data at the image level, and by managing the execution at the instruction level. These combined techniques will lead to a scalable solution with minimal resource consumption and maximal load balancing. IMPAIR is being developed as both a stand-alone tool for image processing, and as a library which can be embedded into non-parallel code to transparently provide parallel high throughput deconvolution.
EFFICIENT SCHEDULING OF PARALLEL JOBS ON MASSIVELY PARALLEL SYSTEMS
F. PETRINI; W. FENG
1999-09-01
We present buffered coscheduling, a new methodology to multitask parallel jobs in a message-passing environment and to develop parallel programs that can pave the way to the efficient implementation of a distributed operating system. Buffered coscheduling is based on three innovative techniques: communication buffering, strobing, and non-blocking communication. By leveraging these techniques, we can perform effective optimizations based on the global status of the parallel machine rather than on the limited knowledge available locally to each processor. The advantages of buffered coscheduling include higher resource utilization, reduced communication overhead, efficient implementation of low-control strategies and fault-tolerant protocols, accurate performance modeling, and a simplified yet still expressive parallel programming model. Preliminary experimental results show that buffered coscheduling is very effective in increasing the overall performance in the presence of load imbalance and communication-intensive workloads.
Scan line graphics generation on the massively parallel processor
NASA Technical Reports Server (NTRS)
Dorband, John E.
1988-01-01
Described here is how researchers implemented a scan line graphics generation algorithm on the Massively Parallel Processor (MPP). Pixels are computed in parallel and their results are applied to the Z buffer in large groups. To perform pixel value calculations, facilitate load balancing across the processors and apply the results to the Z buffer efficiently in parallel requires special virtual routing (sort computation) techniques developed by the author especially for use on single-instruction multiple-data (SIMD) architectures.
Massively Parallel Sequencing: The Next Big Thing in Genetic Medicine
Tucker, Tracy; Marra, Marco; Friedman, Jan M.
2009-01-01
Massively parallel sequencing has reduced the cost and increased the throughput of genomic sequencing by more than three orders of magnitude, and it seems likely that costs will fall and throughput improve even more in the next few years. Clinical use of massively parallel sequencing will provide a way to identify the cause of many diseases of unknown etiology through simultaneous screening of thousands of loci for pathogenic mutations and by sequencing biological specimens for the genomic signatures of novel infectious agents. In addition to providing these entirely new diagnostic capabilities, massively parallel sequencing may also replace arrays and Sanger sequencing in clinical applications where they are currently being used. Routine clinical use of massively parallel sequencing will require higher accuracy, better ways to select genomic subsets of interest, and improvements in the functionality, speed, and ease of use of data analysis software. In addition, substantial enhancements in laboratory computer infrastructure, data storage, and data transfer capacity will be needed to handle the extremely large data sets produced. Clinicians and laboratory personnel will require training to use the sequence data effectively, and appropriate methods will need to be developed to deal with the incidental discovery of pathogenic mutations and variants of uncertain clinical significance. Massively parallel sequencing has the potential to transform the practice of medical genetics and related fields, but the vast amount of personal genomic data produced will increase the responsibility of geneticists to ensure that the information obtained is used in a medically and socially responsible manner. PMID:19679224
Massively parallel neural encoding and decoding of visual stimuli.
Lazar, Aurel A; Zhou, Yiyin
2012-08-01
The massively parallel nature of video Time Encoding Machines (TEMs) calls for scalable, massively parallel decoders that are implemented with neural components. The current generation of decoding algorithms is based on computing the pseudo-inverse of a matrix and does not satisfy these requirements. Here we consider video TEMs with an architecture built using Gabor receptive fields and a population of Integrate-and-Fire neurons. We show how to build a scalable architecture for video Time Decoding Machines using recurrent neural networks. Furthermore, we extend our architecture to handle the reconstruction of visual stimuli encoded with massively parallel video TEMs having neurons with random thresholds. Finally, we discuss in detail our algorithms and demonstrate their scalability and performance on a large scale GPU cluster. PMID:22397951
The Challenge of Massively Parallel Computing
WOMBLE,DAVID E.
1999-11-03
Since the mid-1980's, there have been a number of commercially available parallel computers with hundreds or thousands of processors. These machines have provided a new capability to the scientific community, and they been used successfully by scientists and engineers although with varying degrees of success. One of the reasons for the limited success is the difficulty, or perceived difficulty, in developing code for these machines. In this paper we discuss many of the issues and challenges in developing scalable hardware, system software and algorithms for machines comprising hundreds or thousands of processors.
Staging memory for massively parallel processor
NASA Technical Reports Server (NTRS)
Batcher, Kenneth E. (Inventor)
1988-01-01
The invention herein relates to a computer organization capable of rapidly processing extremely large volumes of data. A staging memory is provided having a main stager portion consisting of a large number of memory banks which are accessed in parallel to receive, store, and transfer data words simultaneous with each other. Substager portions interconnect with the main stager portion to match input and output data formats with the data format of the main stager portion. An address generator is coded for accessing the data banks for receiving or transferring the appropriate words. Input and output permutation networks arrange the lineal order of data into and out of the memory banks.
Design and implementation of a massively parallel version of DIRECT
He, J.; Verstak, A.; Watson, L.; Sosonkina, M.
2007-10-24
This paper describes several massively parallel implementations for a global search algorithm DIRECT. Two parallel schemes take different approaches to address DIRECT's design challenges imposed by memory requirements and data dependency. Three design aspects in topology, data structures, and task allocation are compared in detail. The goal is to analytically investigate the strengths and weaknesses of these parallel schemes, identify several key sources of inefficiency, and experimentally evaluate a number of improvements in the latest parallel DIRECT implementation. The performance studies demonstrate improved data structure efficiency and load balancing on a 2200 processor cluster.
Massively parallel solution of the assignment problem. Technical report
Wein, J.; Zenios, S.
1990-12-01
In this paper we discuss the design, implementation and effectiveness of massively parallel algorithms for the solution of large-scale assignment problems. In particular, we study the auction algorithms of Bertsekas, an algorithm based on the method of multipliers of Hestenes and Powell, and an algorithm based on the alternating direction method of multipliers of Eckstein. We discuss alternative approaches to the massively parallel implementation of the auction algorithm, including Jacobi, Gauss-Seidel and a hybrid scheme. The hybrid scheme, in particular, exploits two different levels of parallelism and an efficient way of communicating the data between them without the need to perform general router operations across the hypercube network. We then study the performance of massively parallel implementations of two methods of multipliers. Implementations are carried out on the Connection Machine CM-2, and the algorithms are evaluated empirically with the solution of large scale problems. The hybrid scheme significantly outperforms all of the other methods and gives the best computational results to date for a massively parallel solution to this problem.
Shift: A Massively Parallel Monte Carlo Radiation Transport Package
Pandya, Tara M; Johnson, Seth R; Davidson, Gregory G; Evans, Thomas M; Hamilton, Steven P
2015-01-01
This paper discusses the massively-parallel Monte Carlo radiation transport package, Shift, developed at Oak Ridge National Laboratory. It reviews the capabilities, implementation, and parallel performance of this code package. Scaling results demonstrate very good strong and weak scaling behavior of the implemented algorithms. Benchmark results from various reactor problems show that Shift results compare well to other contemporary Monte Carlo codes and experimental results.
Efficient parallel global garbage collection on massively parallel computers
Kamada, Tomio; Matsuoka, Satoshi; Yonezawa, Akinori
1994-12-31
On distributed-memory high-performance MPPs where processors are interconnected by an asynchronous network, efficient Garbage Collection (GC) becomes difficult due to inter-node references and references within pending, unprocessed messages. The parallel global GC algorithm (1) takes advantage of reference locality, (2) efficiently traverses references over nodes, (3) admits minimum pause time of ongoing computations, and (4) has been shown to scale up to 1024 node MPPs. The algorithm employs a global weight counting scheme to substantially reduce message traffic. The two methods for confirming the arrival of pending messages are used: one counts numbers of messages and the other uses network `bulldozing.` Performance evaluation in actual implementations on a multicomputer with 32-1024 nodes, Fujitsu AP1000, reveals various favorable properties of the algorithm.
Solving unstructured grid problems on massively parallel computers
NASA Technical Reports Server (NTRS)
Hammond, Steven W.; Schreiber, Robert
1990-01-01
A highly parallel graph mapping technique that enables one to efficiently solve unstructured grid problems on massively parallel computers is presented. Many implicit and explicit methods for solving discretized partial differential equations require each point in the discretization to exchange data with its neighboring points every time step or iteration. The cost of this communication can negate the high performance promised by massively parallel computing. To eliminate this bottleneck, the graph of the irregular problem is mapped into the graph representing the interconnection topology of the computer such that the sum of the distances that the messages travel is minimized. It is shown that using the heuristic mapping algorithm significantly reduces the communication time compared to a naive assignment of processes to processors.
Time efficient 3-D electromagnetic modeling on massively parallel computers
Alumbaugh, D.L.; Newman, G.A.
1995-08-01
A numerical modeling algorithm has been developed to simulate the electromagnetic response of a three dimensional earth to a dipole source for frequencies ranging from 100 to 100MHz. The numerical problem is formulated in terms of a frequency domain--modified vector Helmholtz equation for the scattered electric fields. The resulting differential equation is approximated using a staggered finite difference grid which results in a linear system of equations for which the matrix is sparse and complex symmetric. The system of equations is solved using a preconditioned quasi-minimum-residual method. Dirichlet boundary conditions are employed at the edges of the mesh by setting the tangential electric fields equal to zero. At frequencies less than 1MHz, normal grid stretching is employed to mitigate unwanted reflections off the grid boundaries. For frequencies greater than this, absorbing boundary conditions must be employed by making the stretching parameters of the modified vector Helmholtz equation complex which introduces loss at the boundaries. To allow for faster calculation of realistic models, the original serial version of the code has been modified to run on a massively parallel architecture. This modification involves three distinct tasks; (1) mapping the finite difference stencil to a processor stencil which allows for the necessary information to be exchanged between processors that contain adjacent nodes in the model, (2) determining the most efficient method to input the model which is accomplished by dividing the input into ``global`` and ``local`` data and then reading the two sets in differently, and (3) deciding how to output the data which is an inherently nonparallel process.
A Programming Model for Massive Data Parallelism with Data Dependencies
Cui, Xiaohui; Mueller, Frank; Potok, Thomas E; Zhang, Yongpeng
2009-01-01
Accelerating processors can often be more cost and energy effective for a wide range of data-parallel computing problems than general-purpose processors. For graphics processor units (GPUs), this is particularly the case when program development is aided by environments such as NVIDIA s Compute Unified Device Architecture (CUDA), which dramatically reduces the gap between domain-specific architectures and general purpose programming. Nonetheless, general-purpose GPU (GPGPU) programming remains subject to several restrictions. Most significantly, the separation of host (CPU) and accelerator (GPU) address spaces requires explicit management of GPU memory resources, especially for massive data parallelism that well exceeds the memory capacity of GPUs. One solution to this problem is to transfer data between the GPU and host memories frequently. In this work, we investigate another approach. We run massively data-parallel applications on GPU clusters. We further propose a programming model for massive data parallelism with data dependencies for this scenario. Experience from micro benchmarks and real-world applications shows that our model provides not only ease of programming but also significant performance gains.
NASA Technical Reports Server (NTRS)
Karpoukhin, Mikhii G.; Kogan, Boris Y.; Karplus, Walter J.
1995-01-01
The simulation of heart arrhythmia and fibrillation are very important and challenging tasks. The solution of these problems using sophisticated mathematical models is beyond the capabilities of modern super computers. To overcome these difficulties it is proposed to break the whole simulation problem into two tightly coupled stages: generation of the action potential using sophisticated models. and propagation of the action potential using simplified models. The well known simplified models are compared and modified to bring the rate of depolarization and action potential duration restitution closer to reality. The modified method of lines is used to parallelize the computational process. The conditions for the appearance of 2D spiral waves after the application of a premature beat and the subsequent traveling of the spiral wave inside the simulated tissue are studied.
The language parallel Pascal and other aspects of the massively parallel processor
NASA Technical Reports Server (NTRS)
Reeves, A. P.; Bruner, J. D.
1982-01-01
A high level language for the Massively Parallel Processor (MPP) was designed. This language, called Parallel Pascal, is described in detail. A description of the language design, a description of the intermediate language, Parallel P-Code, and details for the MPP implementation are included. Formal descriptions of Parallel Pascal and Parallel P-Code are given. A compiler was developed which converts programs in Parallel Pascal into the intermediate Parallel P-Code language. The code generator to complete the compiler for the MPP is being developed independently. A Parallel Pascal to Pascal translator was also developed. The architecture design for a VLSI version of the MPP was completed with a description of fault tolerant interconnection networks. The memory arrangement aspects of the MPP are discussed and a survey of other high level languages is given.
Supercomputing on massively parallel bit-serial architectures
NASA Technical Reports Server (NTRS)
Iobst, Ken
1985-01-01
Research on the Goodyear Massively Parallel Processor (MPP) suggests that high-level parallel languages are practical and can be designed with powerful new semantics that allow algorithms to be efficiently mapped to the real machines. For the MPP these semantics include parallel/associative array selection for both dense and sparse matrices, variable precision arithmetic to trade accuracy for speed, micro-pipelined train broadcast, and conditional branching at the processing element (PE) control unit level. The preliminary design of a FORTRAN-like parallel language for the MPP has been completed and is being used to write programs to perform sparse matrix array selection, min/max search, matrix multiplication, Gaussian elimination on single bit arrays and other generic algorithms. A description is given of the MPP design. Features of the system and its operation are illustrated in the form of charts and diagrams.
Development of massively parallel quantum chemistry program SMASH
Ishimura, Kazuya
2015-12-31
A massively parallel program for quantum chemistry calculations SMASH was released under the Apache License 2.0 in September 2014. The SMASH program is written in the Fortran90/95 language with MPI and OpenMP standards for parallelization. Frequently used routines, such as one- and two-electron integral calculations, are modularized to make program developments simple. The speed-up of the B3LYP energy calculation for (C{sub 150}H{sub 30}){sub 2} with the cc-pVDZ basis set (4500 basis functions) was 50,499 on 98,304 cores of the K computer.
Development of massively parallel quantum chemistry program SMASH
NASA Astrophysics Data System (ADS)
Ishimura, Kazuya
2015-12-01
A massively parallel program for quantum chemistry calculations SMASH was released under the Apache License 2.0 in September 2014. The SMASH program is written in the Fortran90/95 language with MPI and OpenMP standards for parallelization. Frequently used routines, such as one- and two-electron integral calculations, are modularized to make program developments simple. The speed-up of the B3LYP energy calculation for (C150H30)2 with the cc-pVDZ basis set (4500 basis functions) was 50,499 on 98,304 cores of the K computer.
Computational fluid dynamics on a massively parallel computer
NASA Technical Reports Server (NTRS)
Jespersen, Dennis C.; Levit, Creon
1989-01-01
A finite difference code was implemented for the compressible Navier-Stokes equations on the Connection Machine, a massively parallel computer. The code is based on the ARC2D/ARC3D program and uses the implicit factored algorithm of Beam and Warming. The codes uses odd-even elimination to solve linear systems. Timings and computation rates are given for the code, and a comparison is made with a Cray XMP.
MIMD massively parallel methods for engineering and science problems
Camp, W.J.; Plimpton, S.J.
1993-08-01
MIMD massively parallel computers promise unique power and flexibility for engineering and scientific simulations. In this paper we review the development of a number of software methods and algorithms for scientific and engineering problems which are helping to realize that promise. We discuss new domain decomposition, load balancing, data layout and communications methods applicable to simulations in a broad range of technical field including signal processing, multi-dimensional structural and fluid mechanics, materials science, and chemical and biological systems.
TSE computers - A means for massively parallel computations
NASA Technical Reports Server (NTRS)
Strong, J. P., III
1976-01-01
A description is presented of hardware concepts for building a massively parallel processing system for two-dimensional data. The processing system is to use logic arrays of 128 x 128 elements which perform over 16 thousand operations simultaneously. Attention is given to image data, logic arrays, basic image logic functions, a prototype negator, an interleaver device, image logic circuits, and an image memory circuit.
Massively parallel Wang Landau sampling on multiple GPUs
Yin, Junqi; Landau, D. P.
2012-01-01
Wang Landau sampling is implemented on the Graphics Processing Unit (GPU) with the Compute Unified Device Architecture (CUDA). Performances on three different GPU cards, including the new generation Fermi architecture card, are compared with that on a Central Processing Unit (CPU). The parameters for massively parallel Wang Landau sampling are tuned in order to achieve fast convergence. For simulations of the water cluster systems, we obtain an average of over 50 times speedup for a given workload.
3D seismic imaging on massively parallel computers
Womble, D.E.; Ober, C.C.; Oldfield, R.
1997-02-01
The ability to image complex geologies such as salt domes in the Gulf of Mexico and thrusts in mountainous regions is a key to reducing the risk and cost associated with oil and gas exploration. Imaging these structures, however, is computationally expensive. Datasets can be terabytes in size, and the processing time required for the multiple iterations needed to produce a velocity model can take months, even with the massively parallel computers available today. Some algorithms, such as 3D, finite-difference, prestack, depth migration remain beyond the capacity of production seismic processing. Massively parallel processors (MPPs) and algorithms research are the tools that will enable this project to provide new seismic processing capabilities to the oil and gas industry. The goals of this work are to (1) develop finite-difference algorithms for 3D, prestack, depth migration; (2) develop efficient computational approaches for seismic imaging and for processing terabyte datasets on massively parallel computers; and (3) develop a modular, portable, seismic imaging code.
The 2nd Symposium on the Frontiers of Massively Parallel Computations
NASA Technical Reports Server (NTRS)
Mills, Ronnie (Editor)
1988-01-01
Programming languages, computer graphics, neural networks, massively parallel computers, SIMD architecture, algorithms, digital terrain models, sort computation, simulation of charged particle transport on the massively parallel processor and image processing are among the topics discussed.
Requirements for supercomputing in energy research: The transition to massively parallel computing
Not Available
1993-02-01
This report discusses: The emergence of a practical path to TeraFlop computing and beyond; requirements of energy research programs at DOE; implementation: supercomputer production computing environment on massively parallel computers; and implementation: user transition to massively parallel computing.
MMS Observations of Parallel Electric Fields
NASA Astrophysics Data System (ADS)
Ergun, R.; Goodrich, K.; Wilder, F. D.; Sturner, A. P.; Holmes, J.; Stawarz, J. E.; Malaspina, D.; Usanova, M.; Torbert, R. B.; Lindqvist, P. A.; Khotyaintsev, Y. V.; Burch, J. L.; Strangeway, R. J.; Russell, C. T.; Pollock, C. J.; Giles, B. L.; Hesse, M.; Goldman, M. V.; Drake, J. F.; Phan, T.; Nakamura, R.
2015-12-01
Parallel electric fields are a necessary condition for magnetic reconnection with non-zero guide field and are ultimately accountable for topological reconfiguration of a magnetic field. Parallel electric fields also play a strong role in charged particle acceleration and turbulence. The Magnetospheric Multiscale (MMS) mission targets these three universal plasma processes. The MMS satellites have an accurate three-dimensional electric field measurement, which can identify parallel electric fields as low as 1 mV/m at four adjacent locations. We present preliminary observations of parallel electric fields from MMS and provide an early interpretation of their impact on magnetic reconnection, in particular, where the topological change occurs. We also examine the role of parallel electric fields in particle acceleration. Direct particle acceleration by parallel electric fields is well established in the auroral region. Observations of double layers in by the Van Allan Probes suggest that acceleration by parallel electric fields may be significant in energizing some populations of the radiation belts. THEMIS observations also indicate that some of the largest parallel electric fields are found in regions of strong field-aligned currents associated with turbulence, suggesting a highly non-linear dissipation mechanism. We discuss how the MMS observations extend our understanding of the role of parallel electric fields in some of the most critical processes in the magnetosphere.
The Massively Parallel Processor and its applications. [for environmental monitoring
NASA Technical Reports Server (NTRS)
Strong, J. P.; Schaefer, D. H.; Fischer, J. R.; Wallgren, K. R.; Bracken, P. A.
1979-01-01
A long-term experimental development program conducted at Goddard Space Flight Center to implement an ultrahigh-speed data processing system known as the Massively Parallel Processor (MPP) is described. The MPP is a single instruction multiple data stream computer designed to perform logical, integer, and floating point arithmetic operations on variable word length data. Information is presented on system architecture, the system configuration, the array unit architecture, individual processing units, and expected operating rates for several image processing applications (including the processing of Landsat data).
Routing performance analysis and optimization within a massively parallel computer
Archer, Charles Jens; Peters, Amanda; Pinnow, Kurt Walter; Swartz, Brent Allen
2013-04-16
An apparatus, program product and method optimize the operation of a massively parallel computer system by, in part, receiving actual performance data concerning an application executed by the plurality of interconnected nodes, and analyzing the actual performance data to identify an actual performance pattern. A desired performance pattern may be determined for the application, and an algorithm may be selected from among a plurality of algorithms stored within a memory, the algorithm being configured to achieve the desired performance pattern based on the actual performance data.
A biconjugate gradient type algorithm on massively parallel architectures
NASA Technical Reports Server (NTRS)
Freund, Roland W.; Hochbruck, Marlis
1991-01-01
The biconjugate gradient (BCG) method is the natural generalization of the classical conjugate gradient algorithm for Hermitian positive definite matrices to general non-Hermitian linear systems. Unfortunately, the original BCG algorithm is susceptible to possible breakdowns and numerical instabilities. Recently, Freund and Nachtigal have proposed a novel BCG type approach, the quasi-minimal residual method (QMR), which overcomes the problems of BCG. Here, an implementation is presented of QMR based on an s-step version of the nonsymmetric look-ahead Lanczos algorithm. The main feature of the s-step Lanczos algorithm is that, in general, all inner products, except for one, can be computed in parallel at the end of each block; this is unlike the other standard Lanczos process where inner products are generated sequentially. The resulting implementation of QMR is particularly attractive on massively parallel SIMD architectures, such as the Connection Machine.
Numerical computation on massively parallel hypercubes. [Connection machine
McBryan, O.A.
1986-01-01
We describe numerical computations on the Connection Machine, a massively parallel hypercube architecture with 65,536 single-bit processors and 32 Mbytes of memory. A parallel extension of COMMON LISP, provides access to the processors and network. The rich software environment is further enhanced by a powerful virtual processor capability, which extends the degree of fine-grained parallelism beyond 1,000,000. We briefly describe the hardware and indicate the principal features of the parallel programming environment. We then present implementations of SOR, multigrid and pre-conditioned conjugate gradient algorithms for solving partial differential equations on the Connection Machine. Despite the lack of floating point hardware, computation rates above 100 megaflops have been achieved in PDE solution. Virtual processors prove to be a real advantage, easing the effort of software development while improving system performance significantly. The software development effort is also facilitated by the fact that hypercube communications prove to be fast and essentially independent of distance. 29 refs., 4 figs.
Learning Quantitative Sequence-Function Relationships from Massively Parallel Experiments
NASA Astrophysics Data System (ADS)
Atwal, Gurinder S.; Kinney, Justin B.
2016-03-01
A fundamental aspect of biological information processing is the ubiquity of sequence-function relationships—functions that map the sequence of DNA, RNA, or protein to a biochemically relevant activity. Most sequence-function relationships in biology are quantitative, but only recently have experimental techniques for effectively measuring these relationships been developed. The advent of such "massively parallel" experiments presents an exciting opportunity for the concepts and methods of statistical physics to inform the study of biological systems. After reviewing these recent experimental advances, we focus on the problem of how to infer parametric models of sequence-function relationships from the data produced by these experiments. Specifically, we retrace and extend recent theoretical work showing that inference based on mutual information, not the standard likelihood-based approach, is often necessary for accurately learning the parameters of these models. Closely connected with this result is the emergence of "diffeomorphic modes"—directions in parameter space that are far less constrained by data than likelihood-based inference would suggest. Analogous to Goldstone modes in physics, diffeomorphic modes arise from an arbitrarily broken symmetry of the inference problem. An analytically tractable model of a massively parallel experiment is then described, providing an explicit demonstration of these fundamental aspects of statistical inference. This paper concludes with an outlook on the theoretical and computational challenges currently facing studies of quantitative sequence-function relationships.
The performance realities of massively parallel processors: A case study
Lubeck, O.M.; Simmons, M.L.; Wasserman, H.J.
1992-07-01
This paper presents the results of an architectural comparison of SIMD massive parallelism, as implemented in the Thinking Machines Corp. CM-2 computer, and vector or concurrent-vector processing, as implemented in the Cray Research Inc. Y-MP/8. The comparison is based primarily upon three application codes that represent Los Alamos production computing. Tests were run by porting optimized CM Fortran codes to the Y-MP, so that the same level of optimization was obtained on both machines. The results for fully-configured systems, using measured data rather than scaled data from smaller configurations, show that the Y-MP/8 is faster than the 64k CM-2 for all three codes. A simple model that accounts for the relative characteristic computational speeds of the two machines, and reduction in overall CM-2 performance due to communication or SIMD conditional execution, is included. The model predicts the performance of two codes well, but fails for the third code, because the proportion of communications in this code is very high. Other factors, such as memory bandwidth and compiler effects, are also discussed. Finally, the paper attempts to show the equivalence of the CM-2 and Y-MP programming models, and also comments on selected future massively parallel processor designs.
Comparison of massively parallel hand-print segmenters
Wilkinson, R.A.; Garris, M.D.
1992-09-01
NIST has developed a massively parallel hand-print recognition system that allows components to be interchanged. Using this system, three different character segmentation algorithms have been developed and studied. They are blob coloring, histogramming, and a hybrid of the two. The blob coloring method uses connected components to isolate characters. The histogramming method locates linear spaces, which may be slanted, to segment characters. The hybrid method is an augmented histogramming method that incorporates statistically adaptive rules to decide when a histogrammed item is too large and applies blob coloring to further segment the difficult item. The hardware configuration is a serial host computer with a 1024 processor Single Instruction Multiple Data (SIMD) machine attached to it. The data used in this comparison is 'NIST Special Database 1' which contains 2100 forms from different writers where each form contains 130 digit characters distributed across 28 fields. This gives a potential 273,000 characters to be segmented. Running the massively parallel system across the 2100 forms, blob coloring required 2.1 seconds per form with an accuracy of 97.5%, histogramming required 14.4 seconds with an accuracy of 95.3%, and the hybrid method required 13.2 seconds with an accuracy of 95.4%. The results of this comparison show that the blob coloring method on a SIMD architecture is superior.
Transmissive Nanohole Arrays for Massively-Parallel Optical Biosensing
2015-01-01
A high-throughput optical biosensing technique is proposed and demonstrated. This hybrid technique combines optical transmission of nanoholes with colorimetric silver staining. The size and spacing of the nanoholes are chosen so that individual nanoholes can be independently resolved in massive parallel using an ordinary transmission optical microscope, and, in place of determining a spectral shift, the brightness of each nanohole is recorded to greatly simplify the readout. Each nanohole then acts as an independent sensor, and the blocking of nanohole optical transmission by enzymatic silver staining defines the specific detection of a biological agent. Nearly 10000 nanoholes can be simultaneously monitored under the field of view of a typical microscope. As an initial proof of concept, biotinylated lysozyme (biotin-HEL) was used as a model analyte, giving a detection limit as low as 0.1 ng/mL. PMID:25530982
Optimal evaluation of array expressions on massively parallel machines
NASA Technical Reports Server (NTRS)
Chatterjee, Siddhartha; Gilbert, John R.; Schreiber, Robert; Teng, Shang-Hua
1992-01-01
We investigate the problem of evaluating FORTRAN 90 style array expressions on massively parallel distributed-memory machines. On such machines, an elementwise operation can be performed in constant time for arrays whose corresponding elements are in the same processor. If the arrays are not aligned in this manner, the cost of aligning them is part of the cost of evaluating the expression. The choice of where to perform the operation then affects this cost. We present algorithms based on dynamic programming to solve this problem efficiently for a wide variety of interconnection schemes, including multidimensional grids and rings, hypercubes, and fat-trees. We also consider expressions containing operations that change the shape of the arrays, and show that our approach extends naturally to handle this case.
Applications of massively parallel computers in telemetry processing
NASA Technical Reports Server (NTRS)
El-Ghazawi, Tarek A.; Pritchard, Jim; Knoble, Gordon
1994-01-01
Telemetry processing refers to the reconstruction of full resolution raw instrumentation data with artifacts, of space and ground recording and transmission, removed. Being the first processing phase of satellite data, this process is also referred to as level-zero processing. This study is aimed at investigating the use of massively parallel computing technology in providing level-zero processing to spaceflights that adhere to the recommendations of the Consultative Committee on Space Data Systems (CCSDS). The workload characteristics, of level-zero processing, are used to identify processing requirements in high-performance computing systems. An example of level-zero functions on a SIMD MPP, such as the MasPar, is discussed. The requirements in this paper are based in part on the Earth Observing System (EOS) Data and Operation System (EDOS).
