Parallel Architecture For Robotics Computation
NASA Technical Reports Server (NTRS)
Fijany, Amir; Bejczy, Antal K.
1990-01-01
Universal Real-Time Robotic Controller and Simulator (URRCS) is highly parallel computing architecture for control and simulation of robot motion. Result of extensive algorithmic study of different kinematic and dynamic computational problems arising in control and simulation of robot motion. Study led to development of class of efficient parallel algorithms for these problems. Represents algorithmically specialized architecture, in sense capable of exploiting common properties of this class of parallel algorithms. System with both MIMD and SIMD capabilities. Regarded as processor attached to bus of external host processor, as part of bus memory.
Electromagnetic physics models for parallel computing architectures
Amadio, G.; Ananya, A.; Apostolakis, J.; Aurora, A.; Bandieramonte, M.; Bhattacharyya, A.; Bianchini, C.; Brun, R.; Canal, P.; Carminati, F.; Duhem, L.; Elvira, D.; Gheata, A.; Gheata, M.; Goulas, I.; Iope, R.; Jun, S. Y.; Lima, G.; Mohanty, A.; Nikitina, T.; Novak, M.; Pokorski, W.; Ribon, A.; Seghal, R.; Shadura, O.; Vallecorsa, S.; Wenzel, S.; Zhang, Y.
2016-11-21
The recent emergence of hardware architectures characterized by many-core or accelerated processors has opened new opportunities for concurrent programming models taking advantage of both SIMD and SIMT architectures. GeantV, a next generation detector simulation, has been designed to exploit both the vector capability of mainstream CPUs and multi-threading capabilities of coprocessors including NVidia GPUs and Intel Xeon Phi. The characteristics of these architectures are very different in terms of the vectorization depth and type of parallelization needed to achieve optimal performance. In this paper we describe implementation of electromagnetic physics models developed for parallel computing architectures as a part of the GeantV project. Finally, the results of preliminary performance evaluation and physics validation are presented as well.
Electromagnetic physics models for parallel computing architectures
Amadio, G.; Ananya, A.; Apostolakis, J.; ...
2016-11-21
The recent emergence of hardware architectures characterized by many-core or accelerated processors has opened new opportunities for concurrent programming models taking advantage of both SIMD and SIMT architectures. GeantV, a next generation detector simulation, has been designed to exploit both the vector capability of mainstream CPUs and multi-threading capabilities of coprocessors including NVidia GPUs and Intel Xeon Phi. The characteristics of these architectures are very different in terms of the vectorization depth and type of parallelization needed to achieve optimal performance. In this paper we describe implementation of electromagnetic physics models developed for parallel computing architectures as a part ofmore » the GeantV project. Finally, the results of preliminary performance evaluation and physics validation are presented as well.« less
Electromagnetic Physics Models for Parallel Computing Architectures
NASA Astrophysics Data System (ADS)
Amadio, G.; Ananya, A.; Apostolakis, J.; Aurora, A.; Bandieramonte, M.; Bhattacharyya, A.; Bianchini, C.; Brun, R.; Canal, P.; Carminati, F.; Duhem, L.; Elvira, D.; Gheata, A.; Gheata, M.; Goulas, I.; Iope, R.; Jun, S. Y.; Lima, G.; Mohanty, A.; Nikitina, T.; Novak, M.; Pokorski, W.; Ribon, A.; Seghal, R.; Shadura, O.; Vallecorsa, S.; Wenzel, S.; Zhang, Y.
2016-10-01
The recent emergence of hardware architectures characterized by many-core or accelerated processors has opened new opportunities for concurrent programming models taking advantage of both SIMD and SIMT architectures. GeantV, a next generation detector simulation, has been designed to exploit both the vector capability of mainstream CPUs and multi-threading capabilities of coprocessors including NVidia GPUs and Intel Xeon Phi. The characteristics of these architectures are very different in terms of the vectorization depth and type of parallelization needed to achieve optimal performance. In this paper we describe implementation of electromagnetic physics models developed for parallel computing architectures as a part of the GeantV project. Results of preliminary performance evaluation and physics validation are presented as well.
Parallel architectures for computing cyclic convolutions
NASA Technical Reports Server (NTRS)
Yeh, C.-S.; Reed, I. S.; Truong, T. K.
1983-01-01
In the paper two parallel architectural structures are developed to compute one-dimensional cyclic convolutions. The first structure is based on the Chinese remainder theorem and Kung's pipelined array. The second structure is a direct mapping from the mathematical definition of a cyclic convolution to a computational architecture. To compute a d-point cyclic convolution the first structure needs d/2 inner product cells, while the second structure and Kung's linear array require d cells. However, to compute a cyclic convolution, the second structure requires less time than both the first structure and Kung's linear array. Another application of the second structure is to multiply a Toeplitz matrix by a vector. A table is listed to compare these two structures and Kung's linear array. Both structures are simple and regular and are therefore suitable for VLSI implementation.
Highly parallel computer architecture for robotic computation
NASA Technical Reports Server (NTRS)
Fijany, Amir (Inventor); Bejczy, Anta K. (Inventor)
1991-01-01
In a computer having a large number of single instruction multiple data (SIMD) processors, each of the SIMD processors has two sets of three individual processor elements controlled by a master control unit and interconnected among a plurality of register file units where data is stored. The register files input and output data in synchronism with a minor cycle clock under control of two slave control units controlling the register file units connected to respective ones of the two sets of processor elements. Depending upon which ones of the register file units are enabled to store or transmit data during a particular minor clock cycle, the processor elements within an SIMD processor are connected in rings or in pipeline arrays, and may exchange data with the internal bus or with neighboring SIMD processors through interface units controlled by respective ones of the two slave control units.
A Simple Physical Optics Algorithm Perfect for Parallel Computing Architecture
NASA Technical Reports Server (NTRS)
Imbriale, W. A.; Cwik, T.
1994-01-01
A reflector antenna computer program based upon a simple discreet approximation of the radiation integral has proven to be extremely easy to adapt to the parallel computing architecture of the modest number of large-gain computing elements such as are used in the Intel iPSC and Touchstone Delta parallel machines.
Nonlinear hierarchical substructural parallelism and computer architecture
NASA Technical Reports Server (NTRS)
Padovan, Joe
1989-01-01
Computer architecture is investigated in conjunction with the algorithmic structures of nonlinear finite-element analysis. To help set the stage for this goal, the development is undertaken by considering the wide-ranging needs associated with the analysis of rolling tires which possess the full range of kinematic, material and boundary condition induced nonlinearity in addition to gross and local cord-matrix material properties.
Parallel algorithms and architecture for computation of manipulator forward dynamics
NASA Technical Reports Server (NTRS)
Fijany, Amir; Bejczy, Antal K.
1989-01-01
Parallel computation of manipulator forward dynamics is investigated. Considering three classes of algorithms for the solution of the problem, that is, the O(n), the O(n exp 2), and the O(n exp 3) algorithms, parallelism in the problem is analyzed. It is shown that the problem belongs to the class of NC and that the time and processors bounds are of O(log2/2n) and O(n exp 4), respectively. However, the fastest stable parallel algorithms achieve the computation time of O(n) and can be derived by parallelization of the O(n exp 3) serial algorithms. Parallel computation of the O(n exp 3) algorithms requires the development of parallel algorithms for a set of fundamentally different problems, that is, the Newton-Euler formulation, the computation of the inertia matrix, decomposition of the symmetric, positive definite matrix, and the solution of triangular systems. Parallel algorithms for this set of problems are developed which can be efficiently implemented on a unique architecture, a triangular array of n(n+2)/2 processors with a simple nearest-neighbor interconnection. This architecture is particularly suitable for VLSI and WSI implementations. The developed parallel algorithm, compared to the best serial O(n) algorithm, achieves an asymptotic speedup of more than two orders-of-magnitude in the computation the forward dynamics.
Panel on future directions in parallel computer architecture
VanTilborg, A.M. )
1989-06-01
One of the program highlights of the 15th Annual International Symposium on Computer Architecture, held May 30 - June 2, 1988 in Honolulu, was a panel session on future directions in parallel computer architecture. The panel was organized and chaired by the author, and was comprised of Prof. Jack Dennis (NASA Ames Research Institute for Advanced Computer Science), Prof. H.T. Kung (Carnegie Mellon), and Dr. Burton Smith (Tera Computer Company). The objective of the panel was to identify the likely trajectory of future parallel computer system progress, particularly from the sandpoint of marketplace acceptance. Approximately 250 attendees participated in the session, in which each panelist began with a ten minute viewgraph explanation of his views, followed by an open and sometimes lively exchange with the audience and fellow panelists. The session ran for ninety minutes.
High performance parallel architectures
Anderson, R.E. )
1989-09-01
In this paper the author describes current high performance parallel computer architectures. A taxonomy is presented to show computer architecture from the user programmer's point-of-view. The effects of the taxonomy upon the programming model are described. Some current architectures are described with respect to the taxonomy. Finally, some predictions about future systems are presented. 5 refs., 1 fig.
NASA Technical Reports Server (NTRS)
Hsia, T. C.; Lu, G. Z.; Han, W. H.
1987-01-01
In advanced robot control problems, on-line computation of inverse Jacobian solution is frequently required. Parallel processing architecture is an effective way to reduce computation time. A parallel processing architecture is developed for the inverse Jacobian (inverse differential kinematic equation) of the PUMA arm. The proposed pipeline/parallel algorithm can be inplemented on an IC chip using systolic linear arrays. This implementation requires 27 processing cells and 25 time units. Computation time is thus significantly reduced.
Jiang, Yuning; Kang, Jinfeng; Wang, Xinan
2017-03-24
Resistive switching memory (RRAM) is considered as one of the most promising devices for parallel computing solutions that may overcome the von Neumann bottleneck of today's electronic systems. However, the existing RRAM-based parallel computing architectures suffer from practical problems such as device variations and extra computing circuits. In this work, we propose a novel parallel computing architecture for pattern recognition by implementing k-nearest neighbor classification on metal-oxide RRAM crossbar arrays. Metal-oxide RRAM with gradual RESET behaviors is chosen as both the storage and computing components. The proposed architecture is tested by the MNIST database. High speed (~100 ns per example) and high recognition accuracy (97.05%) are obtained. The influence of several non-ideal device properties is also discussed, and it turns out that the proposed architecture shows great tolerance to device variations. This work paves a new way to achieve RRAM-based parallel computing hardware systems with high performance.
A Framework to Simulate Semiconductor Devices Using Parallel Computer Architecture
NASA Astrophysics Data System (ADS)
Kumar, Gaurav; Singh, Mandeep; Bulusu, Anand; Trivedi, Gaurav
2016-10-01
Device simulations have become an integral part of semiconductor technology to address many issues (short channel effects, narrow width effects, hot-electron effect) as it goes into nano regime, helping us to continue further with the Moore's Law. TCAD provides a simulation environment to design and develop novel devices, thus a leap forward to study their electrical behaviour in advance. In this paper, a parallel 2D simulator for semiconductor devices using Discontinuous Galerkin Finite Element Method (DG-FEM) is presented. Discontinuous Galerkin (DG) method is used to discretize essential device equations and later these equations are analyzed by using a suitable methodology to find the solution. DG method is characterized to provide more accurate solution as it efficiently conserve the flux and easily handles complex geometries. OpenMP is used to parallelize solution of device equations on manycore processors and a speed of 1.4x is achieved during assembly process of discretization. This study is important for more accurate analysis of novel devices (such as FinFET, GAAFET etc.) on a parallel computing platform and will help us to develop a parallel device simulator which will be able to address this issue efficiently. A case study of PN junction diode is presented to show the effectiveness of proposed approach.