A Computational Fluid Dynamics Algorithm on a Massively Parallel Computer
NASA Technical Reports Server (NTRS)
Jespersen, Dennis C.; Levit, Creon
1989-01-01
The discipline of computational fluid dynamics is demanding ever-increasing computational power to deal with complex fluid flow problems. We investigate the performance of a finite-difference computational fluid dynamics algorithm on a massively parallel computer, the Connection Machine. Of special interest is an implicit time-stepping algorithm; to obtain maximum performance from the Connection Machine, it is necessary to use a nonstandard algorithm to solve the linear systems that arise in the implicit algorithm. We find that the Connection Machine ran achieve very high computation rates on both explicit and implicit algorithms. The performance of the Connection Machine puts it in the same class as today's most powerful conventional supercomputers.
MPSim: A Massively Parallel General Simulation Program for Materials
NASA Astrophysics Data System (ADS)
Iotov, Mihail; Gao, Guanghua; Vaidehi, Nagarajan; Cagin, Tahir; Goddard, William A., III
1997-08-01
In this talk, we describe a general purpose Massively Parallel Simulation (MPSim) program used for computational materials science and life sciences. We also will present scaling aspects of the program along with several case studies. The program incorporates highly efficient CMM method to accurately calculate the interactions. For studying bulk materials, the program uses the Reduced CMM to account for infinite range sums. The software embodies various advanced molecular dynamics algorithms, energy and structure optimization techniques with a set of analysis tools suitable for large scale structures. The applications using the program range amorphous polymers, liquid-polymer interfaces, large viruses, million atom clusters, surfaces, gas diffusion in polymers. Program is originally developed on KSR in an object oriented fashion and is ported to SGI-PC, and HP-Examplar. Message Passing version is originally implemented on Intel Paragon using NX, then MPI and later tested on Cray T3D, and IBM SP2 platforms.
Beam dynamics calculations and particle tracking using massively parallel processors
Ryne, R.D.; Habib, S.
1995-12-31
During the past decade massively parallel processors (MPPs) have slowly gained acceptance within the scientific community. At present these machines typically contain a few hundred to one thousand off-the-shelf microprocessors and a total memory of up to 32 GBytes. The potential performance of these machines is illustrated by the fact that a month long job on a high end workstation might require only a few hours on an MPP. The acceptance of MPPs has been slow for a variety of reasons. For example, some algorithms are not easily parallelizable. Also, in the past these machines were difficult to program. But in recent years the development of Fortran-like languages such as CM Fortran and High Performance Fortran have made MPPs much easier to use. In the following we will describe how MPPs can be used for beam dynamics calculations and long term particle tracking.
Development of a massively parallel parachute performance prediction code
Peterson, C.W.; Strickland, J.H.; Wolfe, W.P.; Sundberg, W.D.; McBride, D.D.
1997-04-01
The Department of Energy has given Sandia full responsibility for the complete life cycle (cradle to grave) of all nuclear weapon parachutes. Sandia National Laboratories is initiating development of a complete numerical simulation of parachute performance, beginning with parachute deployment and continuing through inflation and steady state descent. The purpose of the parachute performance code is to predict the performance of stockpile weapon parachutes as these parachutes continue to age well beyond their intended service life. A new massively parallel computer will provide unprecedented speed and memory for solving this complex problem, and new software will be written to treat the coupled fluid, structure and trajectory calculations as part of a single code. Verification and validation experiments have been proposed to provide the necessary confidence in the computations.
Massively parallel high-order combinatorial genetics in human cells
Wong, Alan S L; Choi, Gigi C G; Cheng, Allen A; Purcell, Oliver; Lu, Timothy K
2016-01-01
The systematic functional analysis of combinatorial genetics has been limited by the throughput that can be achieved and the order of complexity that can be studied. To enable massively parallel characterization of genetic combinations in human cells, we developed a technology for rapid, scalable assembly of high-order barcoded combinatorial genetic libraries that can be quantified with high-throughput sequencing. We applied this technology, combinatorial genetics en masse (CombiGEM), to create high-coverage libraries of 1,521 two-wise and 51,770 three-wise barcoded combinations of 39 human microRNA (miRNA) precursors. We identified miRNA combinations that synergistically sensitize drug-resistant cancer cells to chemotherapy and/or inhibit cancer cell proliferation, providing insights into complex miRNA networks. More broadly, our method will enable high-throughput profiling of multifactorial genetic combinations that regulate phenotypes of relevance to biomedicine, biotechnology and basic science. PMID:26280411
Integration of IR focal plane arrays with massively parallel processor
NASA Astrophysics Data System (ADS)
Esfandiari, P.; Koskey, P.; Vaccaro, K.; Buchwald, W.; Clark, F.; Krejca, B.; Rekeczky, C.; Zarandy, A.
2008-04-01
The intent of this investigation is to replace the low fill factor visible sensor of a Cellular Neural Network (CNN) processor with an InGaAs Focal Plane Array (FPA) using both bump bonding and epitaxial layer transfer techniques for use in the Ballistic Missile Defense System (BMDS) interceptor seekers. The goal is to fabricate a massively parallel digital processor with a local as well as a global interconnect architecture. Currently, this unique CNN processor is capable of processing a target scene in excess of 10,000 frames per second with its visible sensor. What makes the CNN processor so unique is that each processing element includes memory, local data storage, local and global communication devices and a visible sensor supported by a programmable analog or digital computer program.
Efficient Identification of Assembly Neurons within Massively Parallel Spike Trains
Berger, Denise; Borgelt, Christian; Louis, Sebastien; Morrison, Abigail; Grün, Sonja
2010-01-01
The chance of detecting assembly activity is expected to increase if the spiking activities of large numbers of neurons are recorded simultaneously. Although such massively parallel recordings are now becoming available, methods able to analyze such data for spike correlation are still rare, as a combinatorial explosion often makes it infeasible to extend methods developed for smaller data sets. By evaluating pattern complexity distributions the existence of correlated groups can be detected, but their member neurons cannot be identified. In this contribution, we present approaches to actually identify the individual neurons involved in assemblies. Our results may complement other methods and also provide a way to reduce data sets to the “relevant” neurons, thus allowing us to carry out a refined analysis of the detailed correlation structure due to reduced computation time. PMID:19809521
Massively Parallel Simulations of Diffusion in Dense Polymeric Structures
Faulon, Jean-Loup, Wilcox, R.T. , Hobbs, J.D. , Ford, D.M.
1997-11-01
An original computational technique to generate close-to-equilibrium dense polymeric structures is proposed. Diffusion of small gases are studied on the equilibrated structures using massively parallel molecular dynamics simulations running on the Intel Teraflops (9216 Pentium Pro processors) and Intel Paragon(1840 processors). Compared to the current state-of-the-art equilibration methods this new technique appears to be faster by some orders of magnitude.The main advantage of the technique is that one can circumvent the bottlenecks in configuration space that inhibit relaxation in molecular dynamics simulations. The technique is based on the fact that tetravalent atoms (such as carbon and silicon) fit in the center of a regular tetrahedron and that regular tetrahedrons can be used to mesh the three-dimensional space. Thus, the problem of polymer equilibration described by continuous equations in molecular dynamics is reduced to a discrete problem where solutions are approximated by simple algorithms. Practical modeling applications include the constructing of butyl rubber and ethylene-propylene-dimer-monomer (EPDM) models for oxygen and water diffusion calculations. Butyl and EPDM are used in O-ring systems and serve as sealing joints in many manufactured objects. Diffusion coefficients of small gases have been measured experimentally on both polymeric systems, and in general the diffusion coefficients in EPDM are an order of magnitude larger than in butyl. In order to better understand the diffusion phenomena, 10, 000 atoms models were generated and equilibrated for butyl and EPDM. The models were submitted to a massively parallel molecular dynamics simulation to monitor the trajectories of the diffusing species.
Particle simulation of plasmas on the massively parallel processor
NASA Technical Reports Server (NTRS)
Gledhill, I. M. A.; Storey, L. R. O.
1987-01-01
Particle simulations, in which collective phenomena in plasmas are studied by following the self consistent motions of many discrete particles, involve several highly repetitive sets of calculations that are readily adaptable to SIMD parallel processing. A fully electromagnetic, relativistic plasma simulation for the massively parallel processor is described. The particle motions are followed in 2 1/2 dimensions on a 128 x 128 grid, with periodic boundary conditions. The two dimensional simulation space is mapped directly onto the processor network; a Fast Fourier Transform is used to solve the field equations. Particle data are stored according to an Eulerian scheme, i.e., the information associated with each particle is moved from one local memory to another as the particle moves across the spatial grid. The method is applied to the study of the nonlinear development of the whistler instability in a magnetospheric plasma model, with an anisotropic electron temperature. The wave distribution function is included as a new diagnostic to allow simulation results to be compared with satellite observations.
Massively parallel simulations of multiphase flows using Lattice Boltzmann methods
NASA Astrophysics Data System (ADS)
Ahrenholz, Benjamin
2010-03-01
In the last two decades the lattice Boltzmann method (LBM) has matured as an alternative and efficient numerical scheme for the simulation of fluid flows and transport problems. Unlike conventional numerical schemes based on discretizations of macroscopic continuum equations, the LBM is based on microscopic models and mesoscopic kinetic equations. The fundamental idea of the LBM is to construct simplified kinetic models that incorporate the essential physics of microscopic or mesoscopic processes so that the macroscopic averaged properties obey the desired macroscopic equations. Especially applications involving interfacial dynamics, complex and/or changing boundaries and complicated constitutive relationships which can be derived from a microscopic picture are suitable for the LBM. In this talk a modified and optimized version of a Gunstensen color model is presented to describe the dynamics of the fluid/fluid interface where the flow field is based on a multi-relaxation-time model. Based on that modeling approach validation studies of contact line motion are shown. Due to the fact that the LB method generally needs only nearest neighbor information, the algorithm is an ideal candidate for parallelization. Hence, it is possible to perform efficient simulations in complex geometries at a large scale by massively parallel computations. Here, the results of drainage and imbibition (Degree of Freedom > 2E11) in natural porous media gained from microtomography methods are presented. Those fully resolved pore scale simulations are essential for a better understanding of the physical processes in porous media and therefore important for the determination of constitutive relationships.
Efficiently modeling neural networks on massively parallel computers
NASA Technical Reports Server (NTRS)
Farber, Robert M.
1993-01-01
Neural networks are a very useful tool for analyzing and modeling complex real world systems. Applying neural network simulations to real world problems generally involves large amounts of data and massive amounts of computation. To efficiently handle the computational requirements of large problems, we have implemented at Los Alamos a highly efficient neural network compiler for serial computers, vector computers, vector parallel computers, and fine grain SIMD computers such as the CM-2 connection machine. This paper describes the mapping used by the compiler to implement feed-forward backpropagation neural networks for a SIMD (Single Instruction Multiple Data) architecture parallel computer. Thinking Machines Corporation has benchmarked our code at 1.3 billion interconnects per second (approximately 3 gigaflops) on a 64,000 processor CM-2 connection machine (Singer 1990). This mapping is applicable to other SIMD computers and can be implemented on MIMD computers such as the CM-5 connection machine. Our mapping has virtually no communications overhead with the exception of the communications required for a global summation across the processors (which has a sub-linear runtime growth on the order of O(log(number of processors)). We can efficiently model very large neural networks which have many neurons and interconnects and our mapping can extend to arbitrarily large networks (within memory limitations) by merging the memory space of separate processors with fast adjacent processor interprocessor communications. This paper will consider the simulation of only feed forward neural network although this method is extendable to recurrent networks.
Massively Parallel Interrogation of Aptamer Sequence, Structure and Function
Fischer, N O; Tok, J B; Tarasow, T M
2008-02-08
Optimization of high affinity reagents is a significant bottleneck in medicine and the life sciences. The ability to synthetically create thousands of permutations of a lead high-affinity reagent and survey the properties of individual permutations in parallel could potentially relieve this bottleneck. Aptamers are single stranded oligonucleotides affinity reagents isolated by in vitro selection processes and as a class have been shown to bind a wide variety of target molecules. Methodology/Principal Findings. High density DNA microarray technology was used to synthesize, in situ, arrays of approximately 3,900 aptamer sequence permutations in triplicate. These sequences were interrogated on-chip for their ability to bind the fluorescently-labeled cognate target, immunoglobulin E, resulting in the parallel execution of thousands of experiments. Fluorescence intensity at each array feature was well resolved and shown to be a function of the sequence present. The data demonstrated high intra- and interchip correlation between the same features as well as among the sequence triplicates within a single array. Consistent with aptamer mediated IgE binding, fluorescence intensity correlated strongly with specific aptamer sequences and the concentration of IgE applied to the array. The massively parallel sequence-function analyses provided by this approach confirmed the importance of a consensus sequence found in all 21 of the original IgE aptamer sequences and support a common stem:loop structure as being the secondary structure underlying IgE binding. The microarray application, data and results presented illustrate an efficient, high information content approach to optimizing aptamer function. It also provides a foundation from which to better understand and manipulate this important class of high affinity biomolecules.
Electrical properties of seafloor massive sulfides
NASA Astrophysics Data System (ADS)
Spagnoli, Giovanni; Hannington, Mark; Bairlein, Katharina; Hördt, Andreas; Jegen, Marion; Petersen, Sven; Laurila, Tea
2016-06-01
Seafloor massive sulfide (SMS) deposits are increasingly seen as important marine metal resources for the future. A growing number of industrialized nations are involved in the surveying and sampling of such deposits by drilling. Drill ships are expensive and their availability can be limited; seabed drill rigs are a cost-effective alternative and more suitable for obtaining cores for resource evaluation. In order to achieve the objectives of resource evaluations, details are required of the geological, mineralogical, and physical properties of the polymetallic deposits and their host rocks. Electrical properties of the deposits and their ore minerals are distinct from their unmineralized host rocks. Therefore, the use of electrical methods to detect SMS while drilling and recovering drill cores could decrease the costs and accelerate offshore operations by limiting the amount of drilling in unmineralized material. This paper presents new data regarding the electrical properties of SMS cores that can be used in that assessment. Frequency-dependent complex electrical resistivity in the frequency range between 0.002 and 100 Hz was examined in order to potentially discriminate between different types of fresh rocks, alteration and mineralization. Forty mini-cores of SMS and unmineralized host rocks were tested in the laboratory, originating from different tectonic settings such as the intermediate-spreading ridges of the Galapagos and Axial Seamount, and the Pacmanus back-arc basin. The results indicate that there is a clear potential to distinguish between mineralized and non-mineralized samples, with some evidence that even different types of mineralization can be discriminated. This could be achieved using resistivity magnitude alone with appropriate rig-mounted electrical sensors. Exploiting the frequency-dependent behavior of resistivity might amplify the differences and further improve the rock characterization.
Electrical properties of seafloor massive sulfides
NASA Astrophysics Data System (ADS)
Spagnoli, Giovanni; Hannington, Mark; Bairlein, Katharina; Hördt, Andreas; Jegen, Marion; Petersen, Sven; Laurila, Tea
2016-02-01
Seafloor massive sulfide (SMS) deposits are increasingly seen as important marine metal resources for the future. A growing number of industrialized nations are involved in the surveying and sampling of such deposits by drilling. Drill ships are expensive and their availability can be limited; seabed drill rigs are a cost-effective alternative and more suitable for obtaining cores for resource evaluation. In order to achieve the objectives of resource evaluations, details are required of the geological, mineralogical, and physical properties of the polymetallic deposits and their host rocks. Electrical properties of the deposits and their ore minerals are distinct from their unmineralized host rocks. Therefore, the use of electrical methods to detect SMS while drilling and recovering drill cores could decrease the costs and accelerate offshore operations by limiting the amount of drilling in unmineralized material. This paper presents new data regarding the electrical properties of SMS cores that can be used in that assessment. Frequency-dependent complex electrical resistivity in the frequency range between 0.002 and 100 Hz was examined in order to potentially discriminate between different types of fresh rocks, alteration and mineralization. Forty mini-cores of SMS and unmineralized host rocks were tested in the laboratory, originating from different tectonic settings such as the intermediate-spreading ridges of the Galapagos and Axial Seamount, and the Pacmanus back-arc basin. The results indicate that there is a clear potential to distinguish between mineralized and non-mineralized samples, with some evidence that even different types of mineralization can be discriminated. This could be achieved using resistivity magnitude alone with appropriate rig-mounted electrical sensors. Exploiting the frequency-dependent behavior of resistivity might amplify the differences and further improve the rock characterization.
Analysis of composite ablators using massively parallel computation
NASA Technical Reports Server (NTRS)
Shia, David
1995-01-01
In this work, the feasibility of using massively parallel computation to study the response of ablative materials is investigated. Explicit and implicit finite difference methods are used on a massively parallel computer, the Thinking Machines CM-5. The governing equations are a set of nonlinear partial differential equations. The governing equations are developed for three sample problems: (1) transpiration cooling, (2) ablative composite plate, and (3) restrained thermal growth testing. The transpiration cooling problem is solved using a solution scheme based solely on the explicit finite difference method. The results are compared with available analytical steady-state through-thickness temperature and pressure distributions and good agreement between the numerical and analytical solutions is found. It is also found that a solution scheme based on the explicit finite difference method has the following advantages: incorporates complex physics easily, results in a simple algorithm, and is easily parallelizable. However, a solution scheme of this kind needs very small time steps to maintain stability. A solution scheme based on the implicit finite difference method has the advantage that it does not require very small times steps to maintain stability. However, this kind of solution scheme has the disadvantages that complex physics cannot be easily incorporated into the algorithm and that the solution scheme is difficult to parallelize. A hybrid solution scheme is then developed to combine the strengths of the explicit and implicit finite difference methods and minimize their weaknesses. This is achieved by identifying the critical time scale associated with the governing equations and applying the appropriate finite difference method according to this critical time scale. The hybrid solution scheme is then applied to the ablative composite plate and restrained thermal growth problems. The gas storage term is included in the explicit pressure calculation of both
Massively Parallel Processing for Fast and Accurate Stamping Simulations
NASA Astrophysics Data System (ADS)
Gress, Jeffrey J.; Xu, Siguang; Joshi, Ramesh; Wang, Chuan-tao; Paul, Sabu
2005-08-01
The competitive automotive market drives automotive manufacturers to speed up the vehicle development cycles and reduce the lead-time. Fast tooling development is one of the key areas to support fast and short vehicle development programs (VDP). In the past ten years, the stamping simulation has become the most effective validation tool in predicting and resolving all potential formability and quality problems before the dies are physically made. The stamping simulation and formability analysis has become an critical business segment in GM math-based die engineering process. As the simulation becomes as one of the major production tools in engineering factory, the simulation speed and accuracy are the two of the most important measures for stamping simulation technology. The speed and time-in-system of forming analysis becomes an even more critical to support the fast VDP and tooling readiness. Since 1997, General Motors Die Center has been working jointly with our software vendor to develop and implement a parallel version of simulation software for mass production analysis applications. By 2001, this technology was matured in the form of distributed memory processing (DMP) of draw die simulations in a networked distributed memory computing environment. In 2004, this technology was refined to massively parallel processing (MPP) and extended to line die forming analysis (draw, trim, flange, and associated spring-back) running on a dedicated computing environment. The evolution of this technology and the insight gained through the implementation of DM0P/MPP technology as well as performance benchmarks are discussed in this publication.
Cloud identification using genetic algorithms and massively parallel computation
NASA Technical Reports Server (NTRS)
Buckles, Bill P.; Petry, Frederick E.
1996-01-01
As a Guest Computational Investigator under the NASA administered component of the High Performance Computing and Communication Program, we implemented a massively parallel genetic algorithm on the MasPar SIMD computer. Experiments were conducted using Earth Science data in the domains of meteorology and oceanography. Results obtained in these domains are competitive with, and in most cases better than, similar problems solved using other methods. In the meteorological domain, we chose to identify clouds using AVHRR spectral data. Four cloud speciations were used although most researchers settle for three. Results were remarkedly consistent across all tests (91% accuracy). Refinements of this method may lead to more timely and complete information for Global Circulation Models (GCMS) that are prevalent in weather forecasting and global environment studies. In the oceanographic domain, we chose to identify ocean currents from a spectrometer having similar characteristics to AVHRR. Here the results were mixed (60% to 80% accuracy). Given that one is willing to run the experiment several times (say 10), then it is acceptable to claim the higher accuracy rating. This problem has never been successfully automated. Therefore, these results are encouraging even though less impressive than the cloud experiment. Successful conclusion of an automated ocean current detection system would impact coastal fishing, naval tactics, and the study of micro-climates. Finally we contributed to the basic knowledge of GA (genetic algorithm) behavior in parallel environments. We developed better knowledge of the use of subpopulations in the context of shared breeding pools and the migration of individuals. Rigorous experiments were conducted based on quantifiable performance criteria. While much of the work confirmed current wisdom, for the first time we were able to submit conclusive evidence. The software developed under this grant was placed in the public domain. An extensive user
A high-plex PCR approach for massively parallel sequencing.
Nguyen-Dumont, Tú; Pope, Bernard J; Hammet, Fleur; Southey, Melissa C; Park, Daniel J
2013-08-01
Current methods for targeted massively parallel sequencing (MPS) have several drawbacks, including limited design flexibility, expense, and protocol complexity, which restrict their application to settings involving modest target size and requiring low cost and high throughput. To address this, we have developed Hi-Plex, a PCR-MPS strategy intended for high-throughput screening of multiple genomic target regions that integrates simple, automated primer design software to control product size. Featuring permissive thermocycling conditions and clamp bias reduction, our protocol is simple, cost- and time-effective, uses readily available reagents, does not require expensive instrumentation, and requires minimal optimization. In a 60-plex assay targeting the breast cancer predisposition genes PALB2 and XRCC2, we applied Hi-Plex to 100 ng LCL-derived DNA, and 100 ng and 25 ng FFPE tumor-derived DNA. Altogether, at least 86.94% of the human genome-mapped reads were on target, and 100% of targeted amplicons were represented within 25-fold of the mean. Using 25 ng FFPE-derived DNA, 95.14% of mapped reads were on-target and relative representation ranged from 10.1-fold lower to 5.8-fold higher than the mean. These results were obtained using only the initial automatically-designed primers present in equal concentration. Hi-Plex represents a powerful new approach for screening panels of genomic target regions. PMID:23931594
Wavelet-Based DFT calculations on Massively Parallel Hybrid Architectures
NASA Astrophysics Data System (ADS)
Genovese, Luigi
2011-03-01
In this contribution, we present an implementation of a full DFT code that can run on massively parallel hybrid CPU-GPU clusters. Our implementation is based on modern GPU architectures which support double-precision floating-point numbers. This DFT code, named BigDFT, is delivered within the GNU-GPL license either in a stand-alone version or integrated in the ABINIT software package. Hybrid BigDFT routines were initially ported with NVidia's CUDA language, and recently more functionalities have been added with new routines writeen within Kronos' OpenCL standard. The formalism of this code is based on Daubechies wavelets, which is a systematic real-space based basis set. As we will see in the presentation, the properties of this basis set are well suited for an extension on a GPU-accelerated environment. In addition to focusing on the implementation of the operators of the BigDFT code, this presentation also relies of the usage of the GPU resources in a complex code with different kinds of operations. A discussion on the interest of present and expected performances of Hybrid architectures computation in the framework of electronic structure calculations is also adressed.
Comparing current cluster, massively parallel, and accelerated systems
Barker, Kevin J; Davis, Kei; Hoisie, Adolfy; Kerbyson, Darren J; Pakin, Scott; Lang, Mike; Sancho Pitarch, Jose C
2010-01-01
Currently there is large architectural diversity in high perfonnance computing systems. They include 'commodity' cluster systems that optimize per-node performance for small jobs, massively parallel processors (MPPs) that optimize aggregate perfonnance for large jobs, and accelerated systems that optimize both per-node and aggregate performance but only for applications custom-designed to take advantage of such systems. Because of these dissimilarities, meaningful comparisons of achievable performance are not straightforward. In this work we utilize a methodology that combines both empirical analysis and performance modeling to compare clusters (represented by a 4,352-core IB cluster), MPPs (represented by a 147,456-core BG/P), and accelerated systems (represented by the 129,600-core Roadrunner) across a workload of four applications. Strengths of our approach include the ability to compare architectures - as opposed to specific implementations of an architecture - attribute each application's performance bottlenecks to characteristics unique to each system, and to explore performance scenarios in advance of their availability for measurement. Our analysis illustrates that application performance is essentially unrelated to relative peak performance but that application performance can be both predicted and explained using modeling.
Investigation of reflective notching with massively parallel simulation
NASA Astrophysics Data System (ADS)
Tadros, Karim H.; Neureuther, Andrew R.; Gamelin, John K.; Guerrieri, Roberto
1990-06-01
A massively parallel simulation program TEMPEST is used to investigate the role of topography in generating reflective notching and to study the possibility of reducing effects through the introduction of special properties of resists and antireflection coating materials. The emphasis is on examining physical scattering mechanisms such as focused specular reflections resist thickness interference effects reflections from substrate grains and focusing of incident light by the resist curvature. Specular reflection from topography can focus incident radiation causing a 10-fold increase in effective exposure. Further complications such as dimples in the surface of positive resist features can result from a second reflection of focused energy by the resist/air interface. Variations in line-edge exposure due to substrate grain structure are primarily specular in nature and can become significant for grains larger than )tresi Local exposure variations due to vertical standing waves and changes in energy coupling due to changes in resist thickness are displaced laterally and are significant effects even though they are slightly less severe than vertical wave propagation theory suggests. Focusing effects due to refraction by the curved surface of the resist produce only minor changes in exposure. Increased resist contrast and resist absorption offer some improvement in reducing notching effects though minimizing substrate reflectivity is more effective. CPU time using 32 virtual nodes to simulate a 4 pm by 2 pm isolated domain with 13 bleaching steps was 30 minutes
Massively parallel support for a case-based planning system
NASA Technical Reports Server (NTRS)
Kettler, Brian P.; Hendler, James A.; Anderson, William A.
1993-01-01
Case-based planning (CBP), a kind of case-based reasoning, is a technique in which previously generated plans (cases) are stored in memory and can be reused to solve similar planning problems in the future. CBP can save considerable time over generative planning, in which a new plan is produced from scratch. CBP thus offers a potential (heuristic) mechanism for handling intractable problems. One drawback of CBP systems has been the need for a highly structured memory to reduce retrieval times. This approach requires significant domain engineering and complex memory indexing schemes to make these planners efficient. In contrast, our CBP system, CaPER, uses a massively parallel frame-based AI language (PARKA) and can do extremely fast retrieval of complex cases from a large, unindexed memory. The ability to do fast, frequent retrievals has many advantages: indexing is unnecessary; very large case bases can be used; memory can be probed in numerous alternate ways; and queries can be made at several levels, allowing more specific retrieval of stored plans that better fit the target problem with less adaptation. In this paper we describe CaPER's case retrieval techniques and some experimental results showing its good performance, even on large case bases.
Massively parallel processor networks with optical express channels
Deri, R.J.; Brooks, E.D. III; Haigh, R.E.; DeGroot, A.J.
1999-08-24
An optical method for separating and routing local and express channel data comprises interconnecting the nodes in a network with fiber optic cables. A single fiber optic cable carries both express channel traffic and local channel traffic, e.g., in a massively parallel processor (MPP) network. Express channel traffic is placed on, or filtered from, the fiber optic cable at a light frequency or a color different from that of the local channel traffic. The express channel traffic is thus placed on a light carrier that skips over the local intermediate nodes one-by-one by reflecting off of selective mirrors placed at each local node. The local-channel-traffic light carriers pass through the selective mirrors and are not reflected. A single fiber optic cable can thus be threaded throughout a three-dimensional matrix of nodes with the x,y,z directions of propagation encoded by the color of the respective light carriers for both local and express channel traffic. Thus frequency division multiple access is used to hierarchically separate the local and express channels to eliminate the bucket brigade latencies that would otherwise result if the express traffic had to hop between every local node to reach its ultimate destination. 3 figs.
Massively parallel processor networks with optical express channels
Deri, Robert J.; Brooks, III, Eugene D.; Haigh, Ronald E.; DeGroot, Anthony J.
1999-01-01
An optical method for separating and routing local and express channel data comprises interconnecting the nodes in a network with fiber optic cables. A single fiber optic cable carries both express channel traffic and local channel traffic, e.g., in a massively parallel processor (MPP) network. Express channel traffic is placed on, or filtered from, the fiber optic cable at a light frequency or a color different from that of the local channel traffic. The express channel traffic is thus placed on a light carrier that skips over the local intermediate nodes one-by-one by reflecting off of selective mirrors placed at each local node. The local-channel-traffic light carriers pass through the selective mirrors and are not reflected. A single fiber optic cable can thus be threaded throughout a three-dimensional matrix of nodes with the x,y,z directions of propagation encoded by the color of the respective light carriers for both local and express channel traffic. Thus frequency division multiple access is used to hierarchically separate the local and express channels to eliminate the bucket brigade latencies that would otherwise result if the express traffic had to hop between every local node to reach its ultimate destination.
Three-dimensional radiative transfer on a massively parallel computer
NASA Astrophysics Data System (ADS)
Vath, H. M.
1994-04-01
We perform 3D radiative transfer calculations in non-local thermodynamic equilibrium (NLTE) in the simple two-level atom approximation on the Mas-Par MP-1, which contains 8192 processors and is a single instruction multiple data (SIMD) machine, an example of the new generation of massively parallel computers. On such a machine, all processors execute the same command at a given time, but on different data. To make radiative transfer calculations efficient, we must re-consider the numerical methods and storage of data. To solve the transfer equation, we adopt the short characteristic method and examine different acceleration methods to obtain the source function. We use the ALI method and test local and non-local operators. Furthermore, we compare the Ng and the orthomin methods of acceleration. We also investigate the use of multi-grid methods to get fast solutions for the NLTE case. In order to test these numerical methods, we apply them to two problems with and without periodic boundary conditions.
PFLOTRAN: Recent Developments Facilitating Massively-Parallel Reactive Biogeochemical Transport
NASA Astrophysics Data System (ADS)
Hammond, G. E.
2015-12-01
With the recent shift towards modeling carbon and nitrogen cycling in support of climate-related initiatives, emphasis has been placed on incorporating increasingly mechanistic biogeochemistry within Earth system models to more accurately predict the response of terrestrial processes to natural and anthropogenic climate cycles. PFLOTRAN is an open-source subsurface code that is specialized for simulating multiphase flow and multicomponent biogeochemical transport on supercomputers. The object-oriented code was designed with modularity in mind and has been coupled with several third-party simulators (e.g. CLM to simulate land surface processes and E4D for coupled hydrogeophysical inversion). Central to PFLOTRAN's capabilities is its ability to simulate tightly-coupled reactive transport processes. This presentation focuses on recent enhancements to the code that enable the solution of large parameterized biogeochemical reaction networks with numerous chemical species. PFLOTRAN's "reaction sandbox" is described, which facilitates the implementation of user-defined reaction networks without the need for a comprehensive understanding of PFLOTRAN software infrastructure. The reaction sandbox is written in modern Fortran (2003-2008) and leverages encapsulation, inheritance, and polymorphism to provide the researcher with a flexible workspace for prototyping reactions within a massively parallel flow and transport simulation framework. As these prototypical reactions mature into well-accepted implementations, they can be incorporated into PFLOTRAN as native biogeochemistry capability. Users of the reaction sandbox are encouraged to upload their source code to PFLOTRAN's main source code repository, including the addition of simple regression tests to better ensure the long-term code compatibility and validity of simulation results.
Payne, J.L.; Hassan, B.
1998-09-01
Massively parallel computers have enabled the analyst to solve complicated flow fields (turbulent, chemically reacting) that were previously intractable. Calculations are presented using a massively parallel CFD code called SACCARA (Sandia Advanced Code for Compressible Aerothermodynamics Research and Analysis) currently under development at Sandia National Laboratories as part of the Department of Energy (DOE) Accelerated Strategic Computing Initiative (ASCI). Computations were made on a generic reentry vehicle in a hypersonic flowfield utilizing three different distributed parallel computers to assess the parallel efficiency of the code with increasing numbers of processors. The parallel efficiencies for the SACCARA code will be presented for cases using 1, 150, 100 and 500 processors. Computations were also made on a subsonic/transonic vehicle using both 236 and 521 processors on a grid containing approximately 14.7 million grid points. Ongoing and future plans to implement a parallel overset grid capability and couple SACCARA with other mechanics codes in a massively parallel environment are discussed.
Three-Dimensional Radiative Transfer on a Massively Parallel Computer.
NASA Astrophysics Data System (ADS)
Vath, Horst Michael
1994-01-01
We perform three-dimensional radiative transfer calculations on the MasPar MP-1, which contains 8192 processors and is a single instruction multiple data (SIMD) machine, an example of the new generation of massively parallel computers. To make radiative transfer calculations efficient, we must re-consider the numerical methods and methods of storage of data that have been used with serial machines. We developed a numerical code which efficiently calculates images and spectra of astrophysical systems as seen from different viewing directions and at different wavelengths. We use this code to examine a number of different astrophysical systems. First we image the HI distribution of model galaxies. Then we investigate the galaxy NGC 5055, which displays a radial asymmetry in its optical appearance. This can be explained by the presence of dust in the outer HI disk far beyond the optical disk. As the formation of dust is connected to the presence of stars, the existence of dust in outer regions of this galaxy could have consequences for star formation at a time when this galaxy was just forming. Next we use the code for polarized radiative transfer. We first discuss the numerical computation of the required cyclotron opacities and use them to calculate spectra of AM Her systems, binaries containing accreting magnetic white dwarfs. Then we obtain spectra of an extended polar cap. Previous calculations did not consider the three -dimensional extension of the shock. We find that this results in a significant underestimate of the radiation emitted in the shock. Next we calculate the spectrum of the intermediate polar RE 0751+14. For this system we obtain a magnetic field of ~10 MG, which has consequences for the evolution of intermediate polars. Finally we perform 3D radiative transfer in NLTE in the two-level atom approximation. To solve the transfer equation in this case, we adapt the short characteristic method and examine different acceleration methods to obtain the
3-D readout-electronics packaging for high-bandwidth massively paralleled imager
Kwiatkowski, Kris; Lyke, James
2007-12-18
Dense, massively parallel signal processing electronics are co-packaged behind associated sensor pixels. Microchips containing a linear or bilinear arrangement of photo-sensors, together with associated complex electronics, are integrated into a simple 3-D structure (a "mirror cube"). An array of photo-sensitive cells are disposed on a stacked CMOS chip's surface at a 45.degree. angle from light reflecting mirror surfaces formed on a neighboring CMOS chip surface. Image processing electronics are held within the stacked CMOS chip layers. Electrical connections couple each of said stacked CMOS chip layers and a distribution grid, the connections for distributing power and signals to components associated with each stacked CSMO chip layer.
SWAMP+: multiple subsequence alignment using associative massive parallelism
Steinfadt, Shannon Irene; Baker, Johnnie W
2010-10-18
A new parallel algorithm SWAMP+ incorporates the Smith-Waterman sequence alignment on an associative parallel model known as ASC. It is a highly sensitive parallel approach that expands traditional pairwise sequence alignment. This is the first parallel algorithm to provide multiple non-overlapping, non-intersecting subsequence alignments with the accuracy of Smith-Waterman. The efficient algorithm provides multiple alignments similar to BLAST while creating a better workflow for the end users. The parallel portions of the code run in O(m+n) time using m processors. When m = n, the algorithmic analysis becomes O(n) with a coefficient of two, yielding a linear speedup. Implementation of the algorithm on the SIMD ClearSpeed CSX620 confirms this theoretical linear speedup with real timings.
QCD on the Massively Parallel Computer AP1000
NASA Astrophysics Data System (ADS)
Akemi, K.; Fujisaki, M.; Okuda, M.; Tago, Y.; Hashimoto, T.; Hioki, S.; Miyamura, O.; Takaishi, T.; Nakamura, A.; de Forcrand, Ph.; Hege, C.; Stamatescu, I. O.
We present the QCD-TARO program of calculations which uses the parallel computer AP1000 of Fujitsu. We discuss the results on scaling, correlation times and hadronic spectrum, some aspects of the implementation and the future prospects.
A development plan for a massively parallel version of the hydrocode CTH
Robinson, A.C.; Fang, E.; Holdridge, D.; McGlaun, J.M.
1990-07-01
Massively parallel computers and computer networks are beginning to appear as an integral part of the scientific computing workplace. This report documents the goals and the corresponding development plan of the massively parallel project of Departments 1530 and 1420. The main goal of the project is to provide a clear understanding of the issues and difficulties involved in bringing the current production hydrocode CTH to the state of being portable to a number of currently available parallel computing architectures. In the process of this research, various working versions of the code will be produced. 6 refs., 6 figs.
Numerical analysis of electrical defibrillation. The parallel approach.
Ng, K T; Hutchinson, S A; Gao, S
1995-01-01
Numerical modeling offers a viable tool for studying electrical defibrillation, allowing the behavior of field quantities to be observed easily as the different system parameters are varied. One numerical technique, namely the finite-element method, has been found particularly effective for modeling complex thoracic anatomies. However, an accurate finite-element model of the thorax often requires a large number of elements and nodes, leading to a large set of equations that cannot be solved effectively with the computational power of conventional computers. This is especially true if many finite-element solutions need to be achieved within a reasonable time period (eg, electrode configuration optimization). In this study, the use of massively parallel computers to provide the memory and reduction in solution time for solving these large finite-element problems is discussed. Both the uniform and unstructured grid approaches are considered. Algorithms that allow efficient mapping of uniform and unstructured grids to data-parallel and message-passing parallel computers are discussed. An automatic iterative procedure for electrode configuration optimization is presented. The procedure is based on the minimization of an objective function using the parallel direct search technique. Computational performance results are presented together with simulation results. PMID:8656104
A Massively Parallel Adaptive Fast Multipole Method on Heterogeneous Architectures
Lashuk, Ilya; Chandramowlishwaran, Aparna; Langston, Harper; Nguyen, Tuan-Anh; Sampath, Rahul S; Shringarpure, Aashay; Vuduc, Richard; Ying, Lexing; Zorin, Denis; Biros, George
2012-01-01
We describe a parallel fast multipole method (FMM) for highly nonuniform distributions of particles. We employ both distributed memory parallelism (via MPI) and shared memory parallelism (via OpenMP and GPU acceleration) to rapidly evaluate two-body nonoscillatory potentials in three dimensions on heterogeneous high performance computing architectures. We have performed scalability tests with up to 30 billion particles on 196,608 cores on the AMD/CRAY-based Jaguar system at ORNL. On a GPU-enabled system (NSF's Keeneland at Georgia Tech/ORNL), we observed 30x speedup over a single core CPU and 7x speedup over a multicore CPU implementation. By combining GPUs with MPI, we achieve less than 10 ns/particle and six digits of accuracy for a run with 48 million nonuniformly distributed particles on 192 GPUs.
Massively parallel switch-level simulation: A feasibility study
Kravitz, S.A.
1989-01-01
This thesis addresses the feasibility of mapping the COSMOS switch-level simulator onto computers with thousands of simple processors. COSMOS Preprocesses transistor networks into equivalent Boolean behavioral models, capturing the switch-level behavior of a circuit in a set of Boolean formulas. The author shows that thousand-fold parallelism exists in the formulas derived by COSMOS for some actual circuits. He exposes this parallelism by eliminating the event list from the simulator, and he demonstrates that this represents an attractive tradeoff given sufficient parallelism in the circuit model. To investigate the feasibility of this approach, he has developed a prototype implementation of the COSMOS simulator on a 32k processor Connection Machine.
High density packaging and interconnect of massively parallel image processors
NASA Technical Reports Server (NTRS)
Carson, John C.; Indin, Ronald J.
1991-01-01
This paper presents conceptual designs for high density packaging of parallel processing systems. The systems fall into two categories: global memory systems where many processors are packaged into a stack, and distributed memory systems where a single processor and many memory chips are packaged into a stack. Thermal behavior and performance are discussed.
Molecular simulation of rheological properties using massively parallel supercomputers
Bhupathiraju, R.K.; Cui, S.T.; Gupta, S.A.; Cummings, P.T.; Cochran, H.D.
1996-11-01
Advances in parallel supercomputing now make possible molecular-based engineering and science calculations that will soon revolutionize many technologies, such as those involving polymers and those involving aqueous electrolytes. We have developed a suite of message-passing codes for classical molecular simulation of such complex fluids and amorphous materials and have completed a number of demonstration calculations of problems of scientific and technological importance with each. In this paper, we will focus on the molecular simulation of rheological properties, particularly viscosity, of simple and complex fluids using parallel implementations of non-equilibrium molecular dynamics. Such calculations represent significant challenges computationally because, in order to reduce the thermal noise in the calculated properties within acceptable limits, large systems and/or long simulated times are required.
Casting pearls ballistically: Efficient massively parallel simulation of particle deposition
Lubachevsky, B.D.; Privman, V.; Roy, S.C.
1996-06-01
We simulate ballistic particle deposition wherein a large number of spherical particles are {open_quotes}cast{close_quotes} vertically over a planar horizontal surface. Upon first contact (with the surface or with a previously deposited particle) each particle stops. This model helps material scientists to study the adsorption and sediment formation. The model is sequential, with particles deposited one by one. We have found an equivalent formulation using a continuous time random process and we simulate the latter in parallel using a method similar to the one previously employed for simulating Ising spins. We augment the parallel algorithm for simulating Ising spins with several techniques aimed at the increase of efficiency of producing the particle configuration and statistics collection. Some of these techniques are similar to earlier ones. We implement the resulting algorithm on a 16K PE MasPar MP-1 and a 4K PE MasPar MP-2. The parallel code runs on MasPar computers nearly two orders of magnitude faster than an optimized sequential code runs on a fast workstation. 17 refs., 9 figs.
Casting Pearls Ballistically: Efficient Massively Parallel Simulation of Particle Deposition
NASA Astrophysics Data System (ADS)
Lubachevsky, Boris D.; Privman, Vladimir; Roy, Subhas C.
1996-06-01
We simulate ballistic particle deposition wherein a large number of spherical particles are "cast" vertically over a planar horizontal surface. Upon first contact (with the surface or with a previously deposited particle) each particle stops. This model helps material scientists to study the adsorption and sediment formation. The model is sequential, with particles deposited one by one. We have found an equivalent formulation using a continuous time random process and we simulate the latter in parallel using a method similar to the one previously employed for simulating Ising spins. We augment the parallel algorithm for simulating Ising spins with several techniques aimed at the increase of efficiency of producing the particle configuration and statistics collection. Some of these techniques are similar to earlier ones. We implement the resulting algorithm on a 16K PE MasPar MP-1 and a 4K PE MasPar MP-2. The parallel code runs on MasPar computers nearly two orders of magnitude faster than an optimized sequential code runs on a fast workstation.
Performance effects of irregular communications patterns on massively parallel multiprocessors
NASA Technical Reports Server (NTRS)
Saltz, Joel; Petiton, Serge; Berryman, Harry; Rifkin, Adam
1991-01-01
A detailed study of the performance effects of irregular communications patterns on the CM-2 was conducted. The communications capabilities of the CM-2 were characterized under a variety of controlled conditions. In the process of carrying out the performance evaluation, extensive use was made of a parameterized synthetic mesh. In addition, timings with unstructured meshes generated for aerodynamic codes and a set of sparse matrices with banded patterns on non-zeroes were performed. This benchmarking suite stresses the communications capabilities of the CM-2 in a range of different ways. Benchmark results demonstrate that it is possible to make effective use of much of the massive concurrency available in the communications network.
Massively parallel spatial light modulation-based optical signal processing
NASA Astrophysics Data System (ADS)
Li, Yao
1993-03-01
A new optical parallel arithmetic processing scheme using a nonholographic optoelectronic content-addressable memory (CAM) was proposed. The design of a four-bit CAM-based optical carry look-ahead adder was studied. Compared with existing optoelectronic binary addition approaches, this nonholographic CAM Scheme offers a number of practical advantages, such as faster processing speed and ease of optical implementation and alignment. For an addition of numbers longer than four bits, by incorporating the previous stage's carry, a number of four-bit CLA's can be cascaded. Experimental results were also demonstrated. One paper to the Optics Letters was published.
A sweep algorithm for massively parallel simulation of circuit-switched networks
NASA Technical Reports Server (NTRS)
Gaujal, Bruno; Greenberg, Albert G.; Nicol, David M.
1992-01-01
A new massively parallel algorithm is presented for simulating large asymmetric circuit-switched networks, controlled by a randomized-routing policy that includes trunk-reservation. A single instruction multiple data (SIMD) implementation is described, and corresponding experiments on a 16384 processor MasPar parallel computer are reported. A multiple instruction multiple data (MIMD) implementation is also described, and corresponding experiments on an Intel IPSC/860 parallel computer, using 16 processors, are reported. By exploiting parallelism, our algorithm increases the possible execution rate of such complex simulations by as much as an order of magnitude.
Performance of the Wavelet Decomposition on Massively Parallel Architectures
NASA Technical Reports Server (NTRS)
El-Ghazawi, Tarek A.; LeMoigne, Jacqueline; Zukor, Dorothy (Technical Monitor)
2001-01-01
Traditionally, Fourier Transforms have been utilized for performing signal analysis and representation. But although it is straightforward to reconstruct a signal from its Fourier transform, no local description of the signal is included in its Fourier representation. To alleviate this problem, Windowed Fourier transforms and then wavelet transforms have been introduced, and it has been proven that wavelets give a better localization than traditional Fourier transforms, as well as a better division of the time- or space-frequency plane than Windowed Fourier transforms. Because of these properties and after the development of several fast algorithms for computing the wavelet representation of any signal, in particular the Multi-Resolution Analysis (MRA) developed by Mallat, wavelet transforms have increasingly been applied to signal analysis problems, especially real-life problems, in which speed is critical. In this paper we present and compare efficient wavelet decomposition algorithms on different parallel architectures. We report and analyze experimental measurements, using NASA remotely sensed images. Results show that our algorithms achieve significant performance gains on current high performance parallel systems, and meet scientific applications and multimedia requirements. The extensive performance measurements collected over a number of high-performance computer systems have revealed important architectural characteristics of these systems, in relation to the processing demands of the wavelet decomposition of digital images.
Scientific development of a massively parallel ocean climate model. Final report
Semtner, A.J.; Chervin, R.M.
1996-09-01
Over the last three years, very significant advances have been made in refining the grid resolution of ocean models and in improving the physical and numerical treatments of ocean hydrodynamics. Some of these advances have occurred as a result of the successful transition of ocean models onto massively parallel computers, which has been led by Los Alamos investigators. Major progress has been made in simulating global ocean circulation and in understanding various ocean climatic aspects such as the effect of wind driving on heat and freshwater transports. These steps have demonstrated the capability to conduct realistic decadal to century ocean integrations at high resolution on massively parallel computers.
Factorization of large integers on a massively parallel computer
Davis, J.A.; Holdridge, D.B.
1988-01-01
Our interest in integer factorization at Sandia National Laboratories is motivated by cryptographic applications and in particular the security of the RSA encryption-decryption algorithm. We have implemented our version of the quadratic sieve procedure on the NCUBE computer with 1024 processors (nodes). The new code is significantly different in all important aspects from the program used to factor number of order 10/sup 70/ on a single processor CRAY computer. Capabilities of parallel processing and limitation of small local memory necessitated this entirely new implementation. This effort involved several restarts as realizations of program structures that seemed appealing bogged down due to inter-processor communications. We are presently working with integers of magnitude about 10/sup 70/ in tuning this code to the novel hardware. 6 refs., 3 figs.
Signal processing applications of massively parallel charge domain computing devices
NASA Technical Reports Server (NTRS)
Fijany, Amir (Inventor); Barhen, Jacob (Inventor); Toomarian, Nikzad (Inventor)
1999-01-01
The present invention is embodied in a charge coupled device (CCD)/charge injection device (CID) architecture capable of performing a Fourier transform by simultaneous matrix vector multiplication (MVM) operations in respective plural CCD/CID arrays in parallel in O(1) steps. For example, in one embodiment, a first CCD/CID array stores charge packets representing a first matrix operator based upon permutations of a Hartley transform and computes the Fourier transform of an incoming vector. A second CCD/CID array stores charge packets representing a second matrix operator based upon different permutations of a Hartley transform and computes the Fourier transform of an incoming vector. The incoming vector is applied to the inputs of the two CCD/CID arrays simultaneously, and the real and imaginary parts of the Fourier transform are produced simultaneously in the time required to perform a single MVM operation in a CCD/CID array.
Massively parallel algorithms for trace-driven cache simulations
NASA Technical Reports Server (NTRS)
Nicol, David M.; Greenberg, Albert G.; Lubachevsky, Boris D.
1991-01-01
Trace driven cache simulation is central to computer design. A trace is a very long sequence of reference lines from main memory. At the t(exp th) instant, reference x sub t is hashed into a set of cache locations, the contents of which are then compared with x sub t. If at the t sup th instant x sub t is not present in the cache, then it is said to be a miss, and is loaded into the cache set, possibly forcing the replacement of some other memory line, and making x sub t present for the (t+1) sup st instant. The problem of parallel simulation of a subtrace of N references directed to a C line cache set is considered, with the aim of determining which references are misses and related statistics. A simulation method is presented for the Least Recently Used (LRU) policy, which regradless of the set size C runs in time O(log N) using N processors on the exclusive read, exclusive write (EREW) parallel model. A simpler LRU simulation algorithm is given that runs in O(C log N) time using N/log N processors. Timings are presented of the second algorithm's implementation on the MasPar MP-1, a machine with 16384 processors. A broad class of reference based line replacement policies are considered, which includes LRU as well as the Least Frequently Used and Random replacement policies. A simulation method is presented for any such policy that on any trace of length N directed to a C line set runs in the O(C log N) time with high probability using N processors on the EREW model. The algorithms are simple, have very little space overhead, and are well suited for SIMD implementation.
Massively parallel computation of RCS with finite elements
NASA Technical Reports Server (NTRS)
Parker, Jay
1993-01-01
One of the promising combinations of finite element approaches for scattering problems uses Whitney edge elements, spherical vector wave-absorbing boundary conditions, and bi-conjugate gradient solution for the frequency-domain near field. Each of these approaches may be criticized. Low-order elements require high mesh density, but also result in fast, reliable iterative convergence. Spherical wave-absorbing boundary conditions require additional space to be meshed beyond the most minimal near-space region, but result in fully sparse, symmetric matrices which keep storage and solution times low. Iterative solution is somewhat unpredictable and unfriendly to multiple right-hand sides, yet we find it to be uniformly fast on large problems to date, given the other two approaches. Implementation of these approaches on a distributed memory, message passing machine yields huge dividends, as full scalability to the largest machines appears assured and iterative solution times are well-behaved for large problems. We present times and solutions for computed RCS for a conducting cube and composite permeability/conducting sphere on the Intel ipsc860 with up to 16 processors solving over 200,000 unknowns. We estimate problems of approximately 10 million unknowns, encompassing 1000 cubic wavelengths, may be attempted on a currently available 512 processor machine, but would be exceedingly tedious to prepare. The most severe bottlenecks are due to the slow rate of mesh generation on non-parallel machines and the large transfer time from such a machine to the parallel processor. One solution, in progress, is to create and then distribute a coarse mesh among the processors, followed by systematic refinement within each processor. Elimination of redundant node definitions at the mesh-partition surfaces, snap-to-surface post processing of the resulting mesh for good modelling of curved surfaces, and load-balancing redistribution of new elements after the refinement are auxiliary
MASSIVELY PARALLEL LATENT SEMANTIC ANALYSES USING A GRAPHICS PROCESSING UNIT
Cavanagh, J.; Cui, S.
2009-01-01
Latent Semantic Analysis (LSA) aims to reduce the dimensions of large term-document datasets using Singular Value Decomposition. However, with the ever-expanding size of datasets, current implementations are not fast enough to quickly and easily compute the results on a standard PC. A graphics processing unit (GPU) can solve some highly parallel problems much faster than a traditional sequential processor or central processing unit (CPU). Thus, a deployable system using a GPU to speed up large-scale LSA processes would be a much more effective choice (in terms of cost/performance ratio) than using a PC cluster. Due to the GPU’s application-specifi c architecture, harnessing the GPU’s computational prowess for LSA is a great challenge. We presented a parallel LSA implementation on the GPU, using NVIDIA® Compute Unifi ed Device Architecture and Compute Unifi ed Basic Linear Algebra Subprograms software. The performance of this implementation is compared to traditional LSA implementation on a CPU using an optimized Basic Linear Algebra Subprograms library. After implementation, we discovered that the GPU version of the algorithm was twice as fast for large matrices (1 000x1 000 and above) that had dimensions not divisible by 16. For large matrices that did have dimensions divisible by 16, the GPU algorithm ran fi ve to six times faster than the CPU version. The large variation is due to architectural benefi ts of the GPU for matrices divisible by 16. It should be noted that the overall speeds for the CPU version did not vary from relative normal when the matrix dimensions were divisible by 16. Further research is needed in order to produce a fully implementable version of LSA. With that in mind, the research we presented shows that the GPU is a viable option for increasing the speed of LSA, in terms of cost/performance ratio.
A massively parallel computational approach to coupled thermoelastic/porous gas flow problems
NASA Technical Reports Server (NTRS)
Shia, David; Mcmanus, Hugh L.
1995-01-01
A new computational scheme for coupled thermoelastic/porous gas flow problems is presented. Heat transfer, gas flow, and dynamic thermoelastic governing equations are expressed in fully explicit form, and solved on a massively parallel computer. The transpiration cooling problem is used as an example problem. The numerical solutions have been verified by comparison to available analytical solutions. Transient temperature, pressure, and stress distributions have been obtained. Small spatial oscillations in pressure and stress have been observed, which would be impractical to predict with previously available schemes. Comparisons between serial and massively parallel versions of the scheme have also been made. The results indicate that for small scale problems the serial and parallel versions use practically the same amount of CPU time. However, as the problem size increases the parallel version becomes more efficient than the serial version.
Solution of large linear systems of equations on the massively parallel processor
NASA Technical Reports Server (NTRS)
Ida, Nathan; Udawatta, Kapila
1987-01-01
The Massively Parallel Processor (MPP) was designed as a special machine for specific applications in image processing. As a parallel machine, with a large number of processors that can be reconfigured in different combinations it is also applicable to other problems that require a large number of processors. The solution of linear systems of equations on the MPP is investigated. The solution times achieved are compared to those obtained with a serial machine and the performance of the MPP is discussed.
Three-dimensional electromagnetic modeling and inversion on massively parallel computers
Newman, G.A.; Alumbaugh, D.L.
1996-03-01
This report has demonstrated techniques that can be used to construct solutions to the 3-D electromagnetic inverse problem using full wave equation modeling. To this point great progress has been made in developing an inverse solution using the method of conjugate gradients which employs a 3-D finite difference solver to construct model sensitivities and predicted data. The forward modeling code has been developed to incorporate absorbing boundary conditions for high frequency solutions (radar), as well as complex electrical properties, including electrical conductivity, dielectric permittivity and magnetic permeability. In addition both forward and inverse codes have been ported to a massively parallel computer architecture which allows for more realistic solutions that can be achieved with serial machines. While the inversion code has been demonstrated on field data collected at the Richmond field site, techniques for appraising the quality of the reconstructions still need to be developed. Here it is suggested that rather than employing direct matrix inversion to construct the model covariance matrix which would be impossible because of the size of the problem, one can linearize about the 3-D model achieved in the inverse and use Monte-Carlo simulations to construct it. Using these appraisal and construction tools, it is now necessary to demonstrate 3-D inversion for a variety of EM data sets that span the frequency range from induction sounding to radar: below 100 kHz to 100 MHz. Appraised 3-D images of the earth`s electrical properties can provide researchers opportunities to infer the flow paths, flow rates and perhaps the chemistry of fluids in geologic mediums. It also offers a means to study the frequency dependence behavior of the properties in situ. This is of significant relevance to the Department of Energy, paramount to characterizing and monitoring of environmental waste sites and oil and gas exploration.
Massively parallel algorithms for real-time wavefront control of a dense adaptive optics system
Fijany, A.; Milman, M.; Redding, D.
1994-12-31
In this paper massively parallel algorithms and architectures for real-time wavefront control of a dense adaptive optic system (SELENE) are presented. The authors have already shown that the computation of a near optimal control algorithm for SELENE can be reduced to the solution of a discrete Poisson equation on a regular domain. Although, this represents an optimal computation, due the large size of the system and the high sampling rate requirement, the implementation of this control algorithm poses a computationally challenging problem since it demands a sustained computational throughput of the order of 10 GFlops. They develop a novel algorithm, designated as Fast Invariant Imbedding algorithm, which offers a massive degree of parallelism with simple communication and synchronization requirements. Due to these features, this algorithm is significantly more efficient than other Fast Poisson Solvers for implementation on massively parallel architectures. The authors also discuss two massively parallel, algorithmically specialized, architectures for low-cost and optimal implementation of the Fast Invariant Imbedding algorithm.
Electric and Magnetic Forces between Parallel-Wire Conductors.
ERIC Educational Resources Information Center
Morton, N.
1979-01-01
Discusses electric and magnetic forces between parallel-wire conductors and derives, in a simple fashion, order of magnitude estimates of the ratio of the likely electrostatic and electromagnetic forces for a simple parallel-wire balance. (Author/HM)
Large-eddy simulation of the Rayleigh-Taylor instability on a massively parallel computer
Amala, P.A.K.