NASA Technical Reports Server (NTRS)
Blech, Richard A.
1987-01-01
The development of numerical methods and software tools for parallel processors can be aided through the use of a hardware test-bed. The test-bed architecture must be flexible enough to support investigations into architecture-algorithm interactions. One way to implement a test-bed is to use a commercial parallel processor. Unfortunately, most commercial parallel processors are fixed in their interconnection and/or processor architecture. In this paper, we describe a modified n cube architecture, called the hypercluster, which is a superset of many other processor and interconnection architectures. The hypercluster is intended to support research into parallel processing of computational fluid and structural mechanics problems which may require a number of different architectural configurations. An example of how a typical partial differential equation solution algorithm maps on to the hypercluster is given.
Final Report: Super Instruction Architecture for Scalable Parallel Computations
Sanders, Beverly Ann; Bartlett, Rodney; Deumens, Erik
2013-12-23
The most advanced methods for reliable and accurate computation of the electronic structure of molecular and nano systems are the coupled-cluster techniques. These high-accuracy methods help us to understand, for example, how biological enzymes operate and contribute to the design of new organic explosives. The ACES III software provides a modern, high-performance implementation of these methods optimized for high performance parallel computer systems, ranging from small clusters typical in individual research groups, through larger clusters available in campus and regional computer centers, all the way to high-end petascale systems at national labs, including exploiting GPUs if available. This project enhanced the ACESIII software package and used it to study interesting scientific problems.
Architecture-Adaptive Computing Environment: A Tool for Teaching Parallel Programming
NASA Technical Reports Server (NTRS)
Dorband, John E.; Aburdene, Maurice F.
2002-01-01
Recently, networked and cluster computation have become very popular. This paper is an introduction to a new C based parallel language for architecture-adaptive programming, aCe C. The primary purpose of aCe (Architecture-adaptive Computing Environment) is to encourage programmers to implement applications on parallel architectures by providing them the assurance that future architectures will be able to run their applications with a minimum of modification. A secondary purpose is to encourage computer architects to develop new types of architectures by providing an easily implemented software development environment and a library of test applications. This new language should be an ideal tool to teach parallel programming. In this paper, we will focus on some fundamental features of aCe C.
Parallel language constructs for tensor product computations on loosely coupled architectures
NASA Technical Reports Server (NTRS)
Mehrotra, Piyush; Vanrosendale, John
1989-01-01
Distributed memory architectures offer high levels of performance and flexibility, but have proven awkard to program. Current languages for nonshared memory architectures provide a relatively low level programming environment, and are poorly suited to modular programming, and to the construction of libraries. A set of language primitives designed to allow the specification of parallel numerical algorithms at a higher level is described. Tensor product array computations are focused on along with a simple but important class of numerical algorithms. The problem of programming 1-D kernal routines is focused on first, such as parallel tridiagonal solvers, and then how such parallel kernels can be combined to form parallel tensor product algorithms is examined.
NASA Technical Reports Server (NTRS)
Fijany, Amir (Inventor); Bejczy, Antal K. (Inventor)
1993-01-01
This is a real-time robotic controller and simulator which is a MIMD-SIMD parallel architecture for interfacing with an external host computer and providing a high degree of parallelism in computations for robotic control and simulation. It includes a host processor for receiving instructions from the external host computer and for transmitting answers to the external host computer. There are a plurality of SIMD microprocessors, each SIMD processor being a SIMD parallel processor capable of exploiting fine grain parallelism and further being able to operate asynchronously to form a MIMD architecture. Each SIMD processor comprises a SIMD architecture capable of performing two matrix-vector operations in parallel while fully exploiting parallelism in each operation. There is a system bus connecting the host processor to the plurality of SIMD microprocessors and a common clock providing a continuous sequence of clock pulses. There is also a ring structure interconnecting the plurality of SIMD microprocessors and connected to the clock for providing the clock pulses to the SIMD microprocessors and for providing a path for the flow of data and instructions between the SIMD microprocessors. The host processor includes logic for controlling the RRCS by interpreting instructions sent by the external host computer, decomposing the instructions into a series of computations to be performed by the SIMD microprocessors, using the system bus to distribute associated data among the SIMD microprocessors, and initiating activity of the SIMD microprocessors to perform the computations on the data by procedure call.
Parallel architectures for vision
Maresca, M. ); Lavin, M.A. ); Li, H. )
1988-08-01
Vision computing involves the execution of a large number of operations on large sets of structured data. Sequential computers cannot achieve the speed required by most of the current applications and therefore parallel architectural solutions have to be explored. In this paper the authors examine the options that drive the design of a vision oriented computer, starting with the analysis of the basic vision computation and communication requirements. They briefly review the classical taxonomy for parallel computers, based on the multiplicity of the instruction and data stream, and apply a recently proposed criterion, the degree of autonomy of each processor, to further classify fine-grain SIMD massively parallel computers. They identify three types of processor autonomy, namely operation autonomy, addressing autonomy, and connection autonomy. For each type they give the basic definitions and show some examples. They focus on the concept of connection autonomy, which they believe is a key point in the development of massively parallel architectures for vision. They show two examples of parallel computers featuring different types of connection autonomy - the Connection Machine and the Polymorphic-Torus - and compare their cost and benefit.
Jiang, Yuning; Kang, Jinfeng; Wang, Xinan
2017-01-01
Resistive switching memory (RRAM) is considered as one of the most promising devices for parallel computing solutions that may overcome the von Neumann bottleneck of today’s electronic systems. However, the existing RRAM-based parallel computing architectures suffer from practical problems such as device variations and extra computing circuits. In this work, we propose a novel parallel computing architecture for pattern recognition by implementing k-nearest neighbor classification on metal-oxide RRAM crossbar arrays. Metal-oxide RRAM with gradual RESET behaviors is chosen as both the storage and computing components. The proposed architecture is tested by the MNIST database. High speed (~100 ns per example) and high recognition accuracy (97.05%) are obtained. The influence of several non-ideal device properties is also discussed, and it turns out that the proposed architecture shows great tolerance to device variations. This work paves a new way to achieve RRAM-based parallel computing hardware systems with high performance. PMID:28338069
NASA Astrophysics Data System (ADS)
Jiang, Yuning; Kang, Jinfeng; Wang, Xinan
2017-03-01
Resistive switching memory (RRAM) is considered as one of the most promising devices for parallel computing solutions that may overcome the von Neumann bottleneck of today’s electronic systems. However, the existing RRAM-based parallel computing architectures suffer from practical problems such as device variations and extra computing circuits. In this work, we propose a novel parallel computing architecture for pattern recognition by implementing k-nearest neighbor classification on metal-oxide RRAM crossbar arrays. Metal-oxide RRAM with gradual RESET behaviors is chosen as both the storage and computing components. The proposed architecture is tested by the MNIST database. High speed (~100 ns per example) and high recognition accuracy (97.05%) are obtained. The influence of several non-ideal device properties is also discussed, and it turns out that the proposed architecture shows great tolerance to device variations. This work paves a new way to achieve RRAM-based parallel computing hardware systems with high performance.
A learnable parallel processing architecture towards unity of memory and computing.
Li, H; Gao, B; Chen, Z; Zhao, Y; Huang, P; Ye, H; Liu, L; Liu, X; Kang, J
2015-08-14
Developing energy-efficient parallel information processing systems beyond von Neumann architecture is a long-standing goal of modern information technologies. The widely used von Neumann computer architecture separates memory and computing units, which leads to energy-hungry data movement when computers work. In order to meet the need of efficient information processing for the data-driven applications such as big data and Internet of Things, an energy-efficient processing architecture beyond von Neumann is critical for the information society. Here we show a non-von Neumann architecture built of resistive switching (RS) devices named "iMemComp", where memory and logic are unified with single-type devices. Leveraging nonvolatile nature and structural parallelism of crossbar RS arrays, we have equipped "iMemComp" with capabilities of computing in parallel and learning user-defined logic functions for large-scale information processing tasks. Such architecture eliminates the energy-hungry data movement in von Neumann computers. Compared with contemporary silicon technology, adder circuits based on "iMemComp" can improve the speed by 76.8% and the power dissipation by 60.3%, together with a 700 times aggressive reduction in the circuit area.
A learnable parallel processing architecture towards unity of memory and computing
Li, H.; Gao, B.; Chen, Z.; Zhao, Y.; Huang, P.; Ye, H.; Liu, L.; Liu, X.; Kang, J.
2015-01-01
Developing energy-efficient parallel information processing systems beyond von Neumann architecture is a long-standing goal of modern information technologies. The widely used von Neumann computer architecture separates memory and computing units, which leads to energy-hungry data movement when computers work. In order to meet the need of efficient information processing for the data-driven applications such as big data and Internet of Things, an energy-efficient processing architecture beyond von Neumann is critical for the information society. Here we show a non-von Neumann architecture built of resistive switching (RS) devices named “iMemComp”, where memory and logic are unified with single-type devices. Leveraging nonvolatile nature and structural parallelism of crossbar RS arrays, we have equipped “iMemComp” with capabilities of computing in parallel and learning user-defined logic functions for large-scale information processing tasks. Such architecture eliminates the energy-hungry data movement in von Neumann computers. Compared with contemporary silicon technology, adder circuits based on “iMemComp” can improve the speed by 76.8% and the power dissipation by 60.3%, together with a 700 times aggressive reduction in the circuit area. PMID:26271243
A learnable parallel processing architecture towards unity of memory and computing
NASA Astrophysics Data System (ADS)
Li, H.; Gao, B.; Chen, Z.; Zhao, Y.; Huang, P.; Ye, H.; Liu, L.; Liu, X.; Kang, J.
2015-08-01
Developing energy-efficient parallel information processing systems beyond von Neumann architecture is a long-standing goal of modern information technologies. The widely used von Neumann computer architecture separates memory and computing units, which leads to energy-hungry data movement when computers work. In order to meet the need of efficient information processing for the data-driven applications such as big data and Internet of Things, an energy-efficient processing architecture beyond von Neumann is critical for the information society. Here we show a non-von Neumann architecture built of resistive switching (RS) devices named “iMemComp”, where memory and logic are unified with single-type devices. Leveraging nonvolatile nature and structural parallelism of crossbar RS arrays, we have equipped “iMemComp” with capabilities of computing in parallel and learning user-defined logic functions for large-scale information processing tasks. Such architecture eliminates the energy-hungry data movement in von Neumann computers. Compared with contemporary silicon technology, adder circuits based on “iMemComp” can improve the speed by 76.8% and the power dissipation by 60.3%, together with a 700 times aggressive reduction in the circuit area.
An architecture for a wafer-scale-implemented MIMD parallel computer
Wang, Chiajiu.
1988-01-01
In this dissertation, a general-purpose parallel computer architecture is proposed and studied. The proposed architecture, called the modified mesh-connected parallel computer (MMCPC) is obtained by enhancing a mesh-connected parallel computer with row buses and column buses. The MMCPC is a multiple instruction multiple data parallel machine. Because of the regular structure and distributed control mechanisms, the MMCPC is suitable for VLSI or WSI implementation. The bus structure of the MMCPC lends itself to configurability and fault tolerance. The MMCPC can be logically configured as a number of different parallel computer topologies. The MMCPC can tolerate as many faulty PE's, located randomly, as there are available spares, resulting in 100% redundancy utilization. The performance of the MMCPC was analyzed by applying a generalized stochastic Petri net graph to the MMCPC. The GSPN performance modeling results show a need for a new processing element (PE). A new PE architecture, able to handle data processing and message passing concurrently, is proposed and the silicon overhead is estimated in comparison with transputer-like PE's. Based upon the proposed PE, optimum sizes of the MMCPC for different program structures are derived. Two routing algorithms for the MMCPC were proposed and studied. Routing analysis was carried out through simulation. The simulation results show that the dynamic routing algorithm out performs the deterministic routing algorithm.
Parallelizing Navier-Stokes Computations on a Variety of Architectural Platforms
NASA Technical Reports Server (NTRS)
Jayasimha, D. N.; Hayder, M. E.; Pillay, S. K.
1997-01-01
We study the computational, communication, and scalability characteristics of a Computational Fluid Dynamics application, which solves the time accurate flow field of a jet using the compressible Navier-Stokes equations, on a variety of parallel architectural platforms. The platforms chosen for this study are a cluster of workstations (the LACE experimental testbed at NASA Lewis), a shared memory multiprocessor (the Cray YMP), distributed memory multiprocessors with different topologies-the IBM SP and the Cray T3D. We investigate the impact of various networks, connecting the cluster of workstations, on the performance of the application and the overheads induced by popular message passing libraries used for parallelization. The work also highlights the importance of matching the memory bandwidth to the processor speed for good single processor performance. By studying the performance of an application on a variety of architectures, we are able to point out the strengths and weaknesses of each of the example computing platforms.
An Evaluation of Architectural Platforms for Parallel Navier-Stokes Computations
NASA Technical Reports Server (NTRS)
Jayasimha, D. N.; Hayder, M. E.; Pillay, S. K.
1996-01-01
We study the computational, communication, and scalability characteristics of a computational fluid dynamics application, which solves the time accurate flow field of a jet using the compressible Navier-Stokes equations, on a variety of parallel architecture platforms. The platforms chosen for this study are a cluster of workstations (the LACE experimental testbed at NASA Lewis), a shared memory multiprocessor (the Cray YMP), and distributed memory multiprocessors with different topologies - the IBM SP and the Cray T3D. We investigate the impact of various networks connecting the cluster of workstations on the performance of the application and the overheads induced by popular message passing libraries used for parallelization. The work also highlights the importance of matching the memory bandwidth to the processor speed for good single processor performance. By studying the performance of an application on a variety of architectures, we are able to point out the strengths and weaknesses of each of the example computing platforms.
Parallel Subconvolution Filtering Architectures
NASA Technical Reports Server (NTRS)
Gray, Andrew A.
2003-01-01
These architectures are based on methods of vector processing and the discrete-Fourier-transform/inverse-discrete- Fourier-transform (DFT-IDFT) overlap-and-save method, combined with time-block separation of digital filters into frequency-domain subfilters implemented by use of sub-convolutions. The parallel-processing method implemented in these architectures enables the use of relatively small DFT-IDFT pairs, while filter tap lengths are theoretically unlimited. The size of a DFT-IDFT pair is determined by the desired reduction in processing rate, rather than on the order of the filter that one seeks to implement. The emphasis in this report is on those aspects of the underlying theory and design rules that promote computational efficiency, parallel processing at reduced data rates, and simplification of the designs of very-large-scale integrated (VLSI) circuits needed to implement high-order filters and correlators.
Not Available
1991-10-23
An account of the Caltech Concurrent Computation Program (C{sup 3}P), a five year project that focused on answering the question: Can parallel computers be used to do large-scale scientific computations '' As the title indicates, the question is answered in the affirmative, by implementing numerous scientific applications on real parallel computers and doing computations that produced new scientific results. In the process of doing so, C{sup 3}P helped design and build several new computers, designed and implemented basic system software, developed algorithms for frequently used mathematical computations on massively parallel machines, devised performance models and measured the performance of many computers, and created a high performance computing facility based exclusively on parallel computers. While the initial focus of C{sup 3}P was the hypercube architecture developed by C. Seitz, many of the methods developed and lessons learned have been applied successfully on other massively parallel architectures.
NASA Technical Reports Server (NTRS)
Denning, Peter J.; Tichy, Walter F.
1990-01-01
Among the highly parallel computing architectures required for advanced scientific computation, those designated 'MIMD' and 'SIMD' have yielded the best results to date. The present development status evaluation of such architectures shown neither to have attained a decisive advantage in most near-homogeneous problems' treatment; in the cases of problems involving numerous dissimilar parts, however, such currently speculative architectures as 'neural networks' or 'data flow' machines may be entailed. Data flow computers are the most practical form of MIMD fine-grained parallel computers yet conceived; they automatically solve the problem of assigning virtual processors to the real processors in the machine.
Architecture Adaptive Computing Environment
NASA Technical Reports Server (NTRS)
Dorband, John E.
2006-01-01
Architecture Adaptive Computing Environment (aCe) is a software system that includes a language, compiler, and run-time library for parallel computing. aCe was developed to enable programmers to write programs, more easily than was previously possible, for a variety of parallel computing architectures. Heretofore, it has been perceived to be difficult to write parallel programs for parallel computers and more difficult to port the programs to different parallel computing architectures. In contrast, aCe is supportable on all high-performance computing architectures. Currently, it is supported on LINUX clusters. aCe uses parallel programming constructs that facilitate writing of parallel programs. Such constructs were used in single-instruction/multiple-data (SIMD) programming languages of the 1980s, including Parallel Pascal, Parallel Forth, C*, *LISP, and MasPar MPL. In aCe, these constructs are extended and implemented for both SIMD and multiple- instruction/multiple-data (MIMD) architectures. Two new constructs incorporated in aCe are those of (1) scalar and virtual variables and (2) pre-computed paths. The scalar-and-virtual-variables construct increases flexibility in optimizing memory utilization in various architectures. The pre-computed-paths construct enables the compiler to pre-compute part of a communication operation once, rather than computing it every time the communication operation is performed.
HTMT-class Latency Tolerant Parallel Architecture for Petaflops Scale Computation
NASA Technical Reports Server (NTRS)
Sterling, Thomas; Bergman, Larry
2000-01-01
Computational Aero Sciences and other numeric intensive computation disciplines demand computing throughputs substantially greater than the Teraflops scale systems only now becoming available. The related fields of fluids, structures, thermal, combustion, and dynamic controls are among the interdisciplinary areas that in combination with sufficient resolution and advanced adaptive techniques may force performance requirements towards Petaflops. This will be especially true for compute intensive models such as Navier-Stokes are or when such system models are only part of a larger design optimization computation involving many design points. Yet recent experience with conventional MPP configurations comprising commodity processing and memory components has shown that larger scale frequently results in higher programming difficulty and lower system efficiency. While important advances in system software and algorithms techniques have had some impact on efficiency and programmability for certain classes of problems, in general it is unlikely that software alone will resolve the challenges to higher scalability. As in the past, future generations of high-end computers may require a combination of hardware architecture and system software advances to enable efficient operation at a Petaflops level. The NASA led HTMT project has engaged the talents of a broad interdisciplinary team to develop a new strategy in high-end system architecture to deliver petaflops scale computing in the 2004/5 timeframe. The Hybrid-Technology, MultiThreaded parallel computer architecture incorporates several advanced technologies in combination with an innovative dynamic adaptive scheduling mechanism to provide unprecedented performance and efficiency within practical constraints of cost, complexity, and power consumption. The emerging superconductor Rapid Single Flux Quantum electronics can operate at 100 GHz (the record is 770 GHz) and one percent of the power required by convention
NASA Astrophysics Data System (ADS)
Nakamura, Kazuhiro; Yamamoto, Masatoshi; Takagi, Kazuyoshi; Takagi, Naofumi
In this paper, a fast and memory-efficient VLSI architecture for output probability computations of continuous Hidden Markov Models (HMMs) is presented. These computations are the most time-consuming part of HMM-based recognition systems. High-speed VLSI architectures with small registers and low-power dissipation are required for the development of mobile embedded systems with capable human interfaces. We demonstrate store-based block parallel processing (StoreBPP) for output probability computations and present a VLSI architecture that supports it. When the number of HMM states is adequate for accurate recognition, compared with conventional stream-based block parallel processing (StreamBPP) architectures, the proposed architecture requires fewer registers and processing elements and less processing time. The processing elements used in the StreamBPP architecture are identical to those used in the StoreBPP architecture. From a VLSI architectural viewpoint, a comparison shows the efficiency of the proposed architecture through efficient use of registers for storing input feature vectors and intermediate results during computation.
Wong Unhong; Wong Honcheng; Tang Zesheng
2010-05-21
The smoothed particle hydrodynamics (SPH), which is a class of meshfree particle methods (MPMs), has a wide range of applications from micro-scale to macro-scale as well as from discrete systems to continuum systems. Graphics hardware, originally designed for computer graphics, now provide unprecedented computational power for scientific computation. Particle system needs a huge amount of computations in physical simulation. In this paper, an efficient parallel implementation of a SPH method on graphics hardware using the Compute Unified Device Architecture is developed for fluid simulation. Comparing to the corresponding CPU implementation, our experimental results show that the new approach allows significant speedups of fluid simulation through handling huge amount of computations in parallel on graphics hardware.
NASA Astrophysics Data System (ADS)
Nakamura, Kazuhiro; Shimazaki, Ryo; Yamamoto, Masatoshi; Takagi, Kazuyoshi; Takagi, Naofumi
This paper presents a memory-efficient VLSI architecture for output probability computations (OPCs) of continuous hidden Markov models (HMMs) and likelihood score computations (LSCs). These computations are the most time consuming part of HMM-based isolated word recognition systems. We demonstrate multiple fast store-based block parallel processing (MultipleFastStoreBPP) for OPCs and LSCs and present a VLSI architecture that supports it. Compared with conventional fast store-based block parallel processing (FastStoreBPP) and stream-based block parallel processing (StreamBPP) architectures, the proposed architecture requires fewer registers and less processing time. The processing elements (PEs) used in the FastStoreBPP and StreamBPP architectures are identical to those used in the MultipleFastStoreBPP architecture. From a VLSI architectural viewpoint, a comparison shows that the proposed architecture is an improvement over the others, through efficient use of PEs and registers for storing input feature vectors.