1995-03-01
A computational model for the solution of the three-dimensional Navier-Stokes equations is developed. This model includes a turbulence model: a modified Smagorinsky eddy-viscosity with a stochastic backscatter extension. The resultant equations are solved using finite difference techniques: the second-order explicit Lax-Wendroff schemes. This computational model is implemented on a massively parallel computer. Programming models on massively parallel computers are next studied. It is desired to determine the best programming model for the developed computational model. To this end, three different codes are tested on a current massively parallel computer: the CM-5 at Los Alamos. Each code uses a different programming model: one is a data parallel code; the other two are message passing codes. Timing studies are done to determine which method is the fastest. The data parallel approach turns out to be the fastest method on the CM-5 by at least an order of magnitude. The resultant code is then used to study a current problem of interest to the computational fluid dynamics community. This is the Rayleigh-Taylor instability. The Lax-Wendroff methods handle shocks and sharp interfaces poorly. To this end, the Rayleigh-Taylor linear analysis is modified to include a smoothed interface. The linear growth rate problem is then investigated. Finally, the problem of the randomly perturbed interface is examined. Stochastic backscatter breaks the symmetry of the stationary unstable interface and generates a mixing layer growing at the experimentally observed rate. 115 refs., 51 figs., 19 tabs.
NASA Astrophysics Data System (ADS)
Chen, Yufeng; Wu, Zebin; Sun, Le; Wei, Zhihui; Li, Yonglong
2016-04-01
With the gradual increase in the spatial and spectral resolution of hyperspectral images, the size of image data becomes larger and larger, and the complexity of processing algorithms is growing, which poses a big challenge to efficient massive hyperspectral image processing. Cloud computing technologies distribute computing tasks to a large number of computing resources for handling large data sets without the limitation of memory and computing resource of a single machine. This paper proposes a parallel pixel purity index (PPI) algorithm for unmixing massive hyperspectral images based on a MapReduce programming model for the first time in the literature. According to the characteristics of hyperspectral images, we describe the design principle of the algorithm, illustrate the main cloud unmixing processes of PPI, and analyze the time complexity of serial and parallel algorithms. Experimental results demonstrate that the parallel implementation of the PPI algorithm on the cloud can effectively process big hyperspectral data and accelerate the algorithm.
Applications of the massively parallel machine, the MasPar MP-1, to Earth sciences
NASA Technical Reports Server (NTRS)
Fischer, James R.; Strong, James P.; Dorband, John E.; Tilton, James C.
1991-01-01
The computational workload of upcoming NASA science missions, especially the ground data processing for the Earth Observing System, is projected to be quite large (in the 50 to 100 gigaFLOPS range) and corespondingly very expensive to perform using conventional supercomputer systems. High performance, general purpose massively parallel computer systems such as the MasPar MP-1 are being investigated by NASA as a more cost effective alternative. Massively parallel systems are targeted for accelerated development and maturation by NASA's upcoming five-year High Performance Computing and Communications Program. A summary of the broad range of applications currently running on the MP-1 at NASA/Goddard are presented in this paper along with descriptions of the parallel algorithmic techniques employed in five applications that have bearing on Earth sciences.
Massively parallel implementation of the Penn State/NCAR Mesoscale Model
Foster, I.; Michalakes, J.
1992-01-01
Parallel computing promises significant improvements in both the raw speed and cost performance of mesoscale atmospheric models. On distributed-memory massively parallel computers available today, the performance of a mesoscale model will exceed that of conventional supercomputers; on the teraflops machines expected within the next five years, performance will increase by several orders of magnitude. As a result, scientists will be able to consider larger problems, more complex model processes, and finer resolutions. In this paper. we report on a project at Argonne National Laboratory that will allow scientists to take advantage of parallel computing technology. This Massively Parallel Mesoscale Model (MPMM) will be functionally equivalent to the Penn State/NCAR Mesoscale Model (MM). In a prototype study, we produced a parallel version of MM4 using a static (compile-time) coarse-grained patch'' decomposition. This code achieves one-third the performance of a one-processor CRAY Y-MP on twelve Intel 1860 microprocessors. The current version of MPMM is based on all MM5 and uses a more fine-grained approach, decomposing the grid as finely as the mesh itself allows so that each horizontal grid cell is a parallel process. This will allow the code to utilize many hundreds of processors. A high-level language for expressing parallel programs is used to implement communication strearns between the processes in a way that permits dynamic remapping to the physical processors of a particular parallel computer. This facilitates load balancing, grid nesting, and coupling with graphical systems and other models.
Massively parallel implementation of the Penn State/NCAR Mesoscale Model
Foster, I.; Michalakes, J.
1992-12-01
Parallel computing promises significant improvements in both the raw speed and cost performance of mesoscale atmospheric models. On distributed-memory massively parallel computers available today, the performance of a mesoscale model will exceed that of conventional supercomputers; on the teraflops machines expected within the next five years, performance will increase by several orders of magnitude. As a result, scientists will be able to consider larger problems, more complex model processes, and finer resolutions. In this paper. we report on a project at Argonne National Laboratory that will allow scientists to take advantage of parallel computing technology. This Massively Parallel Mesoscale Model (MPMM) will be functionally equivalent to the Penn State/NCAR Mesoscale Model (MM). In a prototype study, we produced a parallel version of MM4 using a static (compile-time) coarse-grained ``patch`` decomposition. This code achieves one-third the performance of a one-processor CRAY Y-MP on twelve Intel 1860 microprocessors. The current version of MPMM is based on all MM5 and uses a more fine-grained approach, decomposing the grid as finely as the mesh itself allows so that each horizontal grid cell is a parallel process. This will allow the code to utilize many hundreds of processors. A high-level language for expressing parallel programs is used to implement communication strearns between the processes in a way that permits dynamic remapping to the physical processors of a particular parallel computer. This facilitates load balancing, grid nesting, and coupling with graphical systems and other models.
A domain decomposition study of massively parallel computing in compressible gas dynamics
NASA Astrophysics Data System (ADS)
Wong, C. C.; Blottner, F. G.; Payne, J. L.; Soetrisno, M.
1995-03-01
The appropriate utilization of massively parallel computers for solving the Navier-Stokes equations is investigated and determined from an engineering perspective. The issues investigated are: (1) Should strip or patch domain decomposition of the spatial mesh be used to reduce computer time? (2) How many computer nodes should be used for a problem with a given sized mesh to reduce computer time? (3) Is the convergence of the Navier-Stokes solution procedure (LU-SGS) adversely influenced by the domain decomposition approach? The results of the paper show that the present Navier-Stokes solution technique has good performance on a massively parallel computer for transient flow problems. For steady-state problems with a large number of mesh cells, the solution procedure will require significant computer time due to an increased number of iterations to achieve a converged solution. There is an optimum number of computer nodes to use for a problem with a given global mesh size.
Nguyen-Dumont, Tú; Pope, Bernard J; Hammet, Fleur; Mahmoodi, Maryam; Tsimiklis, Helen; Southey, Melissa C; Park, Daniel J
2013-11-15
Although per-base sequencing costs have decreased during recent years, library preparation for targeted massively parallel sequencing remains constrained by high reagent cost, limited design flexibility, and protocol complexity. To address these limitations, we previously developed Hi-Plex, a polymerase chain reaction (PCR) massively parallel sequencing strategy for screening panels of genomic target regions. Here, we demonstrate that Hi-Plex applied with hybrid adapters can generate a library suitable for sequencing with both the Ion Torrent and the TruSeq chemistries and that adjusting primer concentrations improves coverage uniformity. These results expand Hi-Plex capabilities as an accurate, affordable, flexible, and rapid approach for various genetic screening applications. PMID:23933242
Nguyen-Dumont, Tú; Pope, Bernard J.; Hammet, Fleur; Mahmoodi, Maryam; Tsimiklis, Helen; Southey, Melissa C.; Park, Daniel J.
2013-01-01
Although per-base sequencing costs have decreased during recent years, library preparation for targeted massively parallel sequencing remains constrained by high reagent cost, limited design flexibility, and protocol complexity. To address these limitations, we previously developed Hi-Plex, a polymerase chain reaction (PCR) massively parallel sequencing strategy for screening panels of genomic target regions. Here, we demonstrate that Hi-Plex applied with hybrid adapters can generate a library suitable for sequencing with both the Ion Torrent and the TruSeq chemistries and that adjusting primer concentrations improves coverage uniformity. These results expand Hi-Plex capabilities as an accurate, affordable, flexible, and rapid approach for various genetic screening applications. PMID:23933242
Massively parallel per-pixel-based zerotree processing architecture for real-time video compression
NASA Astrophysics Data System (ADS)
Alagoda, Geoffrey; Rassau, Alexander M.; Eshraghian, Kamran
2001-11-01
In the span of a few years, mobile multimedia communication has rapidly become a significant area of research and development constantly challenging boundaries on a variety of technological fronts. Video compression, a fundamental component for most mobile multimedia applications, generally places heavy demands in terms of the required processing capacity. Hardware implementations of typical modern hybrid codecs require realisation of components such as motion compensation, wavelet transform, quantisation, zerotree coding and arithmetic coding in real-time. While the implementation of such codecs using a fast generic processor is possible, undesirable trade-offs in terms of power consumption and speed must generally be made. The improvement in power consumption that is achievable through the use of a slow-clocked massively parallel processing environment, while maintaining real-time processing speeds, should thus not be overlooked. An architecture to realise such a massively parallel solution for a zerotree entropy coder is, therefore, presented in this paper.
Numerical and physical instabilities in massively parallel LES of reacting flows
NASA Astrophysics Data System (ADS)
Poinsot, Thierry
LES of reacting flows is rapidly becoming mature and providing levels of precision which can not be reached with any RANS (Reynolds Averaged) technique. In addition to the multiple subgrid scale models required for such LES and to the questions raised by the required numerical accurcay of LES solvers, various issues related the reliability, mesh independence and repetitivity of LES must still be addressed, especially when LES is used on massively parallel machines. This talk discusses some of these issues: (1) the existence of non physical waves (known as `wiggles' by most LES practitioners) in LES, (2) the effects of mesh size on LES of reacting flows, (3) the growth of rounding errors in LES on massively parallel machines and more generally (4) the ability to qualify a LES code as `bug free' and `accurate'. Examples range from academic cases (minimum non-reacting turbulent channel) to applied configurations (a sector of an helicopter combustion chamber).
NASA Technical Reports Server (NTRS)
Manohar, Mareboyana; Tilton, James C.
1994-01-01
A progressive vector quantization (VQ) compression approach is discussed which decomposes image data into a number of levels using full search VQ. The final level is losslessly compressed, enabling lossless reconstruction. The computational difficulties are addressed by implementation on a massively parallel SIMD machine. We demonstrate progressive VQ on multispectral imagery obtained from the Advanced Very High Resolution Radiometer instrument and other Earth observation image data, and investigate the trade-offs in selecting the number of decomposition levels and codebook training method.
Chemical network problems solved on NASA/Goddard's massively parallel processor computer
NASA Technical Reports Server (NTRS)
Cho, Seog Y.; Carmichael, Gregory R.
1987-01-01
The single instruction stream, multiple data stream Massively Parallel Processor (MPP) unit consists of 16,384 bit serial arithmetic processors configured as a 128 x 128 array whose speed can exceed that of current supercomputers (Cyber 205). The applicability of the MPP for solving reaction network problems is presented and discussed, including the mapping of the calculation to the architecture, and CPU timing comparisons.
Parallel contributing area calculation with granularity control on massive grid terrain datasets
NASA Astrophysics Data System (ADS)
Jiang, Ling; Tang, Guoan; Liu, Xuejun; Song, Xiaodong; Yang, Jianyi; Liu, Kai
2013-10-01
The calculation of contributing areas from digital elevation models (DEMs) is one of the important tasks in digital terrain analysis (DTA). The computational process usually involves two steps in a real application: (1) calculating flow directions via a flow model, and (2) computing the contributing area for each grid cell in the DEM. The traditional algorithm for calculating contributing areas is coded as a sequential program executed on a single processor. With the increase of scope and resolution of DEMs, the serial algorithm has become increasingly difficult to perform and is often very time-consuming, especially for DEMs of large areas and fine scales. In recent years, parallel computing is able to meet this challenge with the development of computer technology. However, the parallel implementation with granularity control, an efficient strategy to reap the best parallel performance and to break the limitation of computing resources in processing massive grid terrain datasets, has not been found in DTA research field. This paper develops a message-passing-interface (MPI) parallel approach with granularity control to calculate contributing areas. According to the proposed parallelization strategy, the parallel D8 algorithm with granularity control is designed as well as the parallel AreaD8 algorithm. Based on the domain decomposition of DEM data, it is possible for each process to process multiple partitions decomposed under a grain size. According to an iterative procedure of reading source data, executing the operator and writing resulting data, the partitions achieve the calculation results one by one in each process. The experimental results on a multi-node cluster show that the proposed parallel algorithms with granularity control are the powerful tools to process the big dataset and the parallel D8 algorithm is insensitive to granularity, while the parallel AreaD8 algorithm has an optimal grain size to reap the best parallel performance.
Massively parallel multifrontal methods for finite element analysis on MIMD computer systems
Benner, R.E.
1993-03-01
The development of highly parallel direct solvers for large, sparse linear systems of equations (e.g. for finite element or finite difference models) is lagging behind progress in parallel direct solvers for dense matrices and iterative methods for sparse matrices. We describe a massively parallel (MP) multifrontal solver for the direct solution of large sparse linear systems, such as those routinely encountered in finite element structural analysis, in an effort to address concerns about the viability of scalable, MP direct methods for sparse systems and enhance the software base for MP applications. Performance results are presented and future directions are outlined for research and development efforts in parallel multifrontal and related solvers. In particular, parallel efficiencies of 25% on 1024 nCUBE 2 nodes and 36% on 64 Intel iPSCS60 nodes have been demonstrated, and parallel efficiencies of 60--85% are expected when a severe load imbalance is overcome by static mapping and dynamic load balance techniques previously developed for other parallel solvers and application codes.
Using CLIPS in the domain of knowledge-based massively parallel programming
NASA Technical Reports Server (NTRS)
Dvorak, Jiri J.
1994-01-01
The Program Development Environment (PDE) is a tool for massively parallel programming of distributed-memory architectures. Adopting a knowledge-based approach, the PDE eliminates the complexity introduced by parallel hardware with distributed memory and offers complete transparency in respect of parallelism exploitation. The knowledge-based part of the PDE is realized in CLIPS. Its principal task is to find an efficient parallel realization of the application specified by the user in a comfortable, abstract, domain-oriented formalism. A large collection of fine-grain parallel algorithmic skeletons, represented as COOL objects in a tree hierarchy, contains the algorithmic knowledge. A hybrid knowledge base with rule modules and procedural parts, encoding expertise about application domain, parallel programming, software engineering, and parallel hardware, enables a high degree of automation in the software development process. In this paper, important aspects of the implementation of the PDE using CLIPS and COOL are shown, including the embedding of CLIPS with C++-based parts of the PDE. The appropriateness of the chosen approach and of the CLIPS language for knowledge-based software engineering are discussed.
Massively parallel fast elliptic equation solver for three dimensional hydrodynamics and relativity
Sholl, P.L.; Wilson, J.R.; Mathews, G.J.; Avila, J.H.
1995-01-01
Through the work proposed in this document we expect to advance the forefront of large scale computational efforts on massively parallel distributed-memory multiprocessors. We will develop tools for effective conversion to a parallel implementation of sequential numerical methods used to solve large systems of partial differential equations. The research supported by this work will involve conversion of a program which does state of the art modeling of multi-dimensional hydrodynamics, general relativity and particle transport in energetic astrophysical environments. The proposed parallel algorithm development, particularly the study and development of fast elliptic equation solvers, could significantly benefit this program and other applications involving solutions to systems of differential equations. We shall develop a data communication manager for distributed memory computers as an aid in program conversions to a parallel environment and implement it in the three dimensional relativistic hydrodynamics program discussed below; develop a concurrent system/concurrent subgrid multigrid method. Currently, five systems are approximated sequentially using multigrid successive overrelaxation. Results from an iteration cycle of one multigrid system are used in following multigrid systems iterations. We shall develop a multigrid algorithm for simultaneous computation of the sets of equations. In addition, we shall implement a method for concurrent processing of the subgrids in each of the multigrid computations. The conditions for convergence of the method will be examined. We`ll compare this technique to other parallel multigrid techniques, such as distributed data/sequential subgrids and the Parallel Superconvergent Multigrid of Frederickson and McBryan. We expect the results of these studies to offer insight and tools both for the selection of new algorithms as well as for conversion of existing large codes for massively parallel architectures.
ASCI Red -- Experiences and lessons learned with a massively parallel teraFLOP supercomputer
Christon, M.A.; Crawford, D.A.; Hertel, E.S.; Peery, J.S.; Robinson, A.C.
1997-06-01
The Accelerated Strategic Computing Initiative (ASCI) program involves Sandia, Los Alamos and Lawrence Livermore National Laboratories. At Sandia National Laboratories, ASCI applications include large deformation transient dynamics, shock propagation, electromechanics, and abnormal thermal environments. In order to resolve important physical phenomena in these problems, it is estimated that meshes ranging from 10{sup 6} to 10{sup 9} grid points will be required. The ASCI program is relying on the use of massively parallel supercomputers initially capable of delivering over 1 TFLOPs to perform such demanding computations. The ASCI Red machine at Sandia National Laboratories consists of over 4,500 computational nodes with a peak computational rate of 1.8 TFLOPs, 567 GBytes of memory, and 2 TBytes of disk storage. Regardless of the peak FLOP rate, there are many issues surrounding the use of massively parallel supercomputers in a production environment. These issues include parallel I/O, mesh generation, visualization, archival storage, high-bandwidth networking and the development of parallel algorithms. In order to illustrate these issues and their solution with respect to ASCI Red, demonstration calculations of time-dependent buoyancy-dominated plumes, electromechanics, and shock propagation will be presented.
Massively parallel Monte Carlo for many-particle simulations on GPUs
Anderson, Joshua A.; Jankowski, Eric; Grubb, Thomas L.; Engel, Michael; Glotzer, Sharon C.
2013-12-01
Current trends in parallel processors call for the design of efficient massively parallel algorithms for scientific computing. Parallel algorithms for Monte Carlo simulations of thermodynamic ensembles of particles have received little attention because of the inherent serial nature of the statistical sampling. In this paper, we present a massively parallel method that obeys detailed balance and implement it for a system of hard disks on the GPU. We reproduce results of serial high-precision Monte Carlo runs to verify the method. This is a good test case because the hard disk equation of state over the range where the liquid transforms into the solid is particularly sensitive to small deviations away from the balance conditions. On a Tesla K20, our GPU implementation executes over one billion trial moves per second, which is 148 times faster than on a single Intel Xeon E5540 CPU core, enables 27 times better performance per dollar, and cuts energy usage by a factor of 13. With this improved performance we are able to calculate the equation of state for systems of up to one million hard disks. These large system sizes are required in order to probe the nature of the melting transition, which has been debated for the last forty years. In this paper we present the details of our computational method, and discuss the thermodynamics of hard disks separately in a companion paper.
Medical image processing utilizing neural networks trained on a massively parallel computer.
Kerr, J P; Bartlett, E B
1995-07-01
While finding many applications in science, engineering, and medicine, artificial neural networks (ANNs) have typically been limited to small architectures. In this paper, we demonstrate how very large architecture neural networks can be trained for medical image processing utilizing a massively parallel, single-instruction multiple data (SIMD) computer. The two- to three-orders of magnitude improvement in processing time attainable using a parallel computer makes it practical to train very large architecture ANNs. As an example we have trained several ANNs to demonstrate the tomographic reconstruction of 64 x 64 single photon emission computed tomography (SPECT) images from 64 planar views of the images. The potential for these large architecture ANNs lies in the fact that once the neural network is properly trained on the parallel computer the corresponding interconnection weight file can be loaded on a serial computer. Subsequently, relatively fast processing of all novel images can be performed on a PC or workstation. PMID:7497701
A massively parallel adaptive finite element method with dynamic load balancing
Devine, K.D.; Flaherty, J.E.; Wheat, S.R.; Maccabe, A.B.
1993-05-01
We construct massively parallel, adaptive finite element methods for the solution of hyperbolic conservation laws in one and two dimensions. Spatial discretization is performed by a discontinuous Galerkin finite element method using a basis of piecewise Legendre polynomials. Temporal discretization utilizes a Runge-Kutta method. Dissipative fluxes and projection limiting prevent oscillations near solution discontinuities. The resulting method is of high order and may be parallelized efficiently on MIMD computers. We demonstrate parallel efficiency through computations on a 1024-processor nCUBE/2 hypercube. We also present results using adaptive p-refinement to reduce the computational cost of the method. We describe tiling, a dynamic, element-based data migration system. Tiling dynamically maintains global load balance in the adaptive method by overlapping neighborhoods of processors, where each neighborhood performs local load balancing. We demonstrate the effectiveness of the dynamic load balancing with adaptive p-refinement examples.
A massively parallel adaptive finite element method with dynamic load balancing
Devine, K.D.; Flaherty, J.E.; Wheat, S.R.; Maccabe, A.B.
1993-12-31
The authors construct massively parallel adaptive finite element methods for the solution of hyperbolic conservation laws. Spatial discretization is performed by a discontinuous Galerkin finite element method using a basis of piecewise Legendre polynomials. Temporal discretization utilizes a Runge-Kutta method. Dissipative fluxes and projection limiting prevent oscillations near solution discontinuities. The resulting method is of high order and may be parallelized efficiently on MIMD computers. They demonstrate parallel efficiency through computations on a 1024-processor nCUBE/2 hypercube. They present results using adaptive p-refinement to reduce the computational cost of the method, and tiling, a dynamic, element-based data migration system that maintains global load balance of the adaptive method by overlapping neighborhoods of processors that each perform local balancing.
The use of inexact ODE solver in waveform relaxation methods on a massively parallel computer
Luk, W.S.; Wing, O.
1995-12-01
This paper presents the use of inexact ordinary differential equation (ODE) solver in waveform relaxation methods for solving initial value problems: Since the conventional ODE solvers are inherently sequential, the inexact ODE solver is used by taking time points from only previous waveform iteration for time integration. As a result, this method is truly massively parallel, as the equation is completely unfolded both in system and in time. Convergence analysis shows that the spectral radius of the iteration equation resulting from the {open_quotes}inexact{close_quotes} solver is the same as that from the standard method, and hence the new method is robust. The parallel implementation issues on the DECmpp 12000/Sx computer will also be discussed. Numerical results illustrate that though the number of iterations in the inexact method is increased over the exact method, as expected, the computation time is much reduced because of the large-scale parallelism.
Plimpton, Steve; Thompson, Aidan; Crozier, Paul
LAMMPS (http://lammps.sandia.gov/index.html) stands for Large-scale Atomic/Molecular Massively Parallel Simulator and is a code that can be used to model atoms or, as the LAMMPS website says, as a parallel particle simulator at the atomic, meso, or continuum scale. This Sandia-based website provides a long list of animations from large simulations. These were created using different visualization packages to read LAMMPS output, and each one provides the name of the PI and a brief description of the work done or visualization package used. See also the static images produced from simulations at http://lammps.sandia.gov/pictures.html The foundation paper for LAMMPS is: S. Plimpton, Fast Parallel Algorithms for Short-Range Molecular Dynamics, J Comp Phys, 117, 1-19 (1995), but the website also lists other papers describing contributions to LAMMPS over the years.
Design and Performance Analysis of a Massively Parallel Atmospheric General Circulation Model
NASA Technical Reports Server (NTRS)
Schaffer, Daniel S.; Suarez, Max J.
1998-01-01
In the 1990's computer manufacturers are increasingly turning to the development of parallel processor machines to meet the high performance needs of their customers. Simultaneously, atmospheric scientists study weather and climate phenomena ranging from hurricanes to El Nino to global warming that require increasingly fine resolution models. Here, implementation of a parallel atmospheric general circulation model (GCM) which exploits the power of massively parallel machines is described. Using the horizontal data domain decomposition methodology, this FORTRAN 90 model is able to integrate a 0.6 deg. longitude by 0.5 deg. latitude problem at a rate of 19 Gigaflops on 512 processors of a Cray T3E 600; corresponding to 280 seconds of wall-clock time per simulated model day. At this resolution, the model has 64 times as many degrees of freedom and performs 400 times as many floating point operations per simulated day as the model it replaces.
Massive photons and Dirac monopoles: Electric condensate and magnetic confinement
NASA Astrophysics Data System (ADS)
Guimaraes, M. S.; Rougemont, R.; Wotzasek, C.; Zarro, C. A. D.
2013-06-01
We use the generalized Julia-Toulouse approach (GJTA) for condensation of topological currents (charges or defects) to argue that massive photons can coexist consistently with Dirac monopoles. The Proca theory is obtained here via GJTA as a low energy effective theory describing an electric condensate and the mass of the vector boson is responsible for generating a Meissner effect which confines the magnetic defects in monopole-antimonopole pairs connected by physical open magnetic vortices described by Dirac brane invariants, instead of Dirac strings.
NASA Astrophysics Data System (ADS)
Perumalla, K.; Fujimoto, R.; Pande, S.; Karimabadi, H.; Driscoll, J.; Omelchenko, Y.
2005-12-01
Large parallel/distributed scientific simulations are very complex, and their dynamic behavior is hard to predict. Efficient development of massively parallel codes remains a computational challenge. For example, almost none of the kinetic codes in use in space physics today have dynamic load balancing capability. Here we present a new infrastructure for design and prediction of parallel codes. Performance prediction is useful to analyze, understand and experiment with different partitioning schemes, multiple modeling alternatives and so on, without having to run the application on supercomputers. Instrumentation of the model (with least perturbance to performance) is useful to glean key metrics and understand application-level behavior. Unfortunately, traditional approaches to virtual execution and instrumentation are limited by either slow execution speed or low resolution or both. We present a new framework that provides a high-resolution framework that provides a virtual CPU abstraction (with a full thread context per CPU), yet scales to thousands of virtual CPUs. The tool, called PDES2, presents different levels of modeling interfaces, from general purpose parallel simulations to parallel grid-based particle-in-cell (PIC) codes. The tool itself runs on multiple processors in order to accommodate the high-resolution by distributing the virtual execution across processors. Validation experiments of PIC models in the framework using a 1-D hybrid shock application show close agreement of results from virtual executions with results from actual supercomputer runs. The utility of this tool is further illustrated through an application to a parallel global hybrid code.
LDRD final report on massively-parallel linear programming : the parPCx system.
Parekh, Ojas; Phillips, Cynthia Ann; Boman, Erik Gunnar
2005-02-01
This report summarizes the research and development performed from October 2002 to September 2004 at Sandia National Laboratories under the Laboratory-Directed Research and Development (LDRD) project ''Massively-Parallel Linear Programming''. We developed a linear programming (LP) solver designed to use a large number of processors. LP is the optimization of a linear objective function subject to linear constraints. Companies and universities have expended huge efforts over decades to produce fast, stable serial LP solvers. Previous parallel codes run on shared-memory systems and have little or no distribution of the constraint matrix. We have seen no reports of general LP solver runs on large numbers of processors. Our parallel LP code is based on an efficient serial implementation of Mehrotra's interior-point predictor-corrector algorithm (PCx). The computational core of this algorithm is the assembly and solution of a sparse linear system. We have substantially rewritten the PCx code and based it on Trilinos, the parallel linear algebra library developed at Sandia. Our interior-point method can use either direct or iterative solvers for the linear system. To achieve a good parallel data distribution of the constraint matrix, we use a (pre-release) version of a hypergraph partitioner from the Zoltan partitioning library. We describe the design and implementation of our new LP solver called parPCx and give preliminary computational results. We summarize a number of issues related to efficient parallel solution of LPs with interior-point methods including data distribution, numerical stability, and solving the core linear system using both direct and iterative methods. We describe a number of applications of LP specific to US Department of Energy mission areas and we summarize our efforts to integrate parPCx (and parallel LP solvers in general) into Sandia's massively-parallel integer programming solver PICO (Parallel Interger and Combinatorial Optimizer). We
A Novel Implementation of Massively Parallel Three Dimensional Monte Carlo Radiation Transport
NASA Astrophysics Data System (ADS)
Robinson, P. B.; Peterson, J. D. L.