Andrade, Xavier; Alberdi-Rodriguez, Joseba; Strubbe, David A; Oliveira, Micael J T; Nogueira, Fernando; Castro, Alberto; Muguerza, Javier; Arruabarrena, Agustin; Louie, Steven G; Aspuru-Guzik, Alán; Rubio, Angel; Marques, Miguel A L
2012-06-13
Octopus is a general-purpose density-functional theory (DFT) code, with a particular emphasis on the time-dependent version of DFT (TDDFT). In this paper we present the ongoing efforts to achieve the parallelization of octopus. We focus on the real-time variant of TDDFT, where the time-dependent Kohn-Sham equations are directly propagated in time. This approach has great potential for execution in massively parallel systems such as modern supercomputers with thousands of processors and graphics processing units (GPUs). For harvesting the potential of conventional supercomputers, the main strategy is a multi-level parallelization scheme that combines the inherent scalability of real-time TDDFT with a real-space grid domain-partitioning approach. A scalable Poisson solver is critical for the efficiency of this scheme. For GPUs, we show how using blocks of Kohn-Sham states provides the required level of data parallelism and that this strategy is also applicable for code optimization on standard processors. Our results show that real-time TDDFT, as implemented in octopus, can be the method of choice for studying the excited states of large molecular systems in modern parallel architectures.
NASA Astrophysics Data System (ADS)
Andrade, Xavier; Alberdi-Rodriguez, Joseba; Strubbe, David A.; Oliveira, Micael J. T.; Nogueira, Fernando; Castro, Alberto; Muguerza, Javier; Arruabarrena, Agustin; Louie, Steven G.; Aspuru-Guzik, Alán; Rubio, Angel; Marques, Miguel A. L.
2012-06-01
Octopus is a general-purpose density-functional theory (DFT) code, with a particular emphasis on the time-dependent version of DFT (TDDFT). In this paper we present the ongoing efforts to achieve the parallelization of octopus. We focus on the real-time variant of TDDFT, where the time-dependent Kohn-Sham equations are directly propagated in time. This approach has great potential for execution in massively parallel systems such as modern supercomputers with thousands of processors and graphics processing units (GPUs). For harvesting the potential of conventional supercomputers, the main strategy is a multi-level parallelization scheme that combines the inherent scalability of real-time TDDFT with a real-space grid domain-partitioning approach. A scalable Poisson solver is critical for the efficiency of this scheme. For GPUs, we show how using blocks of Kohn-Sham states provides the required level of data parallelism and that this strategy is also applicable for code optimization on standard processors. Our results show that real-time TDDFT, as implemented in octopus, can be the method of choice for studying the excited states of large molecular systems in modern parallel architectures.
Bipartite memory network architectures for parallel processing
Smith, W.; Kale, L.V. . Dept. of Computer Science)
1990-01-01
Parallel architectures are boradly classified as either shared memory or distributed memory architectures. In this paper, the authors propose a third family of architectures, called bipartite memory network architectures. In this architecture, processors and memory modules constitute a bipartite graph, where each processor is allowed to access a small subset of the memory modules, and each memory module allows access from a small set of processors. The architecture is particularly suitable for computations requiring dynamic load balancing. The authors explore the properties of this architecture by examining the Perfect Difference set based topology for the graph. Extensions of this topology are also suggested.
Architectures for reasoning in parallel
NASA Technical Reports Server (NTRS)
Hall, Lawrence O.
1989-01-01
The research conducted has dealt with rule-based expert systems. The algorithms that may lead to effective parallelization of them were investigated. Both the forward and backward chained control paradigms were investigated in the course of this work. The best computer architecture for the developed and investigated algorithms has been researched. Two experimental vehicles were developed to facilitate this research. They are Backpac, a parallel backward chained rule-based reasoning system and Datapac, a parallel forward chained rule-based reasoning system. Both systems have been written in Multilisp, a version of Lisp which contains the parallel construct, future. Applying the future function to a function causes the function to become a task parallel to the spawning task. Additionally, Backpac and Datapac have been run on several disparate parallel processors. The machines are an Encore Multimax with 10 processors, the Concert Multiprocessor with 64 processors, and a 32 processor BBN GP1000. Both the Concert and the GP1000 are switch-based machines. The Multimax has all its processors hung off a common bus. All are shared memory machines, but have different schemes for sharing the memory and different locales for the shared memory. The main results of the investigations come from experiments on the 10 processor Encore and the Concert with partitions of 32 or less processors. Additionally, experiments have been run with a stripped down version of EMYCIN.
ERIC Educational Resources Information Center
Amenyo, John-Thones
2012-01-01
Carefully engineered playable games can serve as vehicles for students and practitioners to learn and explore the programming of advanced computer architectures to execute applications, such as high performance computing (HPC) and complex, inter-networked, distributed systems. The article presents families of playable games that are grounded in…
Parallel Navier-Stokes computations on shared and distributed memory architectures
NASA Technical Reports Server (NTRS)
Hayder, M. Ehtesham; Jayasimha, D. N.; Pillay, Sasi Kumar
1995-01-01
We study a high order finite difference scheme to solve the time accurate flow field of a jet using the compressible Navier-Stokes equations. As part of our ongoing efforts, we have implemented our numerical model on three parallel computing platforms to study the computational, communication, and scalability characteristics. The platforms chosen for this study are a cluster of workstations connected through fast networks (the LACE experimental testbed at NASA Lewis), a shared memory multiprocessor (the Cray YMP), and a distributed memory multiprocessor (the IBM SPI). Our focus in this study is on the LACE testbed. We present some results for the Cray YMP and the IBM SP1 mainly for comparison purposes. On the LACE testbed, we study: (1) the communication characteristics of Ethernet, FDDI, and the ALLNODE networks and (2) the overheads induced by the PVM message passing library used for parallelizing the application. We demonstrate that clustering of workstations is effective and has the potential to be computationally competitive with supercomputers at a fraction of the cost.
NASA Technical Reports Server (NTRS)
Moxon, Bruce C.; Green, John A.
1990-01-01
A high-performance platform for development of real-time helicopter flight simulations based on a simulation development and analysis platform combining a parallel simulation development and analysis environment with a scalable multiprocessor computer system is described. Simulation functional decomposition is covered, including the sequencing and data dependency of simulation modules and simulation functional mapping to multiple processors. The multiprocessor-based implementation of a blade-element simulation of the UH-60 helicopter is presented, and a prototype developed for a TC2000 computer is generalized in order to arrive at a portable multiprocessor software architecture. It is pointed out that the proposed approach coupled with a pilot's station creates a setting in which simulation engineers, computer scientists, and pilots can work together in the design and evaluation of advanced real-time helicopter simulations.
NASA Astrophysics Data System (ADS)
Mielikainen, Jarno; Huang, Bormin; Wang, Jun; Allen Huang, H.-L.; Goldberg, Mitchell D.
2013-03-01
In recent years, graphics processing units (GPUs) have emerged as a low-cost, low-power and a very high performance alternative to conventional central processing units (CPUs). The latest GPUs offer a speedup of two-to-three orders of magnitude over CPU for various science and engineering applications. The Weather Research and Forecasting (WRF) model is the latest-generation numerical weather prediction model. It has been designed to serve both operational forecasting and atmospheric research needs. It proves useful for a broad spectrum of applications for domain scales ranging from meters to hundreds of kilometers. WRF computes an approximate solution to the differential equations which govern the air motion of the whole atmosphere. Kessler microphysics module in WRF is a simple warm cloud scheme that includes water vapor, cloud water and rain. Microphysics processes which are modeled are rain production, fall and evaporation. The accretion and auto-conversion of cloud water processes are also included along with the production of cloud water from condensation. In this paper, we develop an efficient WRF Kessler microphysics scheme which runs on Graphics Processing Units (GPUs) using the NVIDIA Compute Unified Device Architecture (CUDA). The GPU-based implementation of Kessler microphysics scheme achieves a significant speedup of 70× over its CPU based single-threaded counterpart. When a 4 GPU system is used, we achieve an overall speedup of 132× as compared to the single thread CPU version.
DeHart, Mark D; Williams, Mark L; Bowman, Stephen M
2010-01-01
The SCALE computational architecture has remained basically the same since its inception 30 years ago, although constituent modules and capabilities have changed significantly. This SCALE concept was intended to provide a framework whereby independent codes can be linked to provide a more comprehensive capability than possible with the individual programs - allowing flexibility to address a wide variety of applications. However, the current system was designed originally for mainframe computers with a single CPU and with significantly less memory than today's personal computers. It has been recognized that the present SCALE computation system could be restructured to take advantage of modern hardware and software capabilities, while retaining many of the modular features of the present system. Preliminary work is being done to define specifications and capabilities for a more advanced computational architecture. This paper describes the state of current SCALE development activities and plans for future development. With the release of SCALE 6.1 in 2010, a new phase of evolutionary development will be available to SCALE users within the TRITON and NEWT modules. The SCALE (Standardized Computer Analyses for Licensing Evaluation) code system developed by Oak Ridge National Laboratory (ORNL) provides a comprehensive and integrated package of codes and nuclear data for a wide range of applications in criticality safety, reactor physics, shielding, isotopic depletion and decay, and sensitivity/uncertainty (S/U) analysis. Over the last three years, since the release of version 5.1 in 2006, several important new codes have been introduced within SCALE, and significant advances applied to existing codes. Many of these new features became available with the release of SCALE 6.0 in early 2009. However, beginning with SCALE 6.1, a first generation of parallel computing is being introduced. In addition to near-term improvements, a plan for longer term SCALE enhancement
DFT-Based Electronic Structure Calculations on Hybrid and Massively Parallel Computer Architectures
NASA Astrophysics Data System (ADS)
Briggs, Emil; Hodak, Miroslav; Lu, Wenchang; Bernholc, Jerry
2014-03-01
The latest generation of supercomputers is capable of multi-petaflop peak performance, achieved by using thousands of multi-core CPU's and often coupled with thousands of GPU's. However, efficient utilization of this computing power for electronic structure calculations presents significant challenges. We describe adaptations of the Real-Space Multigrid (RMG) code that enable it to scale well to thousands of nodes. A hybrid technique that uses one MPI process per node, rather than on per core was adopted with OpenMP and POSIX threads used for intra-node parallelization. This reduces the number of MPI process's by an order of magnitude or more and improves individual node memory utilization. GPU accelerators are also becoming common and are capable of extremely high performance for vector workloads. However, they typically have much lower scalar performance than CPU's, so achieving good performance requires that the workload is carefully partitioned and data transfer between CPU and GPU is optimized. We have used a hybrid approach utilizing MPI/OpenMP/POSIX threads and GPU accelerators to reach excellent scaling to over 100,000 cores on a Cray XE6 platform as well as a factor of three performance improvement when using a Cray XK7 system with CPU-GPU nodes.
NASA Astrophysics Data System (ADS)
Romano, Paul Kollath
Monte Carlo particle transport methods are being considered as a viable option for high-fidelity simulation of nuclear reactors. While Monte Carlo methods offer several potential advantages over deterministic methods, there are a number of algorithmic shortcomings that would prevent their immediate adoption for full-core analyses. In this thesis, algorithms are proposed both to ameliorate the degradation in parallel efficiency typically observed for large numbers of processors and to offer a means of decomposing large tally data that will be needed for reactor analysis. A nearest-neighbor fission bank algorithm was proposed and subsequently implemented in the OpenMC Monte Carlo code. A theoretical analysis of the communication pattern shows that the expected cost is O( N ) whereas traditional fission bank algorithms are O(N) at best. The algorithm was tested on two supercomputers, the Intrepid Blue Gene/P and the Titan Cray XK7, and demonstrated nearly linear parallel scaling up to 163,840 processor cores on a full-core benchmark problem. An algorithm for reducing network communication arising from tally reduction was analyzed and implemented in OpenMC. The proposed algorithm groups only particle histories on a single processor into batches for tally purposes---in doing so it prevents all network communication for tallies until the very end of the simulation. The algorithm was tested, again on a full-core benchmark, and shown to reduce network communication substantially. A model was developed to predict the impact of load imbalances on the performance of domain decomposed simulations. The analysis demonstrated that load imbalances in domain decomposed simulations arise from two distinct phenomena: non-uniform particle densities and non-uniform spatial leakage. The dominant performance penalty for domain decomposition was shown to come from these physical effects rather than insufficient network bandwidth or high latency. The model predictions were verified with
Parallel Logic Programming Architecture
1990-04-01
cooperation in distributed problem solving. IEEE Transactions on Systems, Man, and Cybernetics, SMC-l(1), 61-70. 33. Tanenbaum, A. S. (1988). Structured ... Computer Organization, Englewood Cliffs, NJ: Prentice-Hall. 34. Tanenbaum, A. S. (1988). Computer Networks. Englewood Cliffs, NJ: Prentice-Hall. 35
2007-03-01
2003. 23. IBM. How to Secure an Insecure OS. Technical report, IBM Corp., 2002. 24. Intel. LaGrande Technlogy Architectural Overview. Technology...and Ezzat A. Dabbish. “Digital Rights Management in a 3G Mobile Phone and Beyond”. DRM’03. October 2003. 40. Molina, Jesus and William Arbaugh
Massively parallel processor computer
NASA Technical Reports Server (NTRS)
Fung, L. W. (Inventor)
1983-01-01
An apparatus for processing multidimensional data with strong spatial characteristics, such as raw image data, characterized by a large number of parallel data streams in an ordered array is described. It comprises a large number (e.g., 16,384 in a 128 x 128 array) of parallel processing elements operating simultaneously and independently on single bit slices of a corresponding array of incoming data streams under control of a single set of instructions. Each of the processing elements comprises a bidirectional data bus in communication with a register for storing single bit slices together with a random access memory unit and associated circuitry, including a binary counter/shift register device, for performing logical and arithmetical computations on the bit slices, and an I/O unit for interfacing the bidirectional data bus with the data stream source. The massively parallel processor architecture enables very high speed processing of large amounts of ordered parallel data, including spatial translation by shifting or sliding of bits vertically or horizontally to neighboring processing elements.
High Performance Parallel Architectures
NASA Technical Reports Server (NTRS)
El-Ghazawi, Tarek; Kaewpijit, Sinthop
1998-01-01
Traditional remote sensing instruments are multispectral, where observations are collected at a few different spectral bands. Recently, many hyperspectral instruments, that can collect observations at hundreds of bands, have been operational. Furthermore, there have been ongoing research efforts on ultraspectral instruments that can produce observations at thousands of spectral bands. While these remote sensing technology developments hold great promise for new findings in the area of Earth and space science, they present many challenges. These include the need for faster processing of such increased data volumes, and methods for data reduction. Dimension Reduction is a spectral transformation, aimed at concentrating the vital information and discarding redundant data. One such transformation, which is widely used in remote sensing, is the Principal Components Analysis (PCA). This report summarizes our progress on the development of a parallel PCA and its implementation on two Beowulf cluster configuration; one with fast Ethernet switch and the other with a Myrinet interconnection. Details of the implementation and performance results, for typical sets of multispectral and hyperspectral NASA remote sensing data, are presented and analyzed based on the algorithm requirements and the underlying machine configuration. It will be shown that the PCA application is quite challenging and hard to scale on Ethernet-based clusters. However, the measurements also show that a high- performance interconnection network, such as Myrinet, better matches the high communication demand of PCA and can lead to a more efficient PCA execution.
NASA Technical Reports Server (NTRS)
Gentzsch, W.
1982-01-01
Problems which can arise with vector and parallel computers are discussed in a user oriented context. Emphasis is placed on the algorithms used and the programming techniques adopted. Three recently developed supercomputers are examined and typical application examples are given in CRAY FORTRAN, CYBER 205 FORTRAN and DAP (distributed array processor) FORTRAN. The systems performance is compared. The addition of parts of two N x N arrays is considered. The influence of the architecture on the algorithms and programming language is demonstrated. Numerical analysis of magnetohydrodynamic differential equations by an explicit difference method is illustrated, showing very good results for all three systems. The prognosis for supercomputer development is assessed.
NASA Technical Reports Server (NTRS)
Fijany, Amir; Toomarian, Benny N.
2000-01-01
-based architectures for highly parallel and systolic computation of signal/image processing applications, such as FFT and Wavelet and Wlash-Hadamard Transforms.
Kirk, B.L.; Sartori, E.
1997-06-01
Subsequent to the introduction of High Performance Computing in the developed countries, the Organization for Economic Cooperation and Development/Nuclear Energy Agency (OECD/NEA) created the Task Force on Adapting Computer Codes in Nuclear Applications to Parallel Architectures (under the guidance of the Nuclear Science Committee`s Working Party on Advanced Computing) to study the growth area in supercomputing and its applicability to the nuclear community`s computer codes. The result has been four years of investigation for the Task Force in different subject fields - deterministic and Monte Carlo radiation transport, computational mechanics and fluid dynamics, nuclear safety, atmospheric models and waste management.
The science of computing - Parallel computation
NASA Technical Reports Server (NTRS)
Denning, P. J.
1985-01-01
Although parallel computation architectures have been known for computers since the 1920s, it was only in the 1970s that microelectronic components technologies advanced to the point where it became feasible to incorporate multiple processors in one machine. Concommitantly, the development of algorithms for parallel processing also lagged due to hardware limitations. The speed of computing with solid-state chips is limited by gate switching delays. The physical limit implies that a 1 Gflop operational speed is the maximum for sequential processors. A computer recently introduced features a 'hypercube' architecture with 128 processors connected in networks at 5, 6 or 7 points per grid, depending on the design choice. Its computing speed rivals that of supercomputers, but at a fraction of the cost. The added speed with less hardware is due to parallel processing, which utilizes algorithms representing different parts of an equation that can be broken into simpler statements and processed simultaneously. Present, highly developed computer languages like FORTRAN, PASCAL, COBOL, etc., rely on sequential instructions. Thus, increased emphasis will now be directed at parallel processing algorithms to exploit the new architectures.
Research in parallel computing
NASA Technical Reports Server (NTRS)
Ortega, James M.; Henderson, Charles
1994-01-01
This report summarizes work on parallel computations for NASA Grant NAG-1-1529 for the period 1 Jan. - 30 June 1994. Short summaries on highly parallel preconditioners, target-specific parallel reductions, and simulation of delta-cache protocols are provided.
Parallel and Distributed Computing.
1986-12-12
program was devoted to parallel and distributed computing . Support for this part of the program was obtained from the present Army contract and a...Umesh Vazirani. A workshop on parallel and distributed computing was held from May 19 to May 23, 1986 and drew 141 participants. Keywords: Mathematical programming; Protocols; Randomized algorithms. (Author)
Rosa, Massimiliano; Warsa, James S; Perks, Michael
2010-12-14
We have implemented a cell-wise, block-Gauss-Seidel (bGS) iterative algorithm, for the solution of the S{sub n} transport equations on the Roadrunner hybrid, parallel computer architecture. A compute node of this massively parallel machine comprises AMD Opteron cores that are linked to a Cell Broadband Engine{trademark} (Cell/B.E.). LAPACK routines have been ported to the Cell/B.E. in order to make use of its parallel Synergistic Processing Elements (SPEs). The bGS algorithm is based on the LU factorization and solution of a linear system that couples the fluxes for all S{sub n} angles and energy groups on a mesh cell. For every cell of a mesh that has been parallel decomposed on the higher-level Opteron processors, a linear system is transferred to the Cell/B.E. and the parallel LAPACK routines are used to compute a solution, which is then transferred back to the Opteron, where the rest of the computations for the S{sub n} transport problem take place. Compared to standard parallel machines, a hundred-fold speedup of the bGS was observed on the hybrid Roadrunner architecture. Numerical experiments with strong and weak parallel scaling demonstrate the bGS method is viable and compares favorably to full parallel sweeps (FPS) on two-dimensional, unstructured meshes when it is applied to optically thick, multi-material problems. As expected, however, it is not as efficient as FPS in optically thin problems.
NASA Astrophysics Data System (ADS)
Tramm, John R.; Gunow, Geoffrey; He, Tim; Smith, Kord S.; Forget, Benoit; Siegel, Andrew R.
2016-05-01
In this study we present and analyze a formulation of the 3D Method of Characteristics (MOC) technique applied to the simulation of full core nuclear reactors. Key features of the algorithm include a task-based parallelism model that allows independent MOC tracks to be assigned to threads dynamically, ensuring load balancing, and a wide vectorizable inner loop that takes advantage of modern SIMD computer architectures. The algorithm is implemented in a set of highly optimized proxy applications in order to investigate its performance characteristics on CPU, GPU, and Intel Xeon Phi architectures. Speed, power, and hardware cost efficiencies are compared. Additionally, performance bottlenecks are identified for each architecture in order to determine the prospects for continued scalability of the algorithm on next generation HPC architectures.
Parallel Architectures and Parallel Algorithms for Integrated Vision Systems. Ph.D. Thesis
NASA Technical Reports Server (NTRS)
Choudhary, Alok Nidhi
1989-01-01
Computer vision is regarded as one of the most complex and computationally intensive problems. An integrated vision system (IVS) is a system that uses vision algorithms from all levels of processing to perform for a high level application (e.g., object recognition). An IVS normally involves algorithms from low level, intermediate level, and high level vision. Designing parallel architectures for vision systems is of tremendous interest to researchers. Several issues are addressed in parallel architectures and parallel algorithms for integrated vision systems.
Parallel Architectures for Planetary Exploration Requirements (PAPER)
NASA Technical Reports Server (NTRS)
Cezzar, Ruknet; Sen, Ranjan K.