2005-12-01
The goal of our summer project was to implement the difference formulation for radiation transport into Cosmos++, a multidimensional, massively parallel, magneto hydrodynamics code for astrophysical applications (Peter Anninos - AX). The difference formulation is a new method for Symbolic Implicit Monte Carlo thermal transport (Brooks and Szöke - PAT). Formerly, simultaneous implementation of fully implicit Monte Carlo radiation transport in multiple dimensions on multiple processors had not been convincingly demonstrated. We found that a combination of the difference formulation and the inherent structure of Cosmos++ makes such an implementation both accurate and straightforward. We developed a "nearly nearest neighbor physics" technique to allow each processor to work independently, even with a fully implicit code. This technique coupled with the increased accuracy of an implicit Monte Carlo solution and the efficiency of parallel computing systems allows us to demonstrate the possibility of massively parallel thermal transport. This work was performed under the auspices of the U.S. Department of Energy by University of California Lawrence Livermore National Laboratory under contract No. W-7405-Eng-48
NASA Technical Reports Server (NTRS)
Barnden, John; Srinivas, Kankanahalli
1990-01-01
Symbol manipulation as used in traditional Artificial Intelligence has been criticized by neural net researchers for being excessively inflexible and sequential. On the other hand, the application of neural net techniques to the types of high-level cognitive processing studied in traditional artificial intelligence presents major problems as well. A promising way out of this impasse is to build neural net models that accomplish massively parallel case-based reasoning. Case-based reasoning, which has received much attention recently, is essentially the same as analogy-based reasoning, and avoids many of the problems leveled at traditional artificial intelligence. Further problems are avoided by doing many strands of case-based reasoning in parallel, and by implementing the whole system as a neural net. In addition, such a system provides an approach to some aspects of the problems of noise, uncertainty and novelty in reasoning systems. The current neural net system (Conposit), which performs standard rule-based reasoning, is being modified into a massively parallel case-based reasoning version.
Massively parallel regularized 3D inversion of potential fields on CPUs and GPUs
NASA Astrophysics Data System (ADS)
Čuma, Martin; Zhdanov, Michael S.
2014-01-01
We have recently introduced a massively parallel regularized 3D inversion of potential fields data. This program takes as an input gravity or magnetic vector, tensor and Total Magnetic Intensity (TMI) measurements and produces 3D volume of density, susceptibility, or three dimensional magnetization vector, the latest also including magnetic remanence information. The code uses combined MPI and OpenMP approach that maps well onto current multiprocessor multicore clusters and exhibits nearly linear strong and weak parallel scaling. It has been used to invert regional to continental size data sets with up to billion cells of the 3D Earth's volume on large clusters for interpretation of large airborne gravity and magnetics surveys. In this paper we explain the features that made this massive parallelization feasible and extend the code to add GPU support in the form of the OpenACC directives. This implementation resulted in up to a 22x speedup as compared to the scalar multithreaded implementation on a 12 core Intel CPU based computer node. Furthermore, we also introduce a mixed single-double precision approach, which allows us to perform most of the calculation at a single floating point number precision while keeping the result as precise as if the double precision had been used. This approach provides an additional 40% speedup on the GPUs, as compared to the pure double precision implementation. It also has about half of the memory footprint of the fully double precision version.
A cost-effective methodology for the design of massively-parallel VLSI functional units
NASA Technical Reports Server (NTRS)
Venkateswaran, N.; Sriram, G.; Desouza, J.
1993-01-01
In this paper we propose a generalized methodology for the design of cost-effective massively-parallel VLSI Functional Units. This methodology is based on a technique of generating and reducing a massive bit-array on the mask-programmable PAcube VLSI array. This methodology unifies (maintains identical data flow and control) the execution of complex arithmetic functions on PAcube arrays. It is highly regular, expandable and uniform with respect to problem-size and wordlength, thereby reducing the communication complexity. The memory-functional unit interface is regular and expandable. Using this technique functional units of dedicated processors can be mask-programmed on the naked PAcube arrays, reducing the turn-around time. The production cost of such dedicated processors can be drastically reduced since the naked PAcube arrays can be mass-produced. Analysis of the the performance of functional units designed by our method yields promising results.
NASA Astrophysics Data System (ADS)
Plaza, Antonio; Chang, Chein-I.; Plaza, Javier; Valencia, David
2006-05-01
The incorporation of hyperspectral sensors aboard airborne/satellite platforms is currently producing a nearly continual stream of multidimensional image data, and this high data volume has soon introduced new processing challenges. The price paid for the wealth spatial and spectral information available from hyperspectral sensors is the enormous amounts of data that they generate. Several applications exist, however, where having the desired information calculated quickly enough for practical use is highly desirable. High computing performance of algorithm analysis is particularly important in homeland defense and security applications, in which swift decisions often involve detection of (sub-pixel) military targets (including hostile weaponry, camouflage, concealment, and decoys) or chemical/biological agents. In order to speed-up computational performance of hyperspectral imaging algorithms, this paper develops several fast parallel data processing techniques. Techniques include four classes of algorithms: (1) unsupervised classification, (2) spectral unmixing, and (3) automatic target recognition, and (4) onboard data compression. A massively parallel Beowulf cluster (Thunderhead) at NASA's Goddard Space Flight Center in Maryland is used to measure parallel performance of the proposed algorithms. In order to explore the viability of developing onboard, real-time hyperspectral data compression algorithms, a Xilinx Virtex-II field programmable gate array (FPGA) is also used in experiments. Our quantitative and comparative assessment of parallel techniques and strategies may help image analysts in selection of parallel hyperspectral algorithms for specific applications.
Scalable load balancing for massively parallel distributed Monte Carlo particle transport
O'Brien, M. J.; Brantley, P. S.; Joy, K. I.
2013-07-01
In order to run computer simulations efficiently on massively parallel computers with hundreds of thousands or millions of processors, care must be taken that the calculation is load balanced across the processors. Examining the workload of every processor leads to an unscalable algorithm, with run time at least as large as O(N), where N is the number of processors. We present a scalable load balancing algorithm, with run time 0(log(N)), that involves iterated processor-pair-wise balancing steps, ultimately leading to a globally balanced workload. We demonstrate scalability of the algorithm up to 2 million processors on the Sequoia supercomputer at Lawrence Livermore National Laboratory. (authors)
Direct methods for banded linear systems on massively parallel processor computers
Arbenz, P.; Gander, W.
1995-12-01
The authors discuss direct methods for solving systems of linear equations Ax = b, A {element_of} lR{sup nxn}, on massively parallel processor (MPP) computers. Here, A is a real banded n x n matrix with lower and upper half-bandwidth r and s, respectively. We assume that the matrix A has a narrow band, meaning r + s << n. Only in this case, it is worthwhile taking into account the zero structure of A, i.e. store the matrix by diagonals and modify algorithms.
Estimating water flow through a hillslope using the massively parallel processor
NASA Technical Reports Server (NTRS)
Devaney, Judy E.; Camillo, P. J.; Gurney, R. J.
1988-01-01
A new two-dimensional model of water flow in a hillslope has been implemented on the Massively Parallel Processor at the Goddard Space Flight Center. Flow in the soil both in the saturated and unsaturated zones, evaporation and overland flow are all modelled, and the rainfall rates are allowed to vary spatially. Previous models of this type had always been very limited computationally. This model takes less than a minute to model all the components of the hillslope water flow for a day. The model can now be used in sensitivity studies to specify which measurements should be taken and how accurate they should be to describe such flows for environmental studies.
Stochastic simulation of charged particle transport on the massively parallel processor
NASA Technical Reports Server (NTRS)
Earl, James A.
1988-01-01
Computations of cosmic-ray transport based upon finite-difference methods are afflicted by instabilities, inaccuracies, and artifacts. To avoid these problems, researchers developed a Monte Carlo formulation which is closely related not only to the finite-difference formulation, but also to the underlying physics of transport phenomena. Implementations of this approach are currently running on the Massively Parallel Processor at Goddard Space Flight Center, whose enormous computing power overcomes the poor statistical accuracy that usually limits the use of stochastic methods. These simulations have progressed to a stage where they provide a useful and realistic picture of solar energetic particle propagation in interplanetary space.
Block iterative restoration of astronomical images with the massively parallel processor
NASA Technical Reports Server (NTRS)
Heap, Sara R.; Lindler, Don J.
1987-01-01
A method is described for algebraic image restoration capable of treating astronomical images. For a typical 500 x 500 image, direct algebraic restoration would require the solution of a 250,000 x 250,000 linear system. The block iterative approach is used to reduce the problem to solving 4900 121 x 121 linear systems. The algorithm was implemented on the Goddard Massively Parallel Processor, which can solve a 121 x 121 system in approximately 0.06 seconds. Examples are shown of the results for various astronomical images.
A Massively Parallel Solver for the Mechanical Harmonic Analysis of Accelerator Cavities
O. Kononenko
2015-02-17
ACE3P is a 3D massively parallel simulation suite that developed at SLAC National Accelerator Laboratory that can perform coupled electromagnetic, thermal and mechanical study. Effectively utilizing supercomputer resources, ACE3P has become a key simulation tool for particle accelerator R and D. A new frequency domain solver to perform mechanical harmonic response analysis of accelerator components is developed within the existing parallel framework. This solver is designed to determine the frequency response of the mechanical system to external harmonic excitations for time-efficient accurate analysis of the large-scale problems. Coupled with the ACE3P electromagnetic modules, this capability complements a set of multi-physics tools for a comprehensive study of microphonics in superconducting accelerating cavities in order to understand the RF response and feedback requirements for the operational reliability of a particle accelerator. (auth)
Pandya, Tara M.; Johnson, Seth R.; Evans, Thomas M.; Davidson, Gregory G.; Hamilton, Steven P.; Godfrey, Andrew T.
2015-12-21
This paper discusses the implementation, capabilities, and validation of Shift, a massively parallel Monte Carlo radiation transport package developed and maintained at Oak Ridge National Laboratory. It has been developed to scale well from laptop to small computing clusters to advanced supercomputers. Special features of Shift include hybrid capabilities for variance reduction such as CADIS and FW-CADIS, and advanced parallel decomposition and tally methods optimized for scalability on supercomputing architectures. Shift has been validated and verified against various reactor physics benchmarks and compares well to other state-of-the-art Monte Carlo radiation transport codes such as MCNP5, CE KENO-VI, and OpenMC. Somemore » specific benchmarks used for verification and validation include the CASL VERA criticality test suite and several Westinghouse AP1000® problems. These benchmark and scaling studies show promising results.« less
Pandya, Tara M.; Johnson, Seth R.; Evans, Thomas M.; Davidson, Gregory G.; Hamilton, Steven P.; Godfrey, Andrew T.
2015-12-21
This paper discusses the implementation, capabilities, and validation of Shift, a massively parallel Monte Carlo radiation transport package developed and maintained at Oak Ridge National Laboratory. It has been developed to scale well from laptop to small computing clusters to advanced supercomputers. Special features of Shift include hybrid capabilities for variance reduction such as CADIS and FW-CADIS, and advanced parallel decomposition and tally methods optimized for scalability on supercomputing architectures. Shift has been validated and verified against various reactor physics benchmarks and compares well to other state-of-the-art Monte Carlo radiation transport codes such as MCNP5, CE KENO-VI, and OpenMC. Some specific benchmarks used for verification and validation include the CASL VERA criticality test suite and several Westinghouse AP1000^{®} problems. These benchmark and scaling studies show promising results.
NASA Technical Reports Server (NTRS)
Treinish, Lloyd A.; Gough, Michael L.; Wildenhain, W. David
1987-01-01
The capability was developed of rapidly producing visual representations of large, complex, multi-dimensional space and earth sciences data sets via the implementation of computer graphics modeling techniques on the Massively Parallel Processor (MPP) by employing techniques recently developed for typically non-scientific applications. Such capabilities can provide a new and valuable tool for the understanding of complex scientific data, and a new application of parallel computing via the MPP. A prototype system with such capabilities was developed and integrated into the National Space Science Data Center's (NSSDC) Pilot Climate Data System (PCDS) data-independent environment for computer graphics data display to provide easy access to users. While developing these capabilities, several problems had to be solved independently of the actual use of the MPP, all of which are outlined.
NASA Astrophysics Data System (ADS)
Pandya, Tara M.; Johnson, Seth R.; Evans, Thomas M.; Davidson, Gregory G.; Hamilton, Steven P.; Godfrey, Andrew T.
2016-03-01
This work discusses the implementation, capabilities, and validation of Shift, a massively parallel Monte Carlo radiation transport package authored at Oak Ridge National Laboratory. Shift has been developed to scale well from laptops to small computing clusters to advanced supercomputers and includes features such as support for multiple geometry and physics engines, hybrid capabilities for variance reduction methods such as the Consistent Adjoint-Driven Importance Sampling methodology, advanced parallel decompositions, and tally methods optimized for scalability on supercomputing architectures. The scaling studies presented in this paper demonstrate good weak and strong scaling behavior for the implemented algorithms. Shift has also been validated and verified against various reactor physics benchmarks, including the Consortium for Advanced Simulation of Light Water Reactors' Virtual Environment for Reactor Analysis criticality test suite and several Westinghouse AP1000® problems presented in this paper. These benchmark results compare well to those from other contemporary Monte Carlo codes such as MCNP5 and KENO.
Massively Parallel Computation of Soil Surface Roughness Parameters on A Fermi GPU
NASA Astrophysics Data System (ADS)
Li, Xiaojie; Song, Changhe
2016-06-01
Surface roughness is description of the surface micro topography of randomness or irregular. The standard deviation of surface height and the surface correlation length describe the statistical variation for the random component of a surface height relative to a reference surface. When the number of data points is large, calculation of surface roughness parameters is time-consuming. With the advent of Graphics Processing Unit (GPU) architectures, inherently parallel problem can be effectively solved using GPUs. In this paper we propose a GPU-based massively parallel computing method for 2D bare soil surface roughness estimation. This method was applied to the data collected by the surface roughness tester based on the laser triangulation principle during the field experiment in April 2012. The total number of data points was 52,040. It took 47 seconds on a Fermi GTX 590 GPU whereas its serial CPU version took 5422 seconds, leading to a significant 115x speedup.
DGDFT: A massively parallel method for large scale density functional theory calculations
Hu, Wei Yang, Chao; Lin, Lin
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{sup −4} Hartree/atom in terms of the error of energy and 6.2 × 10{sup −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.
Massively Parallel and Scalable Implicit Time Integration Algorithms for Structural Dynamics
NASA Technical Reports Server (NTRS)
Farhat, Charbel
1997-01-01
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 of the following additional facts: (a) explicit schemes are easier to parallelize than implicit ones, and (b) explicit schemes induce short range interprocessor communications that are relatively inexpensive, while the factorization methods used in most implicit schemes induce long range interprocessor communications that often ruin the sought-after speed-up. However, the time step restriction imposed by the Courant stability condition on all explicit schemes cannot yet be offset by the speed of the currently available parallel hardware. Therefore, it is essential to develop efficient 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 the low-frequency dynamics of aerospace structures.
Massively parallel simulation of flow and transport in variably saturated porous and fractured media
Wu, Yu-Shu; Zhang, Keni; Pruess, Karsten
2002-01-15
This paper describes a massively parallel simulation method and its application for modeling multiphase flow and multicomponent transport in porous and fractured reservoirs. The parallel-computing method has been implemented into the TOUGH2 code and its numerical performance is tested on a Cray T3E-900 and IBM SP. The efficiency and robustness of the parallel-computing algorithm are demonstrated by completing two simulations with more than one million gridblocks, using site-specific data obtained from a site-characterization study. The first application involves the development of a three-dimensional numerical model for flow in the unsaturated zone of Yucca Mountain, Nevada. The second application is the study of tracer/radionuclide transport through fracture-matrix rocks for the same site. The parallel-computing technique enhances modeling capabilities by achieving several-orders-of-magnitude speedup for large-scale and high resolution modeling studies. The resulting modeling results provide many new insights into flow and transport processes that could not be obtained from simulations using the single-CPU simulator.
Seismic waves modeling with the Fourier pseudo-spectral method on massively parallel machines.
NASA Astrophysics Data System (ADS)
Klin, Peter
2015-04-01
The Fourier pseudo-spectral method (FPSM) is an approach for the 3D numerical modeling of the wave propagation, which is based on the discretization of the spatial domain in a structured grid and relies on global spatial differential operators for the solution of the wave equation. This last peculiarity is advantageous from the accuracy point of view but poses difficulties for an efficient implementation of the method to be run on parallel computers with distributed memory architecture. The 1D spatial domain decomposition approach has been so far commonly adopted in the parallel implementations of the FPSM, but it implies an intensive data exchange among all the processors involved in the computation, which can degrade the performance because of communication latencies. Moreover, the scalability of the 1D domain decomposition is limited, since the number of processors can not exceed the number of grid points along the directions in which the domain is partitioned. This limitation inhibits an efficient exploitation of the computational environments with a very large number of processors. In order to overcome the limitations of the 1D domain decomposition we implemented a parallel version of the FPSM based on a 2D domain decomposition, which allows to achieve a higher degree of parallelism and scalability on massively parallel machines with several thousands of processing elements. The parallel programming is essentially achieved using the MPI protocol but OpenMP parts are also included in order to exploit the single processor multi - threading capabilities, when available. The developed tool is aimed at the numerical simulation of the seismic waves propagation and in particular is intended for earthquake ground motion research. We show the scalability tests performed up to 16k processing elements on the IBM Blue Gene/Q computer at CINECA (Italy), as well as the application to the simulation of the earthquake ground motion in the alluvial plain of the Po river (Italy).
Mardis, Elaine R
2009-01-01
A variety of techniques that specifically target human gene sequences for differential capture from a genomic sample, coupled with next-generation, massively parallel DNA sequencing instruments, is rapidly supplanting the combination of polymerase chain reaction and capillary sequencing to discover coding variants in medically relevant samples. These studies are most appropriate for the sample numbers necessary to identify both common and rare single nucleotide variants, as well as small insertion or deletion events, which may cause complex inherited diseases. The same massively parallel sequencers are simultaneously being used for whole-genome resequencing and comprehensive, genome-wide variant discovery in studies of somatic diseases such as cancer. Viral and microbial researchers are using next-generation sequences to identify unknown etiologic agents in human diseases, to study the viral and microbial species that occupy surfaces of the human body, and to inform the clinical management of chronic infectious diseases such as human immunodeficiency virus (HIV). Taken together, these approaches are dramatically accelerating the pace of human disease research and are already impacting patient care. PMID:19435481
Madduri, Kamesh; Ediger, David; Jiang, Karl; Bader, David A.; Chavarría-Miranda, Daniel
2009-05-29
We present a new lock-free parallel algorithm for computing betweenness centrality of massive small-world networks. With minor changes to the data structures, our algorithm also achieves better spatial cache locality compared to previous approaches. Betweenness centrality is a key algorithm kernel in the HPCS SSCA#2 Graph Analysis benchmark, which has been extensively used to evaluate the performance of emerging high-performance computing architectures for graph-theoretic computations. We design optimized implementations of betweenness centrality and the SSCA#2 benchmark for two hardware multithreaded systems: a Cray XMT system with the ThreadStorm processor, and a single-socket Sun multicore server with the UltraSparc T2 processor. For a small-world network of 134 million vertices and 1.073 billion edges, the 16-processor XMT system and the 8-core Sun Fire T5120 server achieve TEPS scores (an algorithmic performance count for the SSCA#2 benchmark) of 160 million and 90 million respectively, which corresponds to more than a 2X performance improvement over the previous parallel implementations. To better characterize the performance of these multithreaded systems, we correlate the SSCA#2 performance results with data from the memory-intensive STREAM and RandomAccess benchmarks. Finally, we demonstrate the applicability of our implementation to analyze massive real-world datasets by computing approximate betweenness centrality for a large-scale IMDb movie-actor network.
Madduri, Kamesh; Ediger, David; Jiang, Karl; Bader, David A.; Chavarria-Miranda, Daniel
2009-02-15
We present a new lock-free parallel algorithm for computing betweenness centralityof massive small-world networks. With minor changes to the data structures, ouralgorithm also achieves better spatial cache locality compared to previous approaches. Betweenness centrality is a key algorithm kernel in HPCS SSCA#2, a benchmark extensively used to evaluate the performance of emerging high-performance computing architectures for graph-theoretic computations. We design optimized implementations of betweenness centrality and the SSCA#2 benchmark for two hardware multithreaded systems: a Cray XMT system with the Threadstorm processor, and a single-socket Sun multicore server with the UltraSPARC T2 processor. For a small-world network of 134 million vertices and 1.073 billion edges, the 16-processor XMT system and the 8-core Sun Fire T5120 server achieve TEPS scores (an algorithmic performance count for the SSCA#2 benchmark) of 160 million and 90 million respectively, which corresponds to more than a 2X performance improvement over the previous parallel implementations. To better characterize the performance of these multithreaded systems, we correlate the SSCA#2 performance results with data from the memory-intensive STREAM and RandomAccess benchmarks. Finally, we demonstrate the applicability of our implementation to analyze massive real-world datasets by computing approximate betweenness centrality for a large-scale IMDb movie-actor network.
On distributed memory MPI-based parallelization of SPH codes in massive HPC context
NASA Astrophysics Data System (ADS)
Oger, G.; Le Touzé, D.; Guibert, D.; de Leffe, M.; Biddiscombe, J.; Soumagne, J.; Piccinali, J.-G.
2016-03-01
Most of particle methods share the problem of high computational cost and in order to satisfy the demands of solvers, currently available hardware technologies must be fully exploited. Two complementary technologies are now accessible. On the one hand, CPUs which can be structured into a multi-node framework, allowing massive data exchanges through a high speed network. In this case, each node is usually comprised of several cores available to perform multithreaded computations. On the other hand, GPUs which are derived from the graphics computing technologies, able to perform highly multi-threaded calculations with hundreds of independent threads connected together through a common shared memory. This paper is primarily dedicated to the distributed memory parallelization of particle methods, targeting several thousands of CPU cores. The experience gained clearly shows that parallelizing a particle-based code on moderate numbers of cores can easily lead to an acceptable scalability, whilst a scalable speedup on thousands of cores is much more difficult to obtain. The discussion revolves around speeding up particle methods as a whole, in a massive HPC context by making use of the MPI library. We focus on one particular particle method which is Smoothed Particle Hydrodynamics (SPH), one of the most widespread today in the literature as well as in engineering.
Massively Parallel Dantzig-Wolfe Decomposition Applied to Traffic Flow Scheduling
NASA Technical Reports Server (NTRS)
Rios, Joseph Lucio; Ross, Kevin
2009-01-01
Optimal scheduling of air traffic over the entire National Airspace System is a computationally difficult task. To speed computation, Dantzig-Wolfe decomposition is applied to a known linear integer programming approach for assigning delays to flights. The optimization model is proven to have the block-angular structure necessary for Dantzig-Wolfe decomposition. The subproblems for this decomposition are solved in parallel via independent computation threads. Experimental evidence suggests that as the number of subproblems/threads increases (and their respective sizes decrease), the solution quality, convergence, and runtime improve. A demonstration of this is provided by using one flight per subproblem, which is the finest possible decomposition. This results in thousands of subproblems and associated computation threads. This massively parallel approach is compared to one with few threads and to standard (non-decomposed) approaches in terms of solution quality and runtime. Since this method generally provides a non-integral (relaxed) solution to the original optimization problem, two heuristics are developed to generate an integral solution. Dantzig-Wolfe followed by these heuristics can provide a near-optimal (sometimes optimal) solution to the original problem hundreds of times faster than standard (non-decomposed) approaches. In addition, when massive decomposition is employed, the solution is shown to be more likely integral, which obviates the need for an integerization step. These results indicate that nationwide, real-time, high fidelity, optimal traffic flow scheduling is achievable for (at least) 3 hour planning horizons.
Transcriptional analysis of endocrine disruption using zebrafish and massively parallel sequencing
Baker, Michael E.; Hardiman, Gary
2014-01-01
Endocrine disrupting chemicals (EDCs) including plasticizers, pesticides, detergents and pharmaceuticals, affect a variety of hormone-regulated physiological pathways in humans and wildlife. Many EDCs are lipophilic molecules and bind to hydrophobic pockets in steroid receptors, such as the estrogen receptor and androgen receptor, which are important in vertebrate reproduction and development. Indeed, health effects attributed to EDCs include reproductive dysfunction (e.g., reduced fertility, reproductive tract abnormalities and skewed male/female sex ratios in fish), early puberty, various cancers and obesity. A major concern is the effects of exposure to low concentrations of endocrine disruptors in utero and post partum, which may increase the incidence of cancer and diabetes in adults. EDCs affect transcription of hundreds and even thousands of genes, which has created the need for new tools to monitor the global effects of EDCs. The emergence of massive parallel sequencing for investigating gene transcription provides a sensitive tool for monitoring the effects of EDCs on humans and other vertebrates as well as elucidating the mechanism of action of EDCs. Zebrafish conserve many developmental pathways found in humans, which makes zebrafish a valuable model system for studying EDCs especially on early organ development because their embryos are translucent. In this article we review recent advances in massive parallel sequencing approaches with a focus on zebrafish. We make the case that zebrafish exposed to EDCs at different stages of development, can provide important insights on EDC effects on human health. PMID:24850832
A massively parallel semi-Lagrangian algorithm for solving the transport equation
Manson, Russell; Wang, Dali
2010-01-01
The scalar transport equation underpins many models employed in science, engineering, technology and business. Application areas include, but are not restricted to, pollution transport, weather forecasting, video analysis and encoding (the optical flow equation), options and stock pricing (the Black-Scholes equation) and spatially explicit ecological models. Unfortunately finding numerical solutions to this equation which are fast and accurate is not trivial. Moreover, finding such numerical algorithms that can be implemented on high performance computer architectures efficiently is challenging. In this paper the authors describe a massively parallel algorithm for solving the advection portion of the transport equation. We present an approach here which is different to that used in most transport models and which we have tried and tested for various scenarios. The approach employs an intelligent domain decomposition based on the vector field of the system equations and thus automatically partitions the computational domain into algorithmically autonomous regions. The solution of a classic pure advection transport problem is shown to be conservative, monotonic and highly accurate at large time steps. Additionally we demonstrate that the algorithm is highly efficient for high performance computer architectures and thus offers a route towards massively parallel application.
O'keefe, Matthew; Parr, Terence; Edgar, B. Kevin; Anderson, Steve; Woodward, Paul; Dietz, Hank
1995-01-01
Massively parallel processors (MPPs) hold the promise of extremely high performance that, if realized, could be used to study problems of unprecedented size and complexity. One of the primary stumbling blocks to this promise has been the lack of tools to translate application codes to MPP form. In this article we show how applications codes written in a subset of Fortran 77, called Fortran-P, can be translated to achieve good performance on several massively parallel machines. This subset can express codes that are self-similar, where the algorithm applied to the global data domain is also applied to each subdomain. Wemore » have found many codes that match the Fortran-P programming style and have converted them using our tools. We believe a self-similar coding style will accomplish what a vectorizable style has accomplished for vector machines by allowing the construction of robust, user-friendly, automatic translation systems that increase programmer productivity and generate fast, efficient code for MPPs.« less
Schultheis, Anne M; Ng, Charlotte K Y; De Filippo, Maria R; Piscuoglio, Salvatore; Macedo, Gabriel S; Gatius, Sonia; Perez Mies, Belen; Soslow, Robert A; Lim, Raymond S; Viale, Agnes; Huberman, Kety H; Palacios, Jose C; Reis-Filho, Jorge S; Matias-Guiu, Xavier; Weigelt, Britta
2016-06-01
Synchronous early-stage endometrioid endometrial carcinomas (EECs) and endometrioid ovarian carcinomas (EOCs) are associated with a favorable prognosis and have been suggested to represent independent primary tumors rather than metastatic disease. We subjected sporadic synchronous EECs/EOCs from five patients to whole-exome massively parallel sequencing, which revealed that the EEC and EOC of each case displayed strikingly similar repertoires of somatic mutations and gene copy number alterations. Despite the presence of mutations restricted to the EEC or EOC in each case, we observed that the mutational processes that shaped their respective genomes were consistent. High-depth targeted massively parallel sequencing of sporadic synchronous EECs/EOCs from 17 additional patients confirmed that these lesions are clonally related. In an additional Lynch Syndrome case, however, the EEC and EOC were found to constitute independent cancers lacking somatic mutations in common. Taken together, sporadic synchronous EECs/EOCs are clonally related and likely constitute dissemination from one site to the other. PMID:26832770
MADmap: A Massively Parallel Maximum-Likelihood Cosmic Microwave Background Map-Maker
Cantalupo, Christopher; Borrill, Julian; Jaffe, Andrew; Kisner, Theodore; Stompor, Radoslaw
2009-06-09
MADmap is a software application used to produce maximum-likelihood images of the sky from time-ordered data which include correlated noise, such as those gathered by Cosmic Microwave Background (CMB) experiments. It works efficiently on platforms ranging from small workstations to the most massively parallel supercomputers. Map-making is a critical step in the analysis of all CMB data sets, and the maximum-likelihood approach is the most accurate and widely applicable algorithm; however, it is a computationally challenging task. This challenge will only increase with the next generation of ground-based, balloon-borne and satellite CMB polarization experiments. The faintness of the B-mode signal that these experiments seek to measure requires them to gather enormous data sets. MADmap is already being run on up to O(1011) time samples, O(108) pixels and O(104) cores, with ongoing work to scale to the next generation of data sets and supercomputers. We describe MADmap's algorithm based around a preconditioned conjugate gradient solver, fast Fourier transforms and sparse matrix operations. We highlight MADmap's ability to address problems typically encountered in the analysis of realistic CMB data sets and describe its application to simulations of the Planck and EBEX experiments. The massively parallel and distributed implementation is detailed and scaling complexities are given for the resources required. MADmap is capable of analysing the largest data sets now being collected on computing resources currently available, and we argue that, given Moore's Law, MADmap will be capable of reducing the most massive projected data sets.
ASSET: Analysis of Sequences of Synchronous Events in Massively Parallel Spike Trains.
Torre, Emiliano; Canova, Carlos; Denker, Michael; Gerstein, George; Helias, Moritz; Grün, Sonja
2016-07-01
With the ability to observe the activity from large numbers of neurons simultaneously using modern recording technologies, the chance to identify sub-networks involved in coordinated processing increases. Sequences of synchronous spike events (SSEs) constitute one type of such coordinated spiking that propagates activity in a temporally precise manner. The synfire chain was proposed as one potential model for such network processing. Previous work introduced a method for visualization of SSEs in massively parallel spike trains, based on an intersection matrix that contains in each entry the degree of overlap of active neurons in two corresponding time bins. Repeated SSEs are reflected in the matrix as diagonal structures of high overlap values. The method as such, however, leaves the task of identifying these diagonal structures to visual inspection rather than to a quantitative analysis. Here we present ASSET (Analysis of Sequences of Synchronous EvenTs), an improved, fully automated method which determines diagonal structures in the intersection matrix by a robust mathematical procedure. The method consists of a sequence of steps that i) assess which entries in the matrix potentially belong to a diagonal structure, ii) cluster these entries into individual diagonal structures and iii) determine the neurons composing the associated SSEs. We employ parallel point processes generated by stochastic simulations as test data to demonstrate the performance of the method under a wide range of realistic scenarios, including different types of non-stationarity of the spiking activity and different correlation structures. Finally, the ability of the method to discover SSEs is demonstrated on complex data from large network simulations with embedded synfire chains. Thus, ASSET represents an effective and efficient tool to analyze massively parallel spike data for temporal sequences of synchronous activity. PMID:27420734
ASSET: Analysis of Sequences of Synchronous Events in Massively Parallel Spike Trains
Canova, Carlos; Denker, Michael; Gerstein, George; Helias, Moritz
2016-01-01
With the ability to observe the activity from large numbers of neurons simultaneously using modern recording technologies, the chance to identify sub-networks involved in coordinated processing increases. Sequences of synchronous spike events (SSEs) constitute one type of such coordinated spiking that propagates activity in a temporally precise manner. The synfire chain was proposed as one potential model for such network processing. Previous work introduced a method for visualization of SSEs in massively parallel spike trains, based on an intersection matrix that contains in each entry the degree of overlap of active neurons in two corresponding time bins. Repeated SSEs are reflected in the matrix as diagonal structures of high overlap values. The method as such, however, leaves the task of identifying these diagonal structures to visual inspection rather than to a quantitative analysis. Here we present ASSET (Analysis of Sequences of Synchronous EvenTs), an improved, fully automated method which determines diagonal structures in the intersection matrix by a robust mathematical procedure. The method consists of a sequence of steps that i) assess which entries in the matrix potentially belong to a diagonal structure, ii) cluster these entries into individual diagonal structures and iii) determine the neurons composing the associated SSEs. We employ parallel point processes generated by stochastic simulations as test data to demonstrate the performance of the method under a wide range of realistic scenarios, including different types of non-stationarity of the spiking activity and different correlation structures. Finally, the ability of the method to discover SSEs is demonstrated on complex data from large network simulations with embedded synfire chains. Thus, ASSET represents an effective and efficient tool to analyze massively parallel spike data for temporal sequences of synchronous activity. PMID:27420734
Katouda, Michio; Nakajima, Takahito
2013-12-10
A new algorithm for massively parallel calculations of electron correlation energy of large molecules based on the resolution of identity second-order Møller-Plesset perturbation (RI-MP2) technique is developed and implemented into the quantum chemistry software NTChem. In this algorithm, a Message Passing Interface (MPI) and Open Multi-Processing (OpenMP) hybrid parallel programming model is applied to attain efficient parallel performance on massively parallel supercomputers. An in-core storage scheme of intermediate data of three-center electron repulsion integrals utilizing the distributed memory is developed to eliminate input/output (I/O) overhead. The parallel performance of the algorithm is tested on massively parallel supercomputers such as the K computer (using up to 45 992 central processing unit (CPU) cores) and a commodity Intel Xeon cluster (using up to 8192 CPU cores). The parallel RI-MP2/cc-pVTZ calculation of two-layer nanographene sheets (C150H30)2 (number of atomic orbitals is 9640) is performed using 8991 node and 71 288 CPU cores of the K computer. PMID:26592275
User's Guide for TOUGH2-MP - A Massively Parallel Version of the TOUGH2 Code
Earth Sciences Division; Zhang, Keni; Zhang, Keni; Wu, Yu-Shu; Pruess, Karsten
2008-05-27
TOUGH2-MP is a massively parallel (MP) version of the TOUGH2 code, designed for computationally efficient parallel simulation of isothermal and nonisothermal flows of multicomponent, multiphase fluids in one, two, and three-dimensional porous and fractured media. In recent years, computational requirements have become increasingly intensive in large or highly nonlinear problems for applications in areas such as radioactive waste disposal, CO2 geological sequestration, environmental assessment and remediation, reservoir engineering, and groundwater hydrology. The primary objective of developing the parallel-simulation capability is to significantly improve the computational performance of the TOUGH2 family of codes. The particular goal for the parallel simulator is to achieve orders-of-magnitude improvement in computational time for models with ever-increasing complexity. TOUGH2-MP is designed to perform parallel simulation on multi-CPU computational platforms. An earlier version of TOUGH2-MP (V1.0) was based on the TOUGH2 Version 1.4 with EOS3, EOS9, and T2R3D modules, a software previously qualified for applications in the Yucca Mountain project, and was designed for execution on CRAY T3E and IBM SP supercomputers. The current version of TOUGH2-MP (V2.0) includes all fluid property modules of the standard version TOUGH2 V2.0. It provides computationally efficient capabilities using supercomputers, Linux clusters, or multi-core PCs, and also offers many user-friendly features. The parallel simulator inherits all process capabilities from V2.0 together with additional capabilities for handling fractured media from V1.4. This report provides a quick starting guide on how to set up and run the TOUGH2-MP program for users with a basic knowledge of running the (standard) version TOUGH2 code, The report also gives a brief technical description of the code, including a discussion of parallel methodology, code structure, as well as mathematical and numerical methods used
Microfluidic Reactor Array Device for Massively Parallel In-situ Synthesis of Oligonucleotides
Srivannavit, Onnop; Gulari, Mayurachat; Hua, Zhishan.; Gao, Xiaolian; Zhou, Xiaochuan; Hong, Ailing; Zhou, Tiecheng; Gulari, Erdogan
2009-01-01
We have designed and fabricated a microfluidic reactor array device for massively parallel in-situ synthesis of oligonucleotides (oDNA). The device is made of glass anodically bonded to silicon consisting of three level features: microreactors, microchannels and through inlet/outlet holes. Main challenges in the design of this device include preventing diffusion of photogenerated reagents upon activation and achieving uniform reagent flow through thousands of parallel reactors. The device embodies a simple and effective dynamic isolation mechanism which prevents the intermixing of active reagents between discrete microreactors. Depending on the design parameters, it is possible to achieve uniform flow and synthesis reaction in all of the reactors by proper design of the microreactors and the microchannels. We demonstrated the use of this device on a solution-based, light-directed parallel in-situ oDNA synthesis. We were able to synthesize long oDNA, up to 120 mers at stepwise yield of 98 %. The quality of our microfluidic oDNA microarray including sensitivity, signal noise, specificity, spot variation and accuracy was characterized. Our microfluidic reactor array devices show a great potential for genomics and proteomics researches. PMID:20161215
NASA Technical Reports Server (NTRS)
Morgan, Philip E.
2004-01-01
This final report contains reports of research related to the tasks "Scalable High Performance Computing: Direct and Lark-Eddy Turbulent FLow Simulations Using Massively Parallel Computers" and "Devleop High-Performance Time-Domain Computational Electromagnetics Capability for RCS Prediction, Wave Propagation in Dispersive Media, and Dual-Use Applications. The discussion of Scalable High Performance Computing reports on three objectives: validate, access scalability, and apply two parallel flow solvers for three-dimensional Navier-Stokes flows; develop and validate a high-order parallel solver for Direct Numerical Simulations (DNS) and Large Eddy Simulation (LES) problems; and Investigate and develop a high-order Reynolds averaged Navier-Stokes turbulence model. The discussion of High-Performance Time-Domain Computational Electromagnetics reports on five objectives: enhancement of an electromagnetics code (CHARGE) to be able to effectively model antenna problems; utilize lessons learned in high-order/spectral solution of swirling 3D jets to apply to solving electromagnetics project; transition a high-order fluids code, FDL3DI, to be able to solve Maxwell's Equations using compact-differencing; develop and demonstrate improved radiation absorbing boundary conditions for high-order CEM; and extend high-order CEM solver to address variable material properties. The report also contains a review of work done by the systems engineer.
Madduri, Kamesh; Bader, David A.
2009-02-15
Graph-theoretic abstractions are extensively used to analyze massive data sets. Temporal data streams from socioeconomic interactions, social networking web sites, communication traffic, and scientific computing can be intuitively modeled as graphs. We present the first study of novel high-performance combinatorial techniques for analyzing large-scale information networks, encapsulating dynamic interaction data in the order of billions of entities. We present new data structures to represent dynamic interaction networks, and discuss algorithms for processing parallel insertions and deletions of edges in small-world networks. With these new approaches, we achieve an average performance rate of 25 million structural updates per second and a parallel speedup of nearly28 on a 64-way Sun UltraSPARC T2 multicore processor, for insertions and deletions to a small-world network of 33.5 million vertices and 268 million edges. We also design parallel implementations of fundamental dynamic graph kernels related to connectivity and centrality queries. Our implementations are freely distributed as part of the open-source SNAP (Small-world Network Analysis and Partitioning) complex network analysis framework.
Displacement Current and the Generation of Parallel Electric Fields
Song Yan; Lysak, Robert L.
2006-04-14
We show for the first time the dynamical relationship between the generation of magnetic field-aligned electric field (E{sub parallel}) and the temporal changes and spatial gradients of magnetic and velocity shears, and the plasma density in Earth's magnetosphere. We predict that the signatures of reconnection and auroral particle acceleration should have a correlation with low plasma density, and a localized voltage drop (V{sub parallel}) should often be associated with a localized magnetic stress concentration. Previous interpretations of the E{sub parallel} generation are mostly based on the generalized Ohm's law, causing serious confusion in understanding the nature of reconnection and auroral acceleration.
Climate system modeling on massively parallel systems: LDRD Project 95-ERP-47 final report
Mirin, A.A.; Dannevik, W.P.; Chan, B.; Duffy, P.B.; Eltgroth, P.G.; Wehner, M.F.
1996-12-01
Global warming, acid rain, ozone depletion, and biodiversity loss are some of the major climate-related issues presently being addressed by climate and environmental scientists. Because unexpected changes in the climate could have significant effect on our economy, it is vitally important to improve the scientific basis for understanding and predicting the earth`s climate. The impracticality of modeling the earth experimentally in the laboratory together with the fact that the model equations are highly nonlinear has created a unique and vital role for computer-based climate experiments. However, today`s computer models, when run at desired spatial and temporal resolution and physical complexity, severely overtax the capabilities of our most powerful computers. Parallel processing offers significant potential for attaining increased performance and making tractable simulations that cannot be performed today. The principal goals of this project have been to develop and demonstrate the capability to perform large-scale climate simulations on high-performance computing systems (using methodology that scales to the systems of tomorrow), and to carry out leading-edge scientific calculations using parallelized models. The demonstration platform for these studies has been the 256-processor Cray-T3D located at Lawrence Livermore National Laboratory. Our plan was to undertake an ambitious program in optimization, proof-of-principle and scientific study. These goals have been met. We are now regularly using massively parallel processors for scientific study of the ocean and atmosphere, and preliminary parallel coupled ocean/atmosphere calculations are being carried out as well. Furthermore, our work suggests that it should be possible to develop an advanced comprehensive climate system model with performance scalable to the teraflops range. 9 refs., 3 figs.
Demonstration of EDA flow for massively parallel e-beam lithography
NASA Astrophysics Data System (ADS)
Brandt, P.; Belledent, J.; Tranquillin, C.; Figueiro, T.; Meunier, S.; Bayle, S.; Fay, A.; Milléquant, M.; Icard, B.; Wieland, M.
2014-03-01
Today's soaring complexity in pushing the limits of 193nm immersion lithography drives the development of other technologies. One of these alternatives is mask-less massively parallel electron beam lithography, (MP-EBL), a promising candidate in which future resolution needs can be fulfilled at competitive cost. MAPPER Lithography's MATRIX MP-EBL platform has currently entered an advanced stage of development. The first tool in this platform, the FLX 1200, will operate using more than 1,300 beams, each one writing a stripe 2.2μm wide. 0.2μm overlap from stripe to stripe is allocated for stitching. Each beam is composed of 49 individual sub-beams that can be blanked independently in order to write in a raster scan pixels onto the wafer.
Lehoucq, Richard B.; Salinger, Andrew G.
1999-08-01
We present an approach for determining the linear stability of steady states of PDEs on massively parallel computers. Linearizing the transient behavior around a steady state leads to a generalized eigenvalue problem. The eigenvalues with largest real part are calculated using Arnoldi's iteration driven by a novel implementation of the Cayley transformation to recast the problem as an ordinary eigenvalue problem. The Cayley transformation requires the solution of a linear system at each Arnoldi iteration, which must be done iteratively for the algorithm to scale with problem size. A representative model problem of 3D incompressible flow and heat transfer in a rotating disk reactor is used to analyze the effect of algorithmic parameters on the performance of the eigenvalue algorithm. Successful calculations of leading eigenvalues for matrix systems of order up to 4 million were performed, identifying the critical Grashof number for a Hopf bifurcation.
Massively Parallel Interrogation of the Effects of Gene Expression Levels on Fitness.
Keren, Leeat; Hausser, Jean; Lotan-Pompan, Maya; Vainberg Slutskin, Ilya; Alisar, Hadas; Kaminski, Sivan; Weinberger, Adina; Alon, Uri; Milo, Ron; Segal, Eran
2016-08-25
Data of gene expression levels across individuals, cell types, and disease states is expanding, yet our understanding of how expression levels impact phenotype is limited. Here, we present a massively parallel system for assaying the effect of gene expression levels on fitness in Saccharomyces cerevisiae by systematically altering the expression level of ∼100 genes at ∼100 distinct levels spanning a 500-fold range at high resolution. We show that the relationship between expression levels and growth is gene and environment specific and provides information on the function, stoichiometry, and interactions of genes. Wild-type expression levels in some conditions are not optimal for growth, and genes whose fitness is greatly affected by small changes in expression level tend to exhibit lower cell-to-cell variability in expression. Our study addresses a fundamental gap in understanding the functional significance of gene expression regulation and offers a framework for evaluating the phenotypic effects of expression variation. PMID:27545349
Moore, Richard A; Warren, René L; Freeman, J Douglas; Gustavsen, Julia A; Chénard, Caroline; Friedman, Jan M; Suttle, Curtis A; Zhao, Yongjun; Holt, Robert A
2011-01-01
Massively parallel sequencing technology now provides the opportunity to sample the transcriptome of a given tissue comprehensively. Transcripts at only a few copies per cell are readily detectable, allowing the discovery of low abundance viral and bacterial transcripts in human tissue samples. Here we describe an approach for mining large sequence data sets for the presence of microbial sequences. Further, we demonstrate the sensitivity of this approach by sequencing human RNA-seq libraries spiked with decreasing amounts of an RNA-virus. At a modest depth of sequencing, viral transcripts can be detected at frequencies less than 1 in 1,000,000. With current sequencing platforms approaching outputs of one billion reads per run, this is a highly sensitive method for detecting putative infectious agents associated with human tissues. PMID:21603639
A Massively Parallel Sparse Eigensolver for Structural Dynamics Finite Element Analysis
Day, David M.; Reese, G.M.
1999-05-01
Eigenanalysis is a critical component of structural dynamics which is essential for determinating the vibrational response of systems. This effort addresses the development of numerical algorithms associated with scalable eigensolver techniques suitable for use on massively parallel, distributed memory computers that are capable of solving large scale structural dynamics problems. An iterative Lanczos method was determined to be the best choice for the application. Scalability of the eigenproblem depends on scalability of the underlying linear solver. A multi-level solver (FETI) was selected as most promising for this component. Issues relating to heterogeneous materials, mechanisms and multipoint constraints have been examined, and the linear solver algorithm has been developed to incorporate features that result in a scalable, robust algorithm for practical structural dynamics applications. The resulting tools have been demonstrated on large problems representative of a weapon's system.
Inside the intraterrestrials: The deep biosphere seen through massively parallel sequencing
NASA Astrophysics Data System (ADS)
Biddle, J.
2009-12-01
Deeply buried marine sediments may house a large amount of the Earth’s microbial population. Initial studies based on 16S rRNA clone libraries suggest that these sediments contain unique phylotypes of microorganisms, particularly from the archaeal domain. Since this environment is so difficult to study, microbiologists are challenged to find ways to examine these populations remotely. A major approach taken to study this environment uses massively parallel sequencing to examine the inner genetic workings of these microorganisms after the sediment has been drilled. Both metagenomics and tagged amplicon sequencing have been employed on deep sediments, and initial results show that different geographic regions can be differentiated through genomics and also minor populations may cause major geochemical changes.
Simulating massively parallel electron beam inspection for sub-20 nm defects
NASA Astrophysics Data System (ADS)
Bunday, Benjamin D.; Mukhtar, Maseeh; Quoi, Kathy; Thiel, Brad; Malloy, Matt
2015-03-01
SEMATECH has initiated a program to develop massively-parallel electron beam defect inspection (MPEBI). Here we use JMONSEL simulations to generate expected imaging responses of chosen test cases of patterns and defects with ability to vary parameters for beam energy, spot size, pixel size, and/or defect material and form factor. The patterns are representative of the design rules for an aggressively-scaled FinFET-type design. With these simulated images and resulting shot noise, a signal-to-noise framework is developed, which relates to defect detection probabilities. Additionally, with this infrastructure the effect of detection chain noise and frequency dependent system response can be made, allowing for targeting of best recipe parameters for MPEBI validation experiments, ultimately leading to insights into how such parameters will impact MPEBI tool design, including necessary doses for defect detection and estimations of scanning speeds for achieving high throughput for HVM.
Massively parallel cis-regulatory analysis in the mammalian central nervous system
Shen, Susan Q.; Myers, Connie A.; Hughes, Andrew E.O.; Byrne, Leah C.; Flannery, John G.; Corbo, Joseph C.
2016-01-01
Cis-regulatory elements (CREs, e.g., promoters and enhancers) regulate gene expression, and variants within CREs can modulate disease risk. Next-generation sequencing has enabled the rapid generation of genomic data that predict the locations of CREs, but a bottleneck lies in functionally interpreting these data. To address this issue, massively parallel reporter assays (MPRAs) have emerged, in which barcoded reporter libraries are introduced into cells, and the resulting barcoded transcripts are quantified by next-generation sequencing. Thus far, MPRAs have been largely restricted to assaying short CREs in a limited repertoire of cultured cell types. Here, we present two advances that extend the biological relevance and applicability of MPRAs. First, we adapt exome capture technology to instead capture candidate CREs, thereby tiling across the targeted regions and markedly increasing the length of CREs that can be readily assayed. Second, we package the library into adeno-associated virus (AAV), thereby allowing delivery to target organs in vivo. As a proof of concept, we introduce a capture library of about 46,000 constructs, corresponding to roughly 3500 DNase I hypersensitive (DHS) sites, into the mouse retina by ex vivo plasmid electroporation and into the mouse cerebral cortex by in vivo AAV injection. We demonstrate tissue-specific cis-regulatory activity of DHSs and provide examples of high-resolution truncation mutation analysis for multiplex parsing of CREs. Our approach should enable massively parallel functional analysis of a wide range of CREs in any organ or species that can be infected by AAV, such as nonhuman primates and human stem cell–derived organoids. PMID:26576614
Architecture for next-generation massively parallel maskless lithography system (MPML2)
NASA Astrophysics Data System (ADS)
Su, Ming-Shing; Tsai, Kuen-Yu; Lu, Yi-Chang; Kuo, Yu-Hsuan; Pei, Ting-Hang; Yen, Jia-Yush
2010-03-01
Electron-beam lithography is promising for future manufacturing technology because it does not suffer from wavelength limits set by light sources. Since single electron-beam lithography systems have a common problem in throughput, a multi-electron-beam lithography (MEBL) system should be a feasible alternative using the concept of massive parallelism. In this paper, we evaluate the advantages and the disadvantages of different MEBL system architectures, and propose our novel Massively Parallel MaskLess Lithography System, MPML2. MPML2 system is targeting for cost-effective manufacturing at the 32nm node and beyond. The key structure of the proposed system is its beamlet array cells (BACs). Hundreds of BACs are uniformly arranged over the whole wafer area in the proposed system. Each BAC has a data processor and an array of beamlets, and each beamlet consists of an electron-beam source, a source controller, a set of electron lenses, a blanker, a deflector, and an electron detector. These essential parts of beamlets are integrated using MEMS technology, which increases the density of beamlets and reduces the system cost. The data processor in the BAC processes layout information coming off-chamber and dispatches them to the corresponding beamlet to control its ON/OFF status. High manufacturing cost of masks is saved in maskless lithography systems, however, immense mask data are needed to be handled and transmitted. Therefore, data compression technique is applied to reduce required transmission bandwidth. The compression algorithm is fast and efficient so that the real-time decoder can be implemented on-chip. Consequently, the proposed MPML2 can achieve 10 wafers per hour (WPH) throughput for 300mm-wafer systems.
Macro-scale phenomena of arterial coupled cells: a massively parallel simulation
Shaikh, Mohsin Ahmed; Wall, David J. N.; David, Tim
2012-01-01
Impaired mass transfer characteristics of blood-borne vasoactive species such as adenosine triphosphate in regions such as an arterial bifurcation have been hypothesized as a prospective mechanism in the aetiology of atherosclerotic lesions. Arterial endothelial cells (ECs) and smooth muscle cells (SMCs) respond differentially to altered local haemodynamics and produce coordinated macro-scale responses via intercellular communication. Using a computationally designed arterial segment comprising large populations of mathematically modelled coupled ECs and SMCs, we investigate their response to spatial gradients of blood-borne agonist concentrations and the effect of micro-scale-driven perturbation on the macro-scale. Altering homocellular (between same cell type) and heterocellular (between different cell types) intercellular coupling, we simulated four cases of normal and pathological arterial segments experiencing an identical gradient in the concentration of the agonist. Results show that the heterocellular calcium (Ca2+) coupling between ECs and SMCs is important in eliciting a rapid response when the vessel segment is stimulated by the agonist gradient. In the absence of heterocellular coupling, homocellular Ca2+ coupling between SMCs is necessary for propagation of Ca2+ waves from downstream to upstream cells axially. Desynchronized intracellular Ca2+ oscillations in coupled SMCs are mandatory for this propagation. Upon decoupling the heterocellular membrane potential, the arterial segment looses the inhibitory effect of ECs on the Ca2+ dynamics of the underlying SMCs. The full system comprises hundreds of thousands of coupled nonlinear ordinary differential equations simulated on the massively parallel Blue Gene architecture. The use of massively parallel computational architectures shows the capability of this approach to address macro-scale phenomena driven by elementary micro-scale components of the system. PMID:21920960
Weaver, R. P.; Gittings, M. L.
2004-01-01
The Los Alamos Crestone Project is part of the Department of Energy's (DOE) Accelerated Strategic Computing Initiative, or ASCI Program. The main goal of this software development project is to investigate the use of continuous adaptive mesh refinement (CAMR) techniques for application to problems of interest to the Laboratory. There are many code development efforts in the Crestone Project, both unclassified and classified codes. In this overview I will discuss the unclassified SAGE and the RAGE codes. The SAGE (SAIC adaptive grid Eulerian) code is a one-, two-, and three-dimensional multimaterial Eulerian massively parallel hydrodynamics code for use in solving a variety of high-deformation flow problems. The RAGE CAMR code is built from the SAGE code by adding various radiation packages, improved setup utilities and graphics packages and is used for problems in which radiation transport of energy is important. The goal of these massively-parallel versions of the codes is to run extremely large problems in a reasonable amount of calendar time. Our target is scalable performance to {approx}10,000 processors on a 1 billion CAMR computational cell problem that requires hundreds of variables per cell, multiple physics packages (e.g. radiation and hydrodynamics), and implicit matrix solves for each cycle. A general description of the RAGE code has been published in [l],[ 2], [3] and [4]. Currently, the largest simulations we do are three-dimensional, using around 500 million computation cells and running for literally months of calendar time using {approx}2000 processors. Current ASCI platforms range from several 3-teraOPS supercomputers to one 12-teraOPS machine at Lawrence Livermore National Laboratory, the White machine, and one 20-teraOPS machine installed at Los Alamos, the Q machine. Each machine is a system comprised of many component parts that must perform in unity for the successful run of these simulations. Key features of any massively parallel system
NASA Astrophysics Data System (ADS)
Schultz, A.
2010-12-01
3D forward solvers lie at the core of inverse formulations used to image the variation of electrical conductivity within the Earth's interior. This property is associated with variations in temperature, composition, phase, presence of volatiles, and in specific settings, the presence of groundwater, geothermal resources, oil/gas or minerals. The high cost of 3D solutions has been a stumbling block to wider adoption of 3D methods. Parallel algorithms for modeling frequency domain 3D EM problems have not achieved wide scale adoption, with emphasis on fairly coarse grained parallelism using MPI and similar approaches. The communications bandwidth as well as the latency required to send and receive network communication packets is a limiting factor in implementing fine grained parallel strategies, inhibiting wide adoption of these algorithms. Leading Graphics Processor Unit (GPU) companies now produce GPUs with hundreds of GPU processor cores per die. The footprint, in silicon, of the GPU's restricted instruction set is much smaller than the general purpose instruction set required of a CPU. Consequently, the density of processor cores on a GPU can be much greater than on a CPU. GPUs also have local memory, registers and high speed communication with host CPUs, usually through PCIe type interconnects. The extremely low cost and high computational power of GPUs provides the EM geophysics community with an opportunity to achieve fine grained (i.e. massive) parallelization of codes on low cost hardware. The current generation of GPUs (e.g. NVidia Fermi) provides 3 billion transistors per chip die, with nearly 500 processor cores and up to 6 GB of fast (DDR5) GPU memory. This latest generation of GPU supports fast hardware double precision (64 bit) floating point operations of the type required for frequency domain EM forward solutions. Each Fermi GPU board can sustain nearly 1 TFLOP in double precision, and multiple boards can be installed in the host computer system. We
NASA Astrophysics Data System (ADS)
Kumaki, Takeshi; Ishizaki, Masakatsu; Koide, Tetsushi; Mattausch, Hans Jürgen; Kuroda, Yasuto; Gyohten, Takayuki; Noda, Hideyuki; Dosaka, Katsumi; Arimoto, Kazutami; Saito, Kazunori
This paper presents an integration architecture of content addressable memory (CAM) and a massive-parallel memory-embedded SIMD matrix for constructing a versatile multimedia processor. The massive-parallel memory-embedded SIMD matrix has 2,048 2-bit processing elements, which are connected by a flexible switching network, and supports 2-bit 2,048-way bit-serial and word-parallel operations with a single command. The SIMD matrix architecture is verified to be a better way for processing the repeated arithmetic operation types in multimedia applications. The proposed architecture, reported in this paper, exploits in addition CAM technology and enables therefore fast pipelined table-lookup coding operations. Since both arithmetic and table-lookup operations execute extremely fast, the proposed novel architecture can realize consequently efficient and versatile multimedia data processing. Evaluation results of the proposed CAM-enhanced massive-parallel SIMD matrix processor for the example of the frequently used JPEG image-compression application show that the necessary clock cycle number can be reduced by 86% in comparison to a conventional mobile DSP architecture. The determined performances in Mpixel/mm2 are factors 3.3 and 4.4 better than with a CAM-less massive-parallel memory-embedded SIMD matrix processor and a conventional mobile DSP, respectively.