1989-01-01
The Parallel Architectures for Planetary Exploration Requirements (PAPER) project is essentially research oriented towards technology insertion issues for NASA's unmanned planetary probes. It was initiated to complement and augment the long-term efforts for space exploration with particular reference to NASA/LaRC's (NASA Langley Research Center) research needs for planetary exploration missions of the mid and late 1990s. The requirements for space missions as given in the somewhat dated Advanced Information Processing Systems (AIPS) requirements document are contrasted with the new requirements from JPL/Caltech involving sensor data capture and scene analysis. It is shown that more stringent requirements have arisen as a result of technological advancements. Two possible architectures, the AIPS Proof of Concept (POC) configuration and the MAX Fault-tolerant dataflow multiprocessor, were evaluated. The main observation was that the AIPS design is biased towards fault tolerance and may not be an ideal architecture for planetary and deep space probes due to high cost and complexity. The MAX concepts appears to be a promising candidate, except that more detailed information is required. The feasibility for adding neural computation capability to this architecture needs to be studied. Key impact issues for architectural design of computing systems meant for planetary missions were also identified.
Parallel machine architecture and compiler design facilities
NASA Technical Reports Server (NTRS)
Kuck, David J.; Yew, Pen-Chung; Padua, David; Sameh, Ahmed; Veidenbaum, Alex
1990-01-01
The objective is to provide an integrated simulation environment for studying and evaluating various issues in designing parallel systems, including machine architectures, parallelizing compiler techniques, and parallel algorithms. The status of Delta project (which objective is to provide a facility to allow rapid prototyping of parallelized compilers that can target toward different machine architectures) is summarized. Included are the surveys of the program manipulation tools developed, the environmental software supporting Delta, and the compiler research projects in which Delta has played a role.
Parallel architectures for iterative methods on adaptive, block structured grids
NASA Technical Reports Server (NTRS)
Gannon, D.; Vanrosendale, J.
1983-01-01
A parallel computer architecture well suited to the solution of partial differential equations in complicated geometries is proposed. Algorithms for partial differential equations contain a great deal of parallelism. But this parallelism can be difficult to exploit, particularly on complex problems. One approach to extraction of this parallelism is the use of special purpose architectures tuned to a given problem class. The architecture proposed here is tuned to boundary value problems on complex domains. An adaptive elliptic algorithm which maps effectively onto the proposed architecture is considered in detail. Two levels of parallelism are exploited by the proposed architecture. First, by making use of the freedom one has in grid generation, one can construct grids which are locally regular, permitting a one to one mapping of grids to systolic style processor arrays, at least over small regions. All local parallelism can be extracted by this approach. Second, though there may be a regular global structure to the grids constructed, there will be parallelism at this level. One approach to finding and exploiting this parallelism is to use an architecture having a number of processor clusters connected by a switching network. The use of such a network creates a highly flexible architecture which automatically configures to the problem being solved.
Parallel computer methods for eigenvalue extraction
NASA Technical Reports Server (NTRS)
Akl, Fred
1988-01-01
A new numerical algorithm for the solution of large-order eigenproblems typically encountered in linear elastic finite element systems is presented. The architecture of parallel processing is used in the algorithm to achieve increased speed and efficiency of calculations. The algorithm is based on the frontal technique for the solution of linear simultaneous equations and the modified subspace eigenanalysis method for the solution of the eigenproblem. The advantages of this new algorithm in parallel computer architecture are discussed.
Parallel algorithms and architectures for the manipulator inertia matrix
Amin-Javaheri, M.
1989-01-01
Several parallel algorithms and architectures to compute the manipulator inertia matrix in real time are proposed. An O(N) and an O(log{sub 2}N) parallel algorithm based upon recursive computation of the inertial parameters of sets of composite rigid bodies are formulated. One- and two-dimensional systolic architectures are presented to implement the O(N) parallel algorithm. A cube architecture is employed to implement the diagonal element of the inertia matrix in O(log{sub 2}N) time and the upper off-diagonal elements in O(N) time. The resulting K{sub 1}O(N) + K{sub 2}O(log{sub 2}N) parallel algorithm is more efficient for a cube network implementation. All the architectural configurations are based upon a VLSI Robotics Processor exploiting fine-grain parallelism. In evaluation all the architectural configurations, significant performance parameters such as I/O time and idle time due to processor synchronization as well as CPU utilization and on-chip memory size are fully included. The O(N) and O(log{sub 2}N) parallel algorithms adhere to the precedence relationships among the processors. In order to achieve a higher speedup factor; however, parallel algorithms in conjunction with Non-Strict Computational Models are devised to relax interprocess precedence, and as a result, to decrease the effective computational delays. The effectiveness of the Non-strict Computational Algorithms is verified by computer simulations, based on a PUMA 560 robot manipulator. It is demonstrated that a combination of parallel algorithms and architectures results in a very effective approach to achieve real-time response for computing the manipulator inertia matrix.
Kalman Filter Tracking on Parallel Architectures
NASA Astrophysics Data System (ADS)
Cerati, Giuseppe; Elmer, Peter; Krutelyov, Slava; Lantz, Steven; Lefebvre, Matthieu; McDermott, Kevin; Riley, Daniel; Tadel, Matevž; Wittich, Peter; Würthwein, Frank; Yagil, Avi
2016-11-01
Power density constraints are limiting the performance improvements of modern CPUs. To address this we have seen the introduction of lower-power, multi-core processors such as GPGPU, ARM and Intel MIC. In order to achieve the theoretical performance gains of these processors, it will be necessary to parallelize algorithms to exploit larger numbers of lightweight cores and specialized functions like large vector units. Track finding and fitting is one of the most computationally challenging problems for event reconstruction in particle physics. At the High-Luminosity Large Hadron Collider (HL-LHC), for example, this will be by far the dominant problem. The need for greater parallelism has driven investigations of very different track finding techniques such as Cellular Automata or Hough Transforms. The most common track finding techniques in use today, however, are those based on a Kalman filter approach. Significant experience has been accumulated with these techniques on real tracking detector systems, both in the trigger and offline. They are known to provide high physics performance, are robust, and are in use today at the LHC. Given the utility of the Kalman filter in track finding, we have begun to port these algorithms to parallel architectures, namely Intel Xeon and Xeon Phi. We report here on our progress towards an end-to-end track reconstruction algorithm fully exploiting vectorization and parallelization techniques in a simplified experimental environment.
Fast Parallel Computation Of Manipulator Inverse Dynamics
NASA Technical Reports Server (NTRS)
Fijany, Amir; Bejczy, Antal K.
1991-01-01
Method for fast parallel computation of inverse dynamics problem, essential for real-time dynamic control and simulation of robot manipulators, undergoing development. Enables exploitation of high degree of parallelism and, achievement of significant computational efficiency, while minimizing various communication and synchronization overheads as well as complexity of required computer architecture. Universal real-time robotic controller and simulator (URRCS) consists of internal host processor and several SIMD processors with ring topology. Architecture modular and expandable: more SIMD processors added to match size of problem. Operate asynchronously and in MIMD fashion.
ASP: a parallel computing technology
NASA Astrophysics Data System (ADS)
Lea, R. M.
1990-09-01
ASP modules constitute the basis of a parallel computing technology platform for the rapid development of a broad range of numeric and symbolic information processing systems. Based on off-the-shelf general-purpose hardware and software modules ASP technology is intended to increase productivity in the development (and competitiveness in the marketing) of cost-effective low-MIMD/high-SIMD Massively Parallel Processor (MPPs). The paper discusses ASP module philosophy and demonstrates how ASP modules can satisfy the market algorithmic architectural and engineering requirements of such MPPs. In particular two specific ASP modules based on VLSI and WSI technologies are studied as case examples of ASP technology the latter reporting 1 TOPS/fl3 1 GOPS/W and 1 MOPS/$ as ball-park figures-of-merit of cost-effectiveness.
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.
Parallel processing for scientific computations
NASA Technical Reports Server (NTRS)
Alkhatib, Hasan S.
1991-01-01
The main contribution of the effort in the last two years is the introduction of the MOPPS system. After doing extensive literature search, we introduced the system which is described next. MOPPS employs a new solution to the problem of managing programs which solve scientific and engineering applications on a distributed processing environment. Autonomous computers cooperate efficiently in solving large scientific problems with this solution. MOPPS has the advantage of not assuming the presence of any particular network topology or configuration, computer architecture, or operating system. It imposes little overhead on network and processor resources while efficiently managing programs concurrently. The core of MOPPS is an intelligent program manager that builds a knowledge base of the execution performance of the parallel programs it is managing under various conditions. The manager applies this knowledge to improve the performance of future runs. The program manager learns from experience.
Parallel Computational Protein Design
Zhou, Yichao; Donald, Bruce R.; Zeng, Jianyang
2016-01-01
Computational structure-based protein design (CSPD) is an important problem in computational biology, which aims to design or improve a prescribed protein function based on a protein structure template. It provides a practical tool for real-world protein engineering applications. A popular CSPD method that guarantees to find the global minimum energy solution (GMEC) is to combine both dead-end elimination (DEE) and A* tree search algorithms. However, in this framework, the A* search algorithm can run in exponential time in the worst case, which may become the computation bottleneck of large-scale computational protein design process. To address this issue, we extend and add a new module to the OSPREY program that was previously developed in the Donald lab [1] to implement a GPU-based massively parallel A* algorithm for improving protein design pipeline. By exploiting the modern GPU computational framework and optimizing the computation of the heuristic function for A* search, our new program, called gOSPREY, can provide up to four orders of magnitude speedups in large protein design cases with a small memory overhead comparing to the traditional A* search algorithm implementation, while still guaranteeing the optimality. In addition, gOSPREY can be configured to run in a bounded-memory mode to tackle the problems in which the conformation space is too large and the global optimal solution cannot be computed previously. Furthermore, the GPU-based A* algorithm implemented in the gOSPREY program can be combined with the state-of-the-art rotamer pruning algorithms such as iMinDEE [2] and DEEPer [3] to also consider continuous backbone and side-chain flexibility. PMID:27914056
Northeast Parallel Architectures Center (NPAC)
1992-07-01
and image processing, advanced mathematics, graph theory, and artificial intelligence . Computer vision algorithms are normally divided into three...use top down processing which involves accessing databases, and performing artificial intelligence operations. A Computer Vision System (CVS) involves...recognition. Computational Techniques: Densi ty-quad tree algoritm Goal of the Research: To develop a character recognizer for arbitrary alphabets. A-30 TITLE
Template Matching on Parallel Architectures,
1985-07-01
memory. The processors run asynchronously. Thus according to Hynn’s categories the Butterfl . is a MIMD machine. The processors of the Butterfly are...Generalized Butterfly Architecture This section describes timings for pattern matching on the generalized Butterfl .. Ihe implementations on the Butterfly...these algorithms. Thus the best implementation of the techniques on the generalized Butterfl % are the same as the implementation on the real Butterfly
Parallel Computing Strategies for Irregular Algorithms
NASA Technical Reports Server (NTRS)
Biswas, Rupak; Oliker, Leonid; Shan, Hongzhang; Biegel, Bryan (Technical Monitor)
2002-01-01
Parallel computing promises several orders of magnitude increase in our ability to solve realistic computationally-intensive problems, but relies on their efficient mapping and execution on large-scale multiprocessor architectures. Unfortunately, many important applications are irregular and dynamic in nature, making their effective parallel implementation a daunting task. Moreover, with the proliferation of parallel architectures and programming paradigms, the typical scientist is faced with a plethora of questions that must be answered in order to obtain an acceptable parallel implementation of the solution algorithm. In this paper, we consider three representative irregular applications: unstructured remeshing, sparse matrix computations, and N-body problems, and parallelize them using various popular programming paradigms on a wide spectrum of computer platforms ranging from state-of-the-art supercomputers to PC clusters. We present the underlying problems, the solution algorithms, and the parallel implementation strategies. Smart load-balancing, partitioning, and ordering techniques are used to enhance parallel performance. Overall results demonstrate the complexity of efficiently parallelizing irregular algorithms.