Multi-mode sensor processing on a dynamically reconfigurable massively parallel processor array
NASA Astrophysics Data System (ADS)
Chen, Paul; Butts, Mike; Budlong, Brad; Wasson, Paul
2008-04-01
This paper introduces a novel computing architecture that can be reconfigured in real time to adapt on demand to multi-mode sensor platforms' dynamic computational and functional requirements. This 1 teraOPS reconfigurable Massively Parallel Processor Array (MPPA) has 336 32-bit processors. The programmable 32-bit communication fabric provides streamlined inter-processor connections with deterministically high performance. Software programmability, scalability, ease of use, and fast reconfiguration time (ranging from microseconds to milliseconds) are the most significant advantages over FPGAs and DSPs. This paper introduces the MPPA architecture, its programming model, and methods of reconfigurability. An MPPA platform for reconfigurable computing is based on a structural object programming model. Objects are software programs running concurrently on hundreds of 32-bit RISC processors and memories. They exchange data and control through a network of self-synchronizing channels. A common application design pattern on this platform, called a work farm, is a parallel set of worker objects, with one input and one output stream. Statically configured work farms with homogeneous and heterogeneous sets of workers have been used in video compression and decompression, network processing, and graphics applications.
The divide-expand-consolidate MP2 scheme goes massively parallel
NASA Astrophysics Data System (ADS)
Kristensen, Kasper; Kjærgaard, Thomas; Høyvik, Ida-Marie; Ettenhuber, Patrick; Jørgensen, Poul; Jansik, Branislav; Reine, Simen; Jakowski, Jacek
2013-07-01
For large molecular systems conventional implementations of second order Møller-Plesset (MP2) theory encounter a scaling wall, both memory- and time-wise. We describe how this scaling wall can be removed. We present a massively parallel algorithm for calculating MP2 energies and densities using the divide-expand-consolidate scheme where a calculation on a large system is divided into many small fragment calculations employing local orbital spaces. The resulting algorithm is linear-scaling with system size, exhibits near perfect parallel scalability, removes memory bottlenecks and does not involve any I/O. The algorithm employs three levels of parallelisation combined via a dynamic job distribution scheme. Results on two molecular systems containing 528 and 1056 atoms (4278 and 8556 basis functions) using 47,120 and 94,240 cores are presented. The results demonstrate the scalability of the algorithm both with respect to the number of cores and with respect to system size. The presented algorithm is thus highly suited for large super computer architectures and allows MP2 calculations on large molecular systems to be carried out within a few hours - for example, the correlated calculation on the molecular system containing 1056 atoms took 2.37 hours using 94240 cores.
NASA Astrophysics Data System (ADS)
Nguyen, Trung Dac; Phillips, Carolyn L.; Anderson, Joshua A.; Glotzer, Sharon C.
2011-11-01
Molecular dynamics (MD) methods compute the trajectory of a system of point particles in response to a potential function by numerically integrating Newton's equations of motion. Extending these basic methods with rigid body constraints enables composite particles with complex shapes such as anisotropic nanoparticles, grains, molecules, and rigid proteins to be modeled. Rigid body constraints are added to the GPU-accelerated MD package, HOOMD-blue, version 0.10.0. The software can now simulate systems of particles, rigid bodies, or mixed systems in microcanonical (NVE), canonical (NVT), and isothermal-isobaric (NPT) ensembles. It can also apply the FIRE energy minimization technique to these systems. In this paper, we detail the massively parallel scheme that implements these algorithms and discuss how our design is tuned for the maximum possible performance. Two different case studies are included to demonstrate the performance attained, patchy spheres and tethered nanorods. In typical cases, HOOMD-blue on a single GTX 480 executes 2.5-3.6 times faster than LAMMPS executing the same simulation on any number of CPU cores in parallel. Simulations with rigid bodies may now be run with larger systems and for longer time scales on a single workstation than was previously even possible on large clusters.
A two-phase thermal model for subsurface transport on massively parallel computers
Martinez, M.J.; Hopkins, P.L.
1997-12-01
Many research activities in subsurface transport require the numerical simulation of multiphase flow in porous media. This capability is critical to research in environmental remediation (e.g. contaminations with dense, non-aqueous-phase liquids), nuclear waste management, reservoir engineering, and to the assessment of the future availability of groundwater in many parts of the world. This paper presents an unstructured grid numerical algorithm for subsurface transport in heterogeneous porous media implemented for use on massively parallel (MP) computers. The mathematical model considers nonisothermal two-phase (liquid/gas) flow, including capillary pressure effects, binary diffusion in the gas phase, conductive, latent, and sensible heat transport. The Galerkin finite element method is used for spatial discretization, and temporal integration is accomplished via a predictor/corrector scheme. Message-passing and domain decomposition techniques are used for implementing a scalable algorithm for distributed memory parallel computers. Illustrative applications are shown to demonstrate capabilities and performance, one of which is modeling hydrothermal transport at the Yucca Mountain site for a radioactive waste facility.
NASA Astrophysics Data System (ADS)
Li, J.; Zhang, T.; Huang, Q.; Liu, Q.
2014-12-01
Today's climate datasets are featured with large volume, high degree of spatiotemporal complexity and evolving fast overtime. As visualizing large volume distributed climate datasets is computationally intensive, traditional desktop based visualization applications fail to handle the computational intensity. Recently, scientists have developed remote visualization techniques to address the computational issue. Remote visualization techniques usually leverage server-side parallel computing capabilities to perform visualization tasks and deliver visualization results to clients through network. In this research, we aim to build a remote parallel visualization platform for visualizing and analyzing massive climate data. Our visualization platform was built based on Paraview, which is one of the most popular open source remote visualization and analysis applications. To further enhance the scalability and stability of the platform, we have employed cloud computing techniques to support the deployment of the platform. In this platform, all climate datasets are regular grid data which are stored in NetCDF format. Three types of data access methods are supported in the platform: accessing remote datasets provided by OpenDAP servers, accessing datasets hosted on the web visualization server and accessing local datasets. Despite different data access methods, all visualization tasks are completed at the server side to reduce the workload of clients. As a proof of concept, we have implemented a set of scientific visualization methods to show the feasibility of the platform. Preliminary results indicate that the framework can address the computation limitation of desktop based visualization applications.
Cazzaniga, Paolo; Nobile, Marco S.; Besozzi, Daniela; Bellini, Matteo; Mauri, Giancarlo
2014-01-01
The introduction of general-purpose Graphics Processing Units (GPUs) is boosting scientific applications in Bioinformatics, Systems Biology, and Computational Biology. In these fields, the use of high-performance computing solutions is motivated by the need of performing large numbers of in silico analysis to study the behavior of biological systems in different conditions, which necessitate a computing power that usually overtakes the capability of standard desktop computers. In this work we present coagSODA, a CUDA-powered computational tool that was purposely developed for the analysis of a large mechanistic model of the blood coagulation cascade (BCC), defined according to both mass-action kinetics and Hill functions. coagSODA allows the execution of parallel simulations of the dynamics of the BCC by automatically deriving the system of ordinary differential equations and then exploiting the numerical integration algorithm LSODA. We present the biological results achieved with a massive exploration of perturbed conditions of the BCC, carried out with one-dimensional and bi-dimensional parameter sweep analysis, and show that GPU-accelerated parallel simulations of this model can increase the computational performances up to a 181× speedup compared to the corresponding sequential simulations. PMID:25025072
Practical Realization of Massively Parallel Fiber -Free-Space Optical Interconnects
NASA Astrophysics Data System (ADS)
Gruber, Matthias; Jahns, Jürgen; El Joudi, El Mehdi; Sinzinger, Stefan
2001-06-01
We propose a novel approach to realizing massively parallel optical interconnects based on commercially available multifiber ribbons with MT-type connectors and custom-designed planar-integrated free-space components. It combines the advantages of fiber optics, that is, a long range and convenient and flexible installation, with those of (planar-integrated) free-space optics, that is, a wide range of implementable functions and a high potential for integration and parallelization. For the interface between fibers and free-space optical systems a low-cost practical solution is presented. It consists of using a metal connector plate that was manufactured on a computer-controlled milling machine. Channel densities are of the order of 100 /mm2 between optoelectronic VLSI chips and the free-space optical systems and 1 /mm2 between the free-space optical systems and MT-type fiber connectors. Experiments in combination with specially designed planar-integrated test systems prove that multiple one-to-one and one-to-many interconnects can be established with not more than 10% uniformity error.
Measures of effectiveness for BMD mid-course tracking on MIMD massively parallel computers
VanDyke, J.P.; Tomkins, J.L.; Furnish, M.D.
1995-05-01
The TRC code, a mid-course tracking code for ballistic missiles, has previously been implemented on a 1024-processor MIMD (Multiple Instruction -- Multiple Data) massively parallel computer. Measures of Effectiveness (MOE) for this algorithm have been developed for this computing environment. The MOE code is run in parallel with the TRC code. Particularly useful MOEs include the number of missed objects (real objects for which the TRC algorithm did not construct a track); of ghost tracks (tracks not corresponding to a real object); of redundant tracks (multiple tracks corresponding to a single real object); and of unresolved objects (multiple objects corresponding to a single track). All of these are expressed as a function of time, and tend to maximize during the time in which real objects are spawned (multiple reentry vehicles per post-boost vehicle). As well, it is possible to measure the track-truth separation as a function of time. A set of calculations is presented illustrating these MOEs as a function of time for a case with 99 post-boost vehicles, each of which spawns 9 reentry vehicles.
Bryant, Dean; Seckinger, Anja; Hose, Dirk; Zojer, Niklas; Sahota, Surinder S.
2015-01-01
Human multiple myeloma (MM) is characterized by accumulation of malignant terminally differentiated plasma cells (PCs) in the bone marrow (BM), raising the question when during maturation neoplastic transformation begins. Immunoglobulin IGHV genes carry imprints of clonal tumor history, delineating somatic hypermutation (SHM) events that generally occur in the germinal center (GC). Here, we examine MM-derived IGHV genes using massive parallel deep sequencing, comparing them with profiles in normal BM PCs. In 4/4 presentation IgG MM, monoclonal tumor-derived IGHV sequences revealed significant evidence for intraclonal variation (ICV) in mutation patterns. IGHV sequences of 2/2 normal PC IgG populations revealed dominant oligoclonal expansions, each expansion also displaying mutational ICV. Clonal expansions in MM and in normal BM PCs reveal common IGHV features. In such MM, the data fit a model of tumor origins in which neoplastic transformation is initiated in a GC B-cell committed to terminal differentiation but still targeted by on-going SHM. Strikingly, the data parallel IGHV clonal sequences in some monoclonal gammopathy of undetermined significance (MGUS) known to display on-going SHM imprints. Since MGUS generally precedes MM, these data suggest origins of MGUS and MM with IGHV gene mutational ICV from the same GC B-cell, arising via a distinctive pathway. PMID:25929340
GPAW - massively parallel electronic structure calculations with Python-based software.
Enkovaara, J.; Romero, N.; Shende, S.; Mortensen, J.
2011-01-01
Electronic structure calculations are a widely used tool in materials science and large consumer of supercomputing resources. Traditionally, the software packages for these kind of simulations have been implemented in compiled languages, where Fortran in its different versions has been the most popular choice. While dynamic, interpreted languages, such as Python, can increase the effciency of programmer, they cannot compete directly with the raw performance of compiled languages. However, by using an interpreted language together with a compiled language, it is possible to have most of the productivity enhancing features together with a good numerical performance. We have used this approach in implementing an electronic structure simulation software GPAW using the combination of Python and C programming languages. While the chosen approach works well in standard workstations and Unix environments, massively parallel supercomputing systems can present some challenges in porting, debugging and profiling the software. In this paper we describe some details of the implementation and discuss the advantages and challenges of the combined Python/C approach. We show that despite the challenges it is possible to obtain good numerical performance and good parallel scalability with Python based software.
Sankaran, Ramanan; Angel, Jordan; Brown, W. Michael
2015-04-08
The growth in size of networked high performance computers along with novel accelerator-based node architectures has further emphasized the importance of communication efficiency in high performance computing. The world's largest high performance computers are usually operated as shared user facilities due to the costs of acquisition and operation. Applications are scheduled for execution in a shared environment and are placed on nodes that are not necessarily contiguous on the interconnect. Furthermore, the placement of tasks on the nodes allocated by the scheduler is sub-optimal, leading to performance loss and variability. Here, we investigate the impact of task placement on themore » performance of two massively parallel application codes on the Titan supercomputer, a turbulent combustion flow solver (S3D) and a molecular dynamics code (LAMMPS). Benchmark studies show a significant deviation from ideal weak scaling and variability in performance. The inter-task communication distance was determined to be one of the significant contributors to the performance degradation and variability. A genetic algorithm-based parallel optimization technique was used to optimize the task ordering. This technique provides an improved placement of the tasks on the nodes, taking into account the application's communication topology and the system interconnect topology. As a result, application benchmarks after task reordering through genetic algorithm show a significant improvement in performance and reduction in variability, therefore enabling the applications to achieve better time to solution and scalability on Titan during production.« less
Sankaran, Ramanan; Angel, Jordan; Brown, W. Michael
2015-04-08
The growth in size of networked high performance computers along with novel accelerator-based node architectures has further emphasized the importance of communication efficiency in high performance computing. The world's largest high performance computers are usually operated as shared user facilities due to the costs of acquisition and operation. Applications are scheduled for execution in a shared environment and are placed on nodes that are not necessarily contiguous on the interconnect. Furthermore, the placement of tasks on the nodes allocated by the scheduler is sub-optimal, leading to performance loss and variability. Here, we investigate the impact of task placement on the performance of two massively parallel application codes on the Titan supercomputer, a turbulent combustion flow solver (S3D) and a molecular dynamics code (LAMMPS). Benchmark studies show a significant deviation from ideal weak scaling and variability in performance. The inter-task communication distance was determined to be one of the significant contributors to the performance degradation and variability. A genetic algorithm-based parallel optimization technique was used to optimize the task ordering. This technique provides an improved placement of the tasks on the nodes, taking into account the application's communication topology and the system interconnect topology. As a result, application benchmarks after task reordering through genetic algorithm show a significant improvement in performance and reduction in variability, therefore enabling the applications to achieve better time to solution and scalability on Titan during production.
Automation of Molecular-Based Analyses: A Primer on Massively Parallel Sequencing
Nguyen, Lan; Burnett, Leslie
2014-01-01
Recent advances in genetics have been enabled by new genetic sequencing techniques called massively parallel sequencing (MPS) or next-generation sequencing. Through the ability to sequence in parallel hundreds of thousands to millions of DNA fragments, the cost and time required for sequencing has dramatically decreased. There are a number of different MPS platforms currently available and being used in Australia. Although they differ in the underlying technology involved, their overall processes are very similar: DNA fragmentation, adaptor ligation, immobilisation, amplification, sequencing reaction and data analysis. MPS is being used in research, translational and increasingly now also in clinical settings. Common applications include sequencing of whole genomes, whole exomes or targeted genes for disease-causing gene discovery, genetic diagnosis and targeted cancer therapy. Even though the revolution that is occurring with MPS is exciting due to its increasing use, improving and emerging technologies and new applications, significant challenges still exist. Particularly challenging issues are the bioinformatics required for data analysis, interpretation of results and the ethical dilemma of ‘incidental findings’. PMID:25336762
Field-Scale, Massively Parallel Simulation of Production from Oceanic Gas Hydrate Deposits
NASA Astrophysics Data System (ADS)
Reagan, M. T.; Moridis, G. J.; Freeman, C. M.; Pan, L.; Boyle, K. L.; Johnson, J. N.; Husebo, J. A.
2012-12-01
The quantity of hydrocarbon gases trapped in natural hydrate accumulations is enormous, leading to significant interest in the evaluation of their potential as an energy source. It has been shown that large volumes of gas can be readily produced at high rates for long times from some types of methane hydrate accumulations by means of depressurization-induced dissociation, and using conventional technologies with horizontal or vertical well configurations. However, these systems are currently assessed using simplified or reduced-scale 3D or even 2D production simulations. In this study, we use the massively parallel TOUGH+HYDRATE code (pT+H) to assess the production potential of a large, deep-ocean hydrate reservoir and develop strategies for effective production. The simulations model a full 3D system of over 24 km2 extent, examining the productivity of vertical and horizontal wells, single or multiple wells, and explore variations in reservoir properties. Systems of up to 2.5M gridblocks, running on thousands of supercomputing nodes, are required to simulate such large systems at the highest level of detail. The simulations reveal the challenges inherent in producing from deep, relatively cold systems with extensive water-bearing channels and connectivity to large aquifers, including the difficulty of achieving depressurizing, the challenges of high water removal rates, and the complexity of production design. Also highlighted are new frontiers in large-scale reservoir simulation of coupled flow, transport, thermodynamics, and phase behavior, including the construction of large meshes, the use parallel numerical solvers and MPI, and large-scale, parallel 3D visualization of results.
KINETIC ALFVEN TURBULENCE AND PARALLEL ELECTRIC FIELDS IN FLARE LOOPS
Zhao, J. S.; Wu, D. J.; Lu, J. Y.
2013-04-20
This study investigates the spectral structure of the kinetic Alfven turbulence in the low-beta plasmas. We consider a strong turbulence resulting from collisions between counterpropagating wavepackets with equal energy. Our results show that (1) the spectra of the magnetic and electric field fluctuations display a transition at the electron inertial length scale, (2) the turbulence cascades mainly toward the magnetic field direction as the cascade scale is smaller than the electron inertial length, and (3) the parallel electric field increases as the turbulent scale decreases. We also show that the parallel electric field in the solar flare loops can be 10{sup 2}-10{sup 4} times the Dreicer field as the turbulence reaches the electron inertial length scale.
MicroRNA transcriptome in the newborn mouse ovaries determined by massive parallel sequencing.
Ahn, Hyo Won; Morin, Ryan D; Zhao, Han; Harris, Ronald A; Coarfa, Cristian; Chen, Zi-Jiang; Milosavljevic, Aleksandar; Marra, Marco A; Rajkovic, Aleksandar
2010-07-01
Small non-coding RNAs, such as microRNAs (miRNAs), are involved in diverse biological processes including organ development and tissue differentiation. Global disruption of miRNA biogenesis in Dicer knockout mice disrupts early embryogenesis and primordial germ cell formation. However, the role of miRNAs in early folliculogenesis is poorly understood. In order to identify a full transcriptome set of small RNAs expressed in the newborn (NB) ovary, we extracted small RNA fraction from mouse NB ovary tissues and subjected it to massive parallel sequencing using the Genome Analyzer from Illumina. Massive sequencing produced 4 655 992 reads of 33 bp each representing a total of 154 Mbp of sequence data. The Pash alignment algorithm mapped 50.13% of the reads to the mouse genome. Sequence reads were clustered based on overlapping mapping coordinates and intersected with known miRNAs, small nucleolar RNAs (snoRNAs), piwi-interacting RNA (piRNA) clusters and repetitive genomic regions; 25.2% of the reads mapped to known miRNAs, 25.5% to genomic repeats, 3.5% to piRNAs and 0.18% to snoRNAs. Three hundred and ninety-eight known miRNA species were among the sequenced small RNAs, and 118 isomiR sequences that are not in the miRBase database. Let-7 family was the most abundantly expressed miRNA, and mmu-mir-672, mmu-mir-322, mmu-mir-503 and mmu-mir-465 families are the most abundant X-linked miRNA detected. X-linked mmu-mir-503, mmu-mir-672 and mmu-mir-465 family showed preferential expression in testes and ovaries. We also identified four novel miRNAs that are preferentially expressed in gonads. Gonadal selective miRNAs may play important roles in ovarian development, folliculogenesis and female fertility. PMID:20215419
Wideband aperture array using RF channelizers and massively parallel digital 2D IIR filterbank
NASA Astrophysics Data System (ADS)
Sengupta, Arindam; Madanayake, Arjuna; Gómez-García, Roberto; Engeberg, Erik D.
2014-05-01
Wideband receive-mode beamforming applications in wireless location, electronically-scanned antennas for radar, RF sensing, microwave imaging and wireless communications require digital aperture arrays that offer a relatively constant far-field beam over several octaves of bandwidth. Several beamforming schemes including the well-known true time-delay and the phased array beamformers have been realized using either finite impulse response (FIR) or fast Fourier transform (FFT) digital filter-sum based techniques. These beamforming algorithms offer the desired selectivity at the cost of a high computational complexity and frequency-dependant far-field array patterns. A novel approach to receiver beamforming is the use of massively parallel 2-D infinite impulse response (IIR) fan filterbanks for the synthesis of relatively frequency independent RF beams at an order of magnitude lower multiplier complexity compared to FFT or FIR filter based conventional algorithms. The 2-D IIR filterbanks demand fast digital processing that can support several octaves of RF bandwidth, fast analog-to-digital converters (ADCs) for RF-to-bits type direct conversion of wideband antenna element signals. Fast digital implementation platforms that can realize high-precision recursive filter structures necessary for real-time beamforming, at RF radio bandwidths, are also desired. We propose a novel technique that combines a passive RF channelizer, multichannel ADC technology, and single-phase massively parallel 2-D IIR digital fan filterbanks, realized at low complexity using FPGA and/or ASIC technology. There exists native support for a larger bandwidth than the maximum clock frequency of the digital implementation technology. We also strive to achieve More-than-Moore throughput by processing a wideband RF signal having content with N-fold (B = N Fclk/2) bandwidth compared to the maximum clock frequency Fclk Hz of the digital VLSI platform under consideration. Such increase in bandwidth is
LiNbO3: A photovoltaic substrate for massive parallel manipulation and patterning of nano-objects
NASA Astrophysics Data System (ADS)
Carrascosa, M.; García-Cabañes, A.; Jubera, M.; Ramiro, J. B.; Agulló-López, F.
2015-12-01
The application of evanescent photovoltaic (PV) fields, generated by visible illumination of Fe:LiNbO3 substrates, for parallel massive trapping and manipulation of micro- and nano-objects is critically reviewed. The technique has been often referred to as photovoltaic or photorefractive tweezers. The main advantage of the new method is that the involved electrophoretic and/or dielectrophoretic forces do not require any electrodes and large scale manipulation of nano-objects can be easily achieved using the patterning capabilities of light. The paper describes the experimental techniques for particle trapping and the main reported experimental results obtained with a variety of micro- and nano-particles (dielectric and conductive) and different illumination configurations (single beam, holographic geometry, and spatial light modulator projection). The report also pays attention to the physical basis of the method, namely, the coupling of the evanescent photorefractive fields to the dielectric response of the nano-particles. The role of a number of physical parameters such as the contrast and spatial periodicities of the illumination pattern or the particle deposition method is discussed. Moreover, the main properties of the obtained particle patterns in relation to potential applications are summarized, and first demonstrations reviewed. Finally, the PV method is discussed in comparison to other patterning strategies, such as those based on the pyroelectric response and the electric fields associated to domain poling of ferroelectric materials.
Carrascosa, M.; García-Cabañes, A.; Jubera, M.; Ramiro, J. B.; Agulló-López, F.
2015-12-15
The application of evanescent photovoltaic (PV) fields, generated by visible illumination of Fe:LiNbO{sub 3} substrates, for parallel massive trapping and manipulation of micro- and nano-objects is critically reviewed. The technique has been often referred to as photovoltaic or photorefractive tweezers. The main advantage of the new method is that the involved electrophoretic and/or dielectrophoretic forces do not require any electrodes and large scale manipulation of nano-objects can be easily achieved using the patterning capabilities of light. The paper describes the experimental techniques for particle trapping and the main reported experimental results obtained with a variety of micro- and nano-particles (dielectric and conductive) and different illumination configurations (single beam, holographic geometry, and spatial light modulator projection). The report also pays attention to the physical basis of the method, namely, the coupling of the evanescent photorefractive fields to the dielectric response of the nano-particles. The role of a number of physical parameters such as the contrast and spatial periodicities of the illumination pattern or the particle deposition method is discussed. Moreover, the main properties of the obtained particle patterns in relation to potential applications are summarized, and first demonstrations reviewed. Finally, the PV method is discussed in comparison to other patterning strategies, such as those based on the pyroelectric response and the electric fields associated to domain poling of ferroelectric materials.
Formiconi, A R; Passeri, A; Guelfi, M R; Masoni, M; Pupi, A; Meldolesi, U; Malfetti, P; Calori, L; Guidazzoli, A
1997-11-01
Data from Single Photon Emission Computed Tomography (SPECT) studies are blurred by inevitable physical phenomena occurring during data acquisition. These errors may be compensated by means of reconstruction algorithms which take into account accurate physical models of the data acquisition procedure. Unfortunately, this approach involves high memory requirements as well as a high computational burden which cannot be afforded by the computer systems of SPECT acquisition devices. In this work the possibility of accessing High Performance Computing and Networking (HPCN) resources through a World Wide Web interface for the advanced reconstruction of SPECT data in a clinical environment was investigated. An iterative algorithm with an accurate model of the variable system response was ported on the Multiple Instruction Multiple Data (MIMD) parallel architecture of a Cray T3D massively parallel computer. The system was accessible even from low cost PC-based workstations through standard TCP/IP networking. A speedup factor of 148 was predicted by the benchmarks run on the Cray T3D. A complete brain study of 30 (64 x 64) slices was reconstructed from a set of 90 (64 x 64) projections with ten iterations of the conjugate gradients algorithm in 9 s which corresponds to an actual speed-up factor of 135. The technique was extended to a more accurate 3D modeling of the system response for a true 3D reconstruction of SPECT data; the reconstruction time of the same data set with this more accurate model was 5 min. This work demonstrates the possibility of exploiting remote HPCN resources from hospital sites by means of low cost workstations using standard communication protocols and an user-friendly WWW interface without particular problems for routine use. PMID:9506406
Switching dynamics of thin film ferroelectric devices - a massively parallel phase field study
NASA Astrophysics Data System (ADS)
Ashraf, Md. Khalid
In this thesis, we investigate the switching dynamics in thin film ferroelectrics. Ferroelectric materials are of inherent interest for low power and multi-functional devices. However, possible device applications of these materials have been limited due to the poorly understood electromagnetic and mechanical response at the nanoscale in arbitrary device structures. The difficulty in understanding switching dynamics mainly arises from the presence of features at multiple length scales and the nonlinearity associated with the strongly coupled states. For example, in a ferroelectric material, the domain walls are of nm size whereas the domain pattern forms at micron scale. The switching is determined by coupled chemical, electrostatic, mechanical and thermal interactions. Thus computational understanding of switching dynamics in thin film ferroelectrics and a direct comparison with experiment poses a significant numerical challenge. We have developed a phase field model that describes the physics of polarization dynamics at the microscopic scale. A number of efficient numerical methods have been applied for achieving massive parallelization of all the calculation steps. Conformally mapped elements, node wise assembly and prevention of dynamic loading minimized the communication between processors and increased the parallelization efficiency. With these improvements, we have reached the experimental scale - a significant step forward compared to the state of the art thin film ferroelectric switching dynamics models. Using this model, we elucidated the switching dynamics on multiple surfaces of the multiferroic material BFO. We also calculated the switching energy of scaled BFO islands. Finally, we studied the interaction of domain wall propagation with misfit dislocations in the thin film. We believe that the model will be useful in understanding the switching dynamics in many different experimental setups incorporating thin film ferroelectrics.
Diffuse large B-cell lymphoma: sub-classification by massive parallel quantitative RT-PCR.
Xue, Xuemin; Zeng, Naiyan; Gao, Zifen; Du, Ming-Qing
2015-01-01
Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous entity with remarkably variable clinical outcome. Gene expression profiling (GEP) classifies DLBCL into activated B-cell like (ABC), germinal center B-cell like (GCB), and Type-III subtypes, with ABC-DLBCL characterized by a poor prognosis and constitutive NF-κB activation. A major challenge for the application of this cell of origin (COO) classification in routine clinical practice is to establish a robust clinical assay amenable to routine formalin-fixed paraffin-embedded (FFPE) diagnostic biopsies. In this study, we investigated the possibility of COO-classification using FFPE tissue RNA samples by massive parallel quantitative reverse transcription PCR (qRT-PCR). We established a protocol for parallel qRT-PCR using FFPE RNA samples with the Fluidigm BioMark HD system, and quantified the expression of the COO classifier genes and the NF-κB targeted-genes that characterize ABC-DLBCL in 143 cases of DLBCL. We also trained and validated a series of basic machine-learning classifiers and their derived meta classifiers, and identified SimpleLogistic as the top classifier that gave excellent performance across various GEP data sets derived from fresh-frozen or FFPE tissues by different microarray platforms. Finally, we applied SimpleLogistic to our data set generated by qRT-PCR, and the ABC and GCB-DLBCL assigned showed the respective characteristics in their clinical outcome and NF-κB target gene expression. The methodology established in this study provides a robust approach for DLBCL sub-classification using routine FFPE diagnostic biopsies in a routine clinical setting. PMID:25418578
PORTA: A Massively Parallel Code for 3D Non-LTE Polarized Radiative Transfer
NASA Astrophysics Data System (ADS)
Štěpán, J.