A Parallel Rendering Algorithm for MIMD Architectures
NASA Technical Reports Server (NTRS)
Crockett, Thomas W.; Orloff, Tobias
1991-01-01
Applications such as animation and scientific visualization demand high performance rendering of complex three dimensional scenes. To deliver the necessary rendering rates, highly parallel hardware architectures are required. The challenge is then to design algorithms and software which effectively use the hardware parallelism. A rendering algorithm targeted to distributed memory MIMD architectures is described. For maximum performance, the algorithm exploits both object-level and pixel-level parallelism. The behavior of the algorithm is examined both analytically and experimentally. Its performance for large numbers of processors is found to be limited primarily by communication overheads. An experimental implementation for the Intel iPSC/860 shows increasing performance from 1 to 128 processors across a wide range of scene complexities. It is shown that minimal modifications to the algorithm will adapt it for use on shared memory architectures as well.
Optimal expression evaluation for data parallel architectures
NASA Technical Reports Server (NTRS)
Gilbert, John R.; Schreiber, Robert
1991-01-01
A data parallel machine represents an array or other composits data structure by allocating one processor per data item. A pointwise operation can be performed between two such arrays in unit time, provided their corresponding elements are allocated in the same processors. If the arrays are not aligned in this fashion, the cost of moving one or both of them is part of the cost of operation. The choice of where to perform the operation then affects this cost. If an expression with several operands is to be evaluated, there may be many choices of where to perform the intermediate operations. An efficient algorithm is given to find the minimum cost way to evaluate an expression, for several different data parallel architectures. The algorithm applies to any architecture in which the metric describing the cost of moving an array has a property called robustness. This encompasses most of the common data parallel communication architectures, including meshes of arbitrary dimension and hypercubes.
Optimal expression evaluation for data parallel architectures
NASA Technical Reports Server (NTRS)
Gilbert, J. R.; Schreiber, R.
1990-01-01
A data parallel machine represents an array or other composite data structure by allocating one processor per data item. A pointwise operation can be performed between two such arrays in unit time, provided their corresponding elements are allocated in the same processors. If the arrays are not aligned in this fashion, the cost of moving one or both of them is part of the cost of operation. The choice of where to perform the operation then affects this cost. If an expression with several operands is to be evaluated, there may be many choices of where to perform the intermediate operations. An efficient algorithm is given to find the minimum cost way to evaluate an expression, for several different data parallel architectures. The algorithm applies to any architecture in which the metric describing the cost of moving an array has a property called robustness. This encompasses most of the common data parallel communication architectures, including meshes of arbitrary dimension and hypercubes.
Some fast elliptic solvers on parallel architectures and their complexities
NASA Technical Reports Server (NTRS)
Gallopoulos, E.; Saad, Youcef
1989-01-01
The discretization of separable elliptic partial differential equations leads to linear systems with special block triangular matrices. Several methods are known to solve these systems, the most general of which is the Block Cyclic Reduction (BCR) algorithm which handles equations with nonconsistant coefficients. A method was recently proposed to parallelize and vectorize BCR. Here, the mapping of BCR on distributed memory architectures is discussed, and its complexity is compared with that of other approaches, including the Alternating-Direction method. A fast parallel solver is also described, based on an explicit formula for the solution, which has parallel computational complexity lower than that of parallel BCR.
Some fast elliptic solvers on parallel architectures and their complexities
NASA Technical Reports Server (NTRS)
Gallopoulos, E.; Saad, Y.
1989-01-01
The discretization of separable elliptic partial differential equations leads to linear systems with special block tridiagonal matrices. Several methods are known to solve these systems, the most general of which is the Block Cyclic Reduction (BCR) algorithm which handles equations with nonconstant coefficients. A method was recently proposed to parallelize and vectorize BCR. In this paper, the mapping of BCR on distributed memory architectures is discussed, and its complexity is compared with that of other approaches including the Alternating-Direction method. A fast parallel solver is also described, based on an explicit formula for the solution, which has parallel computational compelxity lower than that of parallel BCR.
The effects of parallel processing architectures on discrete event simulation
NASA Astrophysics Data System (ADS)
Cave, William; Slatt, Edward; Wassmer, Robert E.
2005-05-01
As systems become more complex, particularly those containing embedded decision algorithms, mathematical modeling presents a rigid framework that often impedes representation to a sufficient level of detail. Using discrete event simulation, one can build models that more closely represent physical reality, with actual algorithms incorporated in the simulations. Higher levels of detail increase simulation run time. Hardware designers have succeeded in producing parallel and distributed processor computers with theoretical speeds well into the teraflop range. However, the practical use of these machines on all but some very special problems is extremely limited. The inability to use this power is due to great difficulties encountered when trying to translate real world problems into software that makes effective use of highly parallel machines. This paper addresses the application of parallel processing to simulations of real world systems of varying inherent parallelism. It provides a brief background in modeling and simulation validity and describes a parameter that can be used in discrete event simulation to vary opportunities for parallel processing at the expense of absolute time synchronization and is constrained by validity. It focuses on the effects of model architecture, run-time software architecture, and parallel processor architecture on speed, while providing an environment where modelers can achieve sufficient model accuracy to produce valid simulation results. It describes an approach to simulation development that captures subject area expert knowledge to leverage inherent parallelism in systems in the following ways: * Data structures are separated from instructions to track which instruction sets share what data. This is used to determine independence and thus the potential for concurrent processing at run-time. * Model connectivity (independence) can be inspected visually to determine if the inherent parallelism of a physical system is properly
On the parallelization approaches for Intel MIC architecture
NASA Astrophysics Data System (ADS)
Atanassov, E.; Gurov, T.; Karaivanova, A.; Ivanovska, S.; Durchova, M.; Dimitrov, D.
2016-10-01
The Intel MIC architecture is one of the main processor architectures used for the production of computational accelerators. Increasing energy and cost-effciency of accelerators is one important option for building new HPC systems. However, the effective use of accelerators requires careful optimization on all stages of the algorithm and use of appropriate parallelization approaches. In the domain of statistical methods the quasi-Monte Carlo methods present distinct challenges when thousands of computational cores are to be involved in a computation. In this paper we describe in detail and study the performance of algorithms for generating some popular low-discrepancy sequences, aimed at devices with Intel MIC architecture. By leveraging the powerful vector instructions of the Intel MIC architecture to process many coordinates of the sequences in parallel, we obtain fast implementations that can be plugged-in in any parallel quasi-Monte Carlo computation. We present extensive numerical and timing results that demonstrate the benefit of our algorithms and their parallel effciency. The effects of using hyperthreading are also studied. The generation routines are provided under the GPL.
Modelling parallel programs and multiprocessor architectures with AXE
NASA Technical Reports Server (NTRS)
Yan, Jerry C.; Fineman, Charles E.
1991-01-01
AXE, An Experimental Environment for Parallel Systems, was designed to model and simulate for parallel systems at the process level. It provides an integrated environment for specifying computation models, multiprocessor architectures, data collection, and performance visualization. AXE is being used at NASA-Ames for developing resource management strategies, parallel problem formulation, multiprocessor architectures, and operating system issues related to the High Performance Computing and Communications Program. AXE's simple, structured user-interface enables the user to model parallel programs and machines precisely and efficiently. Its quick turn-around time keeps the user interested and productive. AXE models multicomputers. The user may easily modify various architectural parameters including the number of sites, connection topologies, and overhead for operating system activities. Parallel computations in AXE are represented as collections of autonomous computing objects known as players. Their use and behavior is described. Performance data of the multiprocessor model can be observed on a color screen. These include CPU and message routing bottlenecks, and the dynamic status of the software.
Electro-Optic Computing Architectures. Volume I
1998-02-01
The objective of the Electro - Optic Computing Architecture (EOCA) program was to develop multi-function electro - optic interfaces and optical...interconnect units to enhance the performance of parallel processor systems and form the building blocks for future electro - optic computing architectures...Specifically, three multi-function interface modules were targeted for development - an Electro - Optic Interface (EOI), an Optical Interconnection Unit (OW
Parallel Architectures for Planetary Exploration Requirements (PAPER)
NASA Technical Reports Server (NTRS)
Cezzar, Ruknet
1993-01-01
The project's main contributions have been in the area of student support. Throughout the project, at least one, in some cases two, undergraduate students have been supported. By working with the project, these students gained valuable knowledge involving the scientific research project, including the not-so-pleasant reporting requirements to the funding agencies. The other important contribution was towards the establishment of a graduate program in computer science at Hampton University. Primarily, the PAPER project has served as the main research basis in seeking funds from other agencies, such as the National Science Foundation, for establishing a research infrastructure in the department. In technical areas, especially in the first phase, we believe the trip to Jet Propulsion Laboratory, and gathering together all the pertinent information involving experimental computer architectures aimed for planetary explorations was very helpful. Indeed, if this effort is to be revived in the future due to congressional funding for planetary explorations, say an unmanned mission to Mars, our interim report will be an important starting point. In other technical areas, our simulator has pinpointed and highlighted several important performance issues related to the design of operating system kernels for MIMD machines. In particular, the critical issue of how the kernel itself will run in parallel on a multiple-processor system has been addressed through the various ready list organization and access policies. In the area of neural computing, our main contribution was an introductory tutorial package to familiarize the researchers at NASA with this new and promising field zone axes (20). Finally, we have introduced the notion of reversibility in programming systems which may find applications in various areas of space research.
Introduction to Parallel Computing
1992-05-01
Topology C, Ada, C++, Data-parallel FORTRAN, 2D mesh of node boards, each node FORTRAN-90 (late 1992) board has 1 application processor Devopment Tools ...parallel machines become the wave of the present, tools are increasingly needed to assist programmers in creating parallel tasks and coordinating...their activities. Linda was designed to be such a tool . Linda was designed with three important goals in mind: to be portable, efficient, and easy to use
Super and parallel computers and their impact on civil engineering
Kamat, M.P.
1986-01-01
This book presents the papers given at a conference on the use of supercomputers in civil engineering. Topics considered at the conference included solving nonlinear equations on a hypercube, a custom architectured parallel processing system, distributed data processing, algorithms, computer architecture, parallel processing, vector processing, computerized simulation, and cost benefit analysis.
Modular, Parallel Pulse-Shaping Filter Architectures
NASA Technical Reports Server (NTRS)
Gray, Andrew A.