2014-10-01
The interpretation of the Stokes profiles of the solar (stellar) spectral line radiation requires solving a non-LTE radiative transfer problem that can be very complex, especially when the main interest lies in modeling the linear polarization signals produced by scattering processes and their modification by the Hanle effect. One of the main difficulties is due to the fact that the plasma of a stellar atmosphere can be highly inhomogeneous and dynamic, which implies the need to solve the non-equilibrium problem of generation and transfer of polarized radiation in realistic three-dimensional stellar atmospheric models. Here we present PORTA, a computer program we have developed for solving, in three-dimensional (3D) models of stellar atmospheres, the problem of the generation and transfer of spectral line polarization taking into account anisotropic radiation pumping and the Hanle and Zeeman effects in multilevel atoms. The numerical method of solution is based on a highly convergent iterative algorithm, whose convergence rate is insensitive to the grid size, and on an accurate short-characteristics formal solver of the Stokes-vector transfer equation which uses monotonic Bezier interpolation. In addition to the iterative method and the 3D formal solver, another important feature of PORTA is a novel parallelization strategy suitable for taking advantage of massively parallel computers. Linear scaling of the solution with the number of processors allows to reduce the solution time by several orders of magnitude. We present useful benchmarks and a few illustrations of applications using a 3D model of the solar chromosphere resulting from MHD simulations. Finally, we present our conclusions with a view to future research. For more details see Štěpán & Trujillo Bueno (2013).
Hierarchical Image Segmentation of Remotely Sensed Data using Massively Parallel GNU-LINUX Software
NASA Technical Reports Server (NTRS)
Tilton, James C.
2003-01-01
A hierarchical set of image segmentations is a set of several image segmentations of the same image at different levels of detail in which the segmentations at coarser levels of detail can be produced from simple merges of regions at finer levels of detail. In [1], Tilton, et a1 describes an approach for producing hierarchical segmentations (called HSEG) and gave a progress report on exploiting these hierarchical segmentations for image information mining. The HSEG algorithm is a hybrid of region growing and constrained spectral clustering that produces a hierarchical set of image segmentations based on detected convergence points. In the main, HSEG employs the hierarchical stepwise optimization (HSWO) approach to region growing, which was described as early as 1989 by Beaulieu and Goldberg. The HSWO approach seeks to produce segmentations that are more optimized than those produced by more classic approaches to region growing (e.g. Horowitz and T. Pavlidis, [3]). In addition, HSEG optionally interjects between HSWO region growing iterations, merges between spatially non-adjacent regions (i.e., spectrally based merging or clustering) constrained by a threshold derived from the previous HSWO region growing iteration. While the addition of constrained spectral clustering improves the utility of the segmentation results, especially for larger images, it also significantly increases HSEG s computational requirements. To counteract this, a computationally efficient recursive, divide-and-conquer, implementation of HSEG (RHSEG) was devised, which includes special code to avoid processing artifacts caused by RHSEG s recursive subdivision of the image data. The recursive nature of RHSEG makes for a straightforward parallel implementation. This paper describes the HSEG algorithm, its recursive formulation (referred to as RHSEG), and the implementation of RHSEG using massively parallel GNU-LINUX software. Results with Landsat TM data are included comparing RHSEG with classic
Frequency of Usher syndrome type 1 in deaf children by massively parallel DNA sequencing
Yoshimura, Hidekane; Miyagawa, Maiko; Kumakawa, Kozo; Nishio, Shin-ya; Usami, Shin-ichi
2016-01-01
Usher syndrome type 1 (USH1) is the most severe of the three USH subtypes due to its profound hearing loss, absent vestibular response and retinitis pigmentosa appearing at a prepubescent age. Six causative genes have been identified for USH1, making early diagnosis and therapy possible through DNA testing. Targeted exon sequencing of selected genes using massively parallel DNA sequencing (MPS) technology enables clinicians to systematically tackle previously intractable monogenic disorders and improve molecular diagnosis. Using MPS along with direct sequence analysis, we screened 227 unrelated non-syndromic deaf children and detected recessive mutations in USH1 causative genes in five patients (2.2%): three patients harbored MYO7A mutations and one each carried CDH23 or PCDH15 mutations. As indicated by an earlier genotype–phenotype correlation study of the CDH23 and PCDH15 genes, we considered the latter two patients to have USH1. Based on clinical findings, it was also highly likely that one patient with MYO7A mutations possessed USH1 due to a late onset age of walking. This first report describing the frequency (1.3–2.2%) of USH1 among non-syndromic deaf children highlights the importance of comprehensive genetic testing for early disease diagnosis. PMID:26791358
Massively parallel sampling of lattice proteins reveals foundations of thermal adaptation.
Venev, Sergey V; Zeldovich, Konstantin B
2015-08-01
Evolution of proteins in bacteria and archaea living in different conditions leads to significant correlations between amino acid usage and environmental temperature. The origins of these correlations are poorly understood, and an important question of protein theory, physics-based prediction of types of amino acids overrepresented in highly thermostable proteins, remains largely unsolved. Here, we extend the random energy model of protein folding by weighting the interaction energies of amino acids by their frequencies in protein sequences and predict the energy gap of proteins designed to fold well at elevated temperatures. To test the model, we present a novel scalable algorithm for simultaneous energy calculation for many sequences in many structures, targeting massively parallel computing architectures such as graphics processing unit. The energy calculation is performed by multiplying two matrices, one representing the complete set of sequences, and the other describing the contact maps of all structural templates. An implementation of the algorithm for the CUDA platform is available at http://www.github.com/kzeldovich/galeprot and calculates protein folding energies over 250 times faster than a single central processing unit. Analysis of amino acid usage in 64-mer cubic lattice proteins designed to fold well at different temperatures demonstrates an excellent agreement between theoretical and simulated values of energy gap. The theoretical predictions of temperature trends of amino acid frequencies are significantly correlated with bioinformatics data on 191 bacteria and archaea, and highlight protein folding constraints as a fundamental selection pressure during thermal adaptation in biological evolution. PMID:26254668
Le Crom, Stéphane; Schackwitz, Wendy; Pennacchio, Len; Magnuson, Jon K.; Culley, David E.; Collett, James R.; Martin, Joel; Druzhinina, Irina S.; Mathis, Hugues; Monot, Frédéric; Seiboth, Bernhard; Cherry, Barbara; Rey, Michael; Berka, Randy; Kubicek, Christian P.; Baker, Scott E.; Margeot, Antoine
2009-01-01
Trichoderma reesei (teleomorph Hypocrea jecorina) is the main industrial source of cellulases and hemicellulases harnessed for the hydrolysis of biomass to simple sugars, which can then be converted to biofuels such as ethanol and other chemicals. The highly productive strains in use today were generated by classical mutagenesis. To learn how cellulase production was improved by these techniques, we performed massively parallel sequencing to identify mutations in the genomes of two hyperproducing strains (NG14, and its direct improved descendant, RUT C30). We detected a surprisingly high number of mutagenic events: 223 single nucleotides variants, 15 small deletions or insertions, and 18 larger deletions, leading to the loss of more than 100 kb of genomic DNA. From these events, we report previously undocumented non-synonymous mutations in 43 genes that are mainly involved in nuclear transport, mRNA stability, transcription, secretion/vacuolar targeting, and metabolism. This homogeneity of functional categories suggests that multiple changes are necessary to improve cellulase production and not simply a few clear-cut mutagenic events. Phenotype microarrays show that some of these mutations result in strong changes in the carbon assimilation pattern of the two mutants with respect to the wild-type strain QM6a. Our analysis provides genome-wide insights into the changes induced by classical mutagenesis in a filamentous fungus and suggests areas for the generation of enhanced T. reesei strains for industrial applications such as biofuel production. PMID:19805272
Le Crom, Stéphane; Schackwitz, Wendy; Pennacchio, Len; Magnuson, Jon K; Culley, David E; Collett, James R; Martin, Joel; Druzhinina, Irina S; Mathis, Hugues; Monot, Frédéric; Seiboth, Bernhard; Cherry, Barbara; Rey, Michael; Berka, Randy; Kubicek, Christian P; Baker, Scott E; Margeot, Antoine
2009-09-22
Trichoderma reesei (teleomorph Hypocrea jecorina) is the main industrial source of cellulases and hemicellulases harnessed for the hydrolysis of biomass to simple sugars, which can then be converted to biofuels such as ethanol and other chemicals. The highly productive strains in use today were generated by classical mutagenesis. To learn how cellulase production was improved by these techniques, we performed massively parallel sequencing to identify mutations in the genomes of two hyperproducing strains (NG14, and its direct improved descendant, RUT C30). We detected a surprisingly high number of mutagenic events: 223 single nucleotides variants, 15 small deletions or insertions, and 18 larger deletions, leading to the loss of more than 100 kb of genomic DNA. From these events, we report previously undocumented non-synonymous mutations in 43 genes that are mainly involved in nuclear transport, mRNA stability, transcription, secretion/vacuolar targeting, and metabolism. This homogeneity of functional categories suggests that multiple changes are necessary to improve cellulase production and not simply a few clear-cut mutagenic events. Phenotype microarrays show that some of these mutations result in strong changes in the carbon assimilation pattern of the two mutants with respect to the wild-type strain QM6a. Our analysis provides genome-wide insights into the changes induced by classical mutagenesis in a filamentous fungus and suggests areas for the generation of enhanced T. reesei strains for industrial applications such as biofuel production. PMID:19805272
SIESTA-PEXSI: Massively parallel method for efficient and accurate ab initio materials simulation
NASA Astrophysics Data System (ADS)
Lin, Lin; Huhs, Georg; Garcia, Alberto; Yang, Chao
2014-03-01
We describe how to combine the pole expansion and selected inversion (PEXSI) technique with the SIESTA method, which uses numerical atomic orbitals for Kohn-Sham density functional theory (KSDFT) calculations. The PEXSI technique can efficiently utilize the sparsity pattern of the Hamiltonian matrix and the overlap matrix generated from codes such as SIESTA, and solves KSDFT without using cubic scaling matrix diagonalization procedure. The complexity of PEXSI scales at most quadratically with respect to the system size, and the accuracy is comparable to that obtained from full diagonalization. One distinct feature of PEXSI is that it achieves low order scaling without using the near-sightedness property and can be therefore applied to metals as well as insulators and semiconductors, at room temperature or even lower temperature. The PEXSI method is highly scalable, and the recently developed massively parallel PEXSI technique can make efficient usage of 10,000 ~100,000 processors on high performance machines. We demonstrate the performance the SIESTA-PEXSI method using several examples for large scale electronic structure calculation including long DNA chain and graphene-like structures with more than 20000 atoms. Funded by Luis Alvarez fellowship in LBNL, and DOE SciDAC project in partnership with BES.
Nagai, Satoshi; Hida, Kohsuke; Urusizaki, Shingo; Takano, Yoshihito; Hongo, Yuki; Kameda, Takahiko; Abe, Kazuo
2016-02-01
In this study, we compared the eukaryote biodiversity between Hiroshima Bay and Ishigaki Island in Japanese coastal waters by using the massively parallel sequencing (MPS)-based technique to collect preliminary data. The relative abundance of Alveolata was highest in both localities, and the second highest groups were Stramenopiles, Opisthokonta, or Hacrobia, which varied depending on the samples considered. For microalgal phyla, the relative abundance of operational taxonomic units (OTUs) and the number of MPS were highest for Dinophyceae in both localities, followed by Bacillariophyceae in Hiroshima Bay, and by Bacillariophyceae or Chlorophyceae in Ishigaki Island. The number of detected OTUs in Hiroshima Bay and Ishigaki Island was 645 and 791, respectively, and 15.3% and 12.5% of the OTUs were common between the two localities. In the non-metric multidimensional scaling analysis, the samples from the two localities were plotted in different positions. In the dendrogram developed using similarity indices, the samples were clustered into different nodes based on localities with high multiscale bootstrap values, reflecting geographic differences in biodiversity. Thus, we succeeded in demonstrating biodiversity differences between the two localities, although the read numbers of the MPSs were not high enough. The corresponding analysis showed a clear seasonal change in the biodiversity of Hiroshima Bay but it was not clear in Ishigaki Island. Thus, the MPS-based technique shows a great advantage of high performance by detecting several hundreds of OTUs from a single sample, strongly suggesting the effectiveness to apply this technique to routine monitoring programs. PMID:26476293
Liu, Fengsong; Tang, Ting; Sun, Lingling; Jose Priya, T A
2012-02-01
To explore the transcriptome of Musca domestica larvae and to identify unique sequences, we used massively parallel pyrosequencing on the Roche 454-FLX platform to generate a substantial EST dataset of this fly. As a result, we obtained a total of 249,555 ESTs with an average read length of 373 bp. These reads were assembled into 13,206 contigs and 20,556 singletons. Using BlastX searches of the Swissprot and Nr databases, we were able to identify 4,814 contigs and 8,166 singletons as unique sequences. Subsequently, the annotated sequences were subjected to GO analysis and the search results showed a majority of the query sequences were assignable to certain gene ontology terms. In addition, functional classification and pathway assignment were performed by KEGG and 2,164 unique sequences were mapped into 184 KEGG pathways in total. As the first attempt on large-scale RNA sequencing of M. domestica, this general picture of the transcriptome can establish a fundamental resource for further research on functional genomics. PMID:21643958
Warshauer, David H.; Churchill, Jennifer D.; Novroski, Nicole; King, Jonathan L.; Budowle, Bruce
2015-01-01
Massively parallel sequencing (MPS) technology is capable of determining the sizes of short tandem repeat (STR) alleles as well as their individual nucleotide sequences. Thus, single nucleotide polymorphisms (SNPs) within the repeat regions of STRs and variations in the pattern of repeat units in a given repeat motif can be used to differentiate alleles of the same length. In this study, MPS was used to sequence 28 forensically-relevant Y-chromosome STRs in a set of 41 DNA samples from the 3 major U.S. population groups (African Americans, Caucasians, and Hispanics). The resulting sequence data, which were analyzed with STRait Razor v2.0, revealed 37 unique allele sequence variants that have not been previously reported. Of these, 19 sequences were variations of documented sequences resulting from the presence of intra-repeat SNPs or alternative repeat unit patterns. Despite a limited sampling, two of the most frequently-observed variants were found only in African American samples. The remaining 18 variants represented allele sequences for which there were no published data with which to compare. These findings illustrate the great potential of MPS with regard to increasing the resolving power of STR typing and emphasize the need for sample population characterization of STR alleles. PMID:26391384
GRay: A MASSIVELY PARALLEL GPU-BASED CODE FOR RAY TRACING IN RELATIVISTIC SPACETIMES
Chan, Chi-kwan; Psaltis, Dimitrios; Özel, Feryal
2013-11-01
We introduce GRay, a massively parallel integrator designed to trace the trajectories of billions of photons in a curved spacetime. This graphics-processing-unit (GPU)-based integrator employs the stream processing paradigm, is implemented in CUDA C/C++, and runs on nVidia graphics cards. The peak performance of GRay using single-precision floating-point arithmetic on a single GPU exceeds 300 GFLOP (or 1 ns per photon per time step). For a realistic problem, where the peak performance cannot be reached, GRay is two orders of magnitude faster than existing central-processing-unit-based ray-tracing codes. This performance enhancement allows more effective searches of large parameter spaces when comparing theoretical predictions of images, spectra, and light curves from the vicinities of compact objects to observations. GRay can also perform on-the-fly ray tracing within general relativistic magnetohydrodynamic algorithms that simulate accretion flows around compact objects. Making use of this algorithm, we calculate the properties of the shadows of Kerr black holes and the photon rings that surround them. We also provide accurate fitting formulae of their dependencies on black hole spin and observer inclination, which can be used to interpret upcoming observations of the black holes at the center of the Milky Way, as well as M87, with the Event Horizon Telescope.
Arboleda, VA; Lee, H; Sánchez, FJ; Délot, EC; Sandberg, DE; Grody, WW; Nelson, SF; Vilain, E
2013-01-01
Disorders of sex development (DSD) are rare disorders in which there is discordance between chromosomal, gonadal, and phenotypic sex. Only a minority of patients clinically diagnosed with DSD obtains a molecular diagnosis, leaving a large gap in our understanding of the prevalence, management, and outcomes in affected patients. We created a novel DSD-genetic diagnostic tool, in which sex development genes are captured using RNA probes and undergo massively parallel sequencing. In the pilot group of 14 patients, we determined sex chromosome dosage, copy number variation, and gene mutations. In the patients with a known genetic diagnosis (obtained either on a clinical or research basis), this test identified the molecular cause in 100% (7/7) of patients. In patients in whom no molecular diagnosis had been made, this tool identified a genetic diagnosis in two of seven patients. Targeted sequencing of genes representing a specific spectrum of disorders can result in a higher rate of genetic diagnoses than current diagnostic approaches. Our DSD diagnostic tool provides for first time, in a single blood test, a comprehensive genetic diagnosis in patients presenting with a wide range of urogenital anomalies. PMID:22435390
Collins, Stephen C.; Bray, Steven M.; Suhl, Joshua A.; Cutler, David J.; Coffee, Bradford; Zwick, Michael E.; Warren, Stephen T.
2010-01-01
Fragile X syndrome (FXS), the most common inherited form of developmental delay, is typically caused by CGG-repeat expansion in FMR1. However, little attention has been paid to sequence variants in FMR1. Through the use of pooled-template massively parallel sequencing, we identified 130 novel FMR1 sequence variants in a population of 963 developmentally delayed males without CGG-repeat expansion mutations. Among these, we identified a novel missense change, p.R138Q, which alters a conserved residue in the nuclear localization signal of FMRP. We have also identified three promoter mutations in this population, all of which significantly reduce in vitro levels of FMR1 transcription. Additionally, we identified 10 noncoding variants of possible functional significance in the introns and 3’-untranslated region of FMR1, including two predicted splice site mutations. These findings greatly expand the catalogue of known FMR1 sequence variants and suggest that FMR1 sequence variants may represent an important cause of developmental delay. PMID:20799337
Mitochondrial DNA heteroplasmy in the emerging field of massively parallel sequencing
Just, Rebecca S.; Irwin, Jodi A.; Parson, Walther
2015-01-01
Long an important and useful tool in forensic genetic investigations, mitochondrial DNA (mtDNA) typing continues to mature. Research in the last few years has demonstrated both that data from the entire molecule will have practical benefits in forensic DNA casework, and that massively parallel sequencing (MPS) methods will make full mitochondrial genome (mtGenome) sequencing of forensic specimens feasible and cost-effective. A spate of recent studies has employed these new technologies to assess intraindividual mtDNA variation. However, in several instances, contamination and other sources of mixed mtDNA data have been erroneously identified as heteroplasmy. Well vetted mtGenome datasets based on both Sanger and MPS sequences have found authentic point heteroplasmy in approximately 25% of individuals when minor component detection thresholds are in the range of 10–20%, along with positional distribution patterns in the coding region that differ from patterns of point heteroplasmy in the well-studied control region. A few recent studies that examined very low-level heteroplasmy are concordant with these observations when the data are examined at a common level of resolution. In this review we provide an overview of considerations related to the use of MPS technologies to detect mtDNA heteroplasmy. In addition, we examine published reports on point heteroplasmy to characterize features of the data that will assist in the evaluation of future mtGenome data developed by any typing method. PMID:26009256
NASA Astrophysics Data System (ADS)
Settgast, R. R.; Johnson, S.; Fu, P.; Walsh, S. D.; Ryerson, F. J.; Antoun, T.
2012-12-01
Hydraulic fracturing has been an enabling technology for commercially stimulating fracture networks for over half of a century. It has become one of the most widespread technologies for engineering subsurface fracture systems. Despite the ubiquity of this technique in the field, understanding and prediction of the hydraulic induced propagation of the fracture network in realistic, heterogeneous reservoirs has been limited. A number of developments in multiscale modeling in recent years have allowed researchers in related fields to tackle the modeling of complex fracture propagation as well as the mechanics of heterogeneous materials. These developments, combined with advances in quantifying solution uncertainties, provide possibilities for the geologic modeling community to capture both the fracturing behavior and longer-term permeability evolution of rock masses under hydraulic loading across both dynamic and viscosity-dominated regimes. Here we will demonstrate the first phase of this effort through illustrations of fully three-dimensional, tightly coupled hydromechanical simulations of hydraulically induced fracture network propagation run on massively parallel computing scales, and discuss preliminary results regarding the mechanisms by which fracture interactions and the accompanying changes to the stress field can lead to deleterious or beneficial changes to the fracture network.
Massively parallel LES of azimuthal thermo-acoustic instabilities in annular gas turbines
NASA Astrophysics Data System (ADS)
Wolf, P.; Staffelbach, G.; Roux, A.; Gicquel, L.; Poinsot, T.; Moureau, V.
2009-06-01
Increasingly stringent regulations and the need to tackle rising fuel prices have placed great emphasis on the design of aeronautical gas turbines, which are unfortunately more and more prone to combustion instabilities. In the particular field of annular combustion chambers, these instabilities often take the form of azimuthal modes. To predict these modes, one must compute the full combustion chamber, which remained out of reach until very recently and the development of massively parallel computers. In this article, full annular Large Eddy Simulations (LES) of two helicopter combustors, which differ only on the swirlers' design, are performed. In both computations, LES captures self-established rotating azimuthal modes. However, the two cases exhibit different thermo-acoustic responses and the resulting limit-cycles are different. With the first design, a self-excited strong instability develops, leading to pulsating flames and local flashback. In the second case, the flames are much less affected by the azimuthal mode and remain stable, allowing an acceptable operation. Hence, this study highlights the potential of LES for discriminating injection system designs. To cite this article: P. Wolf et al., C. R. Mecanique 337 (2009).
Massively parallel LES of azimuthal thermo-acoustic instabilities in annular gas turbines
NASA Astrophysics Data System (ADS)
Wolf, Pierre; Staffelbach, Gabriel; Gicquel, Laurent; Poinsot, Thierry
2009-07-01
Most of the energy produced worldwide comes from the combustion of fossil fuels. In the context of global climate changes and dramatically decreasing resources, there is a critical need for optimizing the process of burning, especially in the field of gas turbines. Unfortunately, new designs for efficient combustion are prone to destructive thermo-acoustic instabilities. Large Eddy Simulation (LES) is a promising tool to predict turbulent reacting flows in complex industrial configurations and explore the mechanisms triggering the coupling between acoustics and combustion. In the particular field of annular combustion chambers, these instabilities usually take the form of azimuthal modes. To predict these modes, one must compute the full combustion chamber comprising all sectors, which remained out of reach until very recently and the development of massively parallel computers. A fully compressible, multi-species reactive Navier-Stokes solver is used on up to 4096 BlueGene/P CPUs for two designs of a full annular helicopter chamber. Results show evidence of self-established azimuthal modes for the two cases but with different energy containing limit-cycles. Mesh dependency is checked with grids comprising 38 and 93 million tetrahedra. The fact that the two grid predictions yield similar flow topologies and limit-cycles enforces the ability of LES to discriminate design changes.
Onions, D; Côté, C; Love, B; Toms, B; Koduri, S; Armstrong, A; Chang, A; Kolman, J
2011-09-22
Massively parallel, deep, sequencing of the transcriptome coupled with algorithmic analysis to identify adventitious agents (MP-Seq™) is an important adjunct in ensuring the safety of cells used in vaccine production. Such cells may harbour novel viruses whose sequences are unknown or latent viruses that are only expressed following stress to the cells. MP-Seq is an unbiased and comprehensive method to identify such viruses and other adventitious agents without prior knowledge of the nature of those agents. Here we demonstrate its utility as part of an integrated approach to identify and characterise potential contaminants within commonly used virus and vaccine production cell lines. Through this analysis, in combination with more traditional approaches, we have excluded the presence of porcine circoviruses in the ATCC Vero cell bank (CCL-81), however, we found that a full length betaretrovirus related to SRV can be expressed in these cells, a factor that may be of importance in the production of certain vaccines. Similarly, insect cells are proving to be valuable for the production of virus like particles and sub-unit vaccines, but they can harbour a range of latent viruses. We show that following MP-Seq of the Trichoplusia ni (High Five cell line) transcriptome we were able to detect a contaminating, latent nodavirus and identify an expressed errantivirus genome. Collectively, these studies have reinforced the role of MP-Seq as an integral tool for the identification of contaminating agents in vaccine cell substrates. PMID:21651935
GRay: A Massively Parallel GPU-based Code for Ray Tracing in Relativistic Spacetimes
NASA Astrophysics Data System (ADS)
Chan, Chi-kwan; Psaltis, Dimitrios; Özel, Feryal
2013-11-01
We introduce GRay, a massively parallel integrator designed to trace the trajectories of billions of photons in a curved spacetime. This graphics-processing-unit (GPU)-based integrator employs the stream processing paradigm, is implemented in CUDA C/C++, and runs on nVidia graphics cards. The peak performance of GRay using single-precision floating-point arithmetic on a single GPU exceeds 300 GFLOP (or 1 ns per photon per time step). For a realistic problem, where the peak performance cannot be reached, GRay is two orders of magnitude faster than existing central-processing-unit-based ray-tracing codes. This performance enhancement allows more effective searches of large parameter spaces when comparing theoretical predictions of images, spectra, and light curves from the vicinities of compact objects to observations. GRay can also perform on-the-fly ray tracing within general relativistic magnetohydrodynamic algorithms that simulate accretion flows around compact objects. Making use of this algorithm, we calculate the properties of the shadows of Kerr black holes and the photon rings that surround them. We also provide accurate fitting formulae of their dependencies on black hole spin and observer inclination, which can be used to interpret upcoming observations of the black holes at the center of the Milky Way, as well as M87, with the Event Horizon Telescope.
Ermolenko, Natalya A; Boyarskikh, Uljana A; Kechin, Andrey A; Mazitova, Alexandra M; Khrapov, Evgeny A; Petrova, Valentina D; Lazarev, Alexandr F; Kushlinskii, Nikolay E; Filipenko, Maxim L
2015-01-01
The aim of this study was to implement massive parallel sequencing (MPS) technology in clinical genetics testing. We developed and tested an amplicon-based method for resequencing the BRCA1 and BRCA2 genes on an Illumina MiSeq to identify disease-causing mutations in patients with hereditary breast or ovarian cancer (HBOC). The coding regions of BRCA1 and BRCA2 were resequenced in 96 HBOC patient DNA samples obtained from different sample types: peripheral blood leukocytes, whole blood drops dried on paper, and buccal wash epithelia. A total of 16 random DNA samples were characterized using standard Sanger sequencing and applied to optimize the variant calling process and evaluate the accuracy of the MPS-method. The best bioinformatics workflow included the filtration of variants using GATK with the following cut-offs: variant frequency >14%, coverage (>25x) and presence in both the forward and reverse reads. The MPS method had 100% sensitivity and 94.4% specificity. Similar accuracy levels were achieved for DNA obtained from the different sample types. The workflow presented herein requires low amounts of DNA samples (170 ng) and is cost-effective due to the elimination of DNA and PCR product normalization steps. PMID:26625824
Nuttle, Xander; Itsara, Andy; Shendure, Jay; Eichler, Evan E.
2014-01-01
The most common recurrent copy number variants associated with autism, developmental delay, and epilepsy are flanked by segmental duplications. Complete genetic characterization of these events is challenging because their breakpoints often occur within high-identity, copy number polymorphic paralogous sequences that cannot be specifically assayed using hybridization-based methods. Here, we provide a protocol for breakpoint resolution with sequence-level precision. Massively parallel sequencing is performed on libraries generated from haplotype-resolved chromosomes, genomic DNA, or molecular inversion probe–captured breakpoint-informative regions harboring paralog-distinguishing variants. Quantifying sequencing depth over informative sites enables breakpoint localization, typically within several kilobases to tens of kilobases. Depending on the approach employed, the sequencing platform, and the accuracy and completeness of the reference genome sequence, this protocol takes from a few days to several months to complete. Once established for a specific genomic disorder, it is possible to process thousands of DNA samples within as little as 3–4 weeks. PMID:24874815
Kristiansson, Erik; Asker, Noomi; Förlin, Lars; Larsson, DG Joakim
2009-01-01
Background The teleost Zoarces viviparus (eelpout) lives along the coasts of Northern Europe and has long been an established model organism for marine ecology and environmental monitoring. The scarce information about this species genome has however restrained the use of efficient molecular-level assays, such as gene expression microarrays. Results In the present study we present the first comprehensive characterization of the Zoarces viviparus liver transcriptome. From 400,000 reads generated by massively parallel pyrosequencing, more than 50,000 pieces of putative transcripts were assembled, annotated and functionally classified. The data was estimated to cover roughly 40% of the total transcriptome and homologues for about half of the genes of Gasterosteus aculeatus (stickleback) were identified. The sequence data was consequently used to design an oligonucleotide microarray for large-scale gene expression analysis. Conclusion Our results show that one run using a Genome Sequencer FLX from 454 Life Science/Roche generates enough genomic information for adequate de novo assembly of a large number of genes in a higher vertebrate. The generated sequence data, including the validated microarray probes, are publicly available to promote genome-wide research in Zoarces viviparus. PMID:19646242