2003-01-01
Novel architectures based on parallel subconvolution frequency-domain filtering methods have been developed for modular processing rate reduction of discrete-time pulse-shaping filters. Such pulse-shaping is desirable and often necessary to obtain bandwidth efficiency in very-high-rate wireless communications systems. In principle, this processing could be implemented in very-large-scale integrated (VLSI) circuits. Whereas other approaches to digital pulse-shaping are based primarily on time-domain processing concepts, the theory and design rules of the architectures presented here are founded on frequency-domain processing that has advantages in certain systems.
Interfacing Computer Aided Parallelization and Performance Analysis
NASA Technical Reports Server (NTRS)
Jost, Gabriele; Jin, Haoqiang; Labarta, Jesus; Gimenez, Judit; Biegel, Bryan A. (Technical Monitor)
2003-01-01
When porting sequential applications to parallel computer architectures, the program developer will typically go through several cycles of source code optimization and performance analysis. We have started a project to develop an environment where the user can jointly navigate through program structure and performance data information in order to make efficient optimization decisions. In a prototype implementation we have interfaced the CAPO computer aided parallelization tool with the Paraver performance analysis tool. We describe both tools and their interface and give an example for how the interface helps within the program development cycle of a benchmark code.
Cross-fertilization between connectionist networks and highly parallel architectures
NASA Technical Reports Server (NTRS)
Barnden, John; Srinivas, Kankanahalli
1989-01-01
The theoretical and practical connections between connectionist schemes such as neural-network computers and traditional symbolic processing architectures involving a high degree of parallelism are explored, reviewing the results of recent investigations. Topics addressed include data flow, data structure, and control flow; conventional pointers; associative addressing; hashing and reduced representations; the problem of binding values to variables; and levels of parallelism. It is concluded that connectionism is more closely related to traditional computer science and technology than is generally admitted; more cooperation between followers of the two approaches is recommended.
Opportunities in computational mechanics: Advances in parallel computing
Lesar, R.A.
1999-02-01
In this paper, the authors will discuss recent advances in computing power and the prospects for using these new capabilities for studying plasticity and failure. They will first review the new capabilities made available with parallel computing. They will discuss how these machines perform and how well their architecture might work on materials issues. Finally, they will give some estimates on the size of problems possible using these computers.
PISCES: An environment for parallel scientific computation
NASA Technical Reports Server (NTRS)
Pratt, T. W.
1985-01-01
The parallel implementation of scientific computing environment (PISCES) is a project to provide high-level programming environments for parallel MIMD computers. Pisces 1, the first of these environments, is a FORTRAN 77 based environment which runs under the UNIX operating system. The Pisces 1 user programs in Pisces FORTRAN, an extension of FORTRAN 77 for parallel processing. The major emphasis in the Pisces 1 design is in providing a carefully specified virtual machine that defines the run-time environment within which Pisces FORTRAN programs are executed. Each implementation then provides the same virtual machine, regardless of differences in the underlying architecture. The design is intended to be portable to a variety of architectures. Currently Pisces 1 is implemented on a network of Apollo workstations and on a DEC VAX uniprocessor via simulation of the task level parallelism. An implementation for the Flexible Computing Corp. FLEX/32 is under construction. An introduction to the Pisces 1 virtual computer and the FORTRAN 77 extensions is presented. An example of an algorithm for the iterative solution of a system of equations is given. The most notable features of the design are the provision for several granularities of parallelism in programs and the provision of a window mechanism for distributed access to large arrays of data.
Computer architecture evaluation for structural dynamics computations: Project summary
NASA Technical Reports Server (NTRS)
Standley, Hilda M.
1989-01-01
The intent of the proposed effort is the examination of the impact of the elements of parallel architectures on the performance realized in a parallel computation. To this end, three major projects are developed: a language for the expression of high level parallelism, a statistical technique for the synthesis of multicomputer interconnection networks based upon performance prediction, and a queueing model for the analysis of shared memory hierarchies.
NETRA: A parallel architecture for integrated vision systems. 1: Architecture and organization
NASA Technical Reports Server (NTRS)
Choudhary, Alok N.; Patel, Janak H.; Ahuja, Narendra
1989-01-01
Computer vision is regarded as one of the most complex and computationally intensive problems. An integrated vision system (IVS) is considered to be a system that uses vision algorithms from all levels of processing for a high level application (such as object recognition). A model of computation is presented for parallel processing for an IVS. Using the model, desired features and capabilities of a parallel architecture suitable for IVSs are derived. Then a multiprocessor architecture (called NETRA) is presented. This architecture is highly flexible without the use of complex interconnection schemes. The topology of NETRA is recursively defined and hence is easily scalable from small to large systems. Homogeneity of NETRA permits fault tolerance and graceful degradation under faults. It is a recursively defined tree-type hierarchical architecture where each of the leaf nodes consists of a cluster of processors connected with a programmable crossbar with selective broadcast capability to provide for desired flexibility. A qualitative evaluation of NETRA is presented. Then general schemes are described to map parallel algorithms onto NETRA. Algorithms are classified according to their communication requirements for parallel processing. An extensive analysis of inter-cluster communication strategies in NETRA is presented, and parameters affecting performance of parallel algorithms when mapped on NETRA are discussed. Finally, a methodology to evaluate performance of algorithms on NETRA is described.
Problem size, parallel architecture and optimal speedup
NASA Technical Reports Server (NTRS)
Nicol, David M.; Willard, Frank H.
1987-01-01
The communication and synchronization overhead inherent in parallel processing can lead to situations where adding processors to the solution method actually increases execution time. Problem type, problem size, and architecture type all affect the optimal number of processors to employ. The numerical solution of an elliptic partial differential equation is examined in order to study the relationship between problem size and architecture. The equation's domain is discretized into n sup 2 grid points which are divided into partitions and mapped onto the individual processor memories. The relationships between grid size, stencil type, partitioning strategy, processor execution time, and communication network type are analytically quantified. In so doing, the optimal number of processors was determined to assign to the solution, and identified (1) the smallest grid size which fully benefits from using all available processors, (2) the leverage on performance given by increasing processor speed or communication network speed, and (3) the suitability of various architectures for large numerical problems.
Optimal expression evaluation for data parallel architectures
NASA Technical Reports Server (NTRS)
Gilbert, John R.; Schreiber, Robert
1990-01-01
A data parallel machine represents an array or other composite data structure by allocating one processor (at least conceptually) per data item. A pointwise operation can be performed between two such arrays in unit time, provided their corresponding elements are allocated in the same processors. If the arrays are not aligned in this fashion, the cost of moving one or both of them is part of the cost of the operation. The choice of where to perform the operation then affects this cost. If an expression with several operands is to be evaluated, there may be many choices of where to perform the intermediate operations. An efficient algorithm is given to find the minimum-cost way to evaluate an expression, for several different data parallel architectures. This algorithm applies to any architecture in which the metric describing the cost of moving an array is robust. This encompasses most of the common data parallel communication architectures, including meshes of arbitrary dimension and hypercubes. Remarks are made on several variations of the problem, some of which are solved and some of which remain open.
Monte Carlo simulations on SIMD computer architectures
Burmester, C.P.; Gronsky, R.; Wille, L.T.
1992-03-01
Algorithmic considerations regarding the implementation of various materials science applications of the Monte Carlo technique to single instruction multiple data (SMM) computer architectures are presented. In particular, implementation of the Ising model with nearest, next nearest, and long range screened Coulomb interactions on the SIMD architecture MasPar MP-1 (DEC mpp-12000) series of massively parallel computers is demonstrated. Methods of code development which optimize processor array use and minimize inter-processor communication are presented including lattice partitioning and the use of processor array spanning tree structures for data reduction. Both geometric and algorithmic parallel approaches are utilized. Benchmarks in terms of Monte Carlo updates per second for the MasPar architecture are presented and compared to values reported in the literature from comparable studies on other architectures.
A novel parallel architecture for real-time image processing
NASA Astrophysics Data System (ADS)
Hu, Junhong; Zhang, Tianxu; Zhong, Sheng; Chen, Xujun
2009-10-01
A novel DSP/FPGA-based parallel architecture for real-time image processing is presented in this paper, DSPs are the main processing unit and FPGAs are used to be logic units for image interface protocol, image processing, image display, synchronization communication portocol of DSPs and DSP's reprogramming interface of 422/485. The presented architecture is composed of two modules: the preprocessing module and the processing module, and the latter is extendable for better performance. Modules are connected by LINK communication port, whose LVDS protocol has the ability of anti-jamming. And DSP's programs can be updated easily by 422/485 with PC's serial port. Analysis and experiments result shows that the prototype with the proposed parallel architecture has many promising charactersitics such as powerful computing capability, broad data transfer bandwidth, and is easy to be extended and updated.
Impact of Parallel Computing on Large Scale Aeroelastic Computations
NASA Technical Reports Server (NTRS)
Guruswamy, Guru P.; Kwak, Dochan (Technical Monitor)
2000-01-01
Aeroelasticity is computationally one of the most intensive fields in aerospace engineering. Though over the last three decades the computational speed of supercomputers have substantially increased, they are still inadequate for large scale aeroelastic computations using high fidelity flow and structural equations. In addition to reaching a saturation in computational speed because of changes in economics, computer manufactures are stopping the manufacturing of mainframe type supercomputers. This has led computational aeroelasticians to face the gigantic task of finding alternate approaches for fulfilling their needs. The alternate path to over come speed and availability limitations of mainframe type supercomputers is to use parallel computers. During this decade several different architectures have evolved. In FY92 the US Government started the High Performance Computing and Communication (HPCC) program. As a participant in this program NASA developed several parallel computational tools for aeroelastic applications. This talk describes the impact of those application tools on high fidelity based multidisciplinary analysis.
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.
Review of parallel computing methods and tools for FPGA technology
NASA Astrophysics Data System (ADS)
Cieszewski, Radosław; Linczuk, Maciej; Pozniak, Krzysztof; Romaniuk, Ryszard
2013-10-01
Parallel computing is emerging as an important area of research in computer architectures and software systems. Many algorithms can be greatly accelerated using parallel computing techniques. Specialized parallel computer architectures are used for accelerating speci c tasks. High-Energy Physics Experiments measuring systems often use FPGAs for ne-grained computation. FPGA combines many bene ts of both software and ASIC implementations. Like software, the mapped circuit is exible, and can be recon gured over the lifetime of the system. FPGAs therefore have the potential to achieve far greater performance than software as a result of bypassing the fetch-decode-execute operations of traditional processors, and possibly exploiting a greater level of parallelism. Creating parallel programs implemented in FPGAs is not trivial. This paper presents existing methods and tools for ne-grained computation implemented in FPGA using Behavioral Description and High Level Programming Languages.
Time dependent processing in a parallel pipeline architecture.
Biddiscombe, John; Geveci, Berk; Martin, Ken; Moreland, Kenneth; Thompson, David
2007-01-01
Pipeline architectures provide a versatile and efficient mechanism for constructing visualizations, and they have been implemented in numerous libraries and applications over the past two decades. In addition to allowing developers and users to freely combine algorithms, visualization pipelines have proven to work well when streaming data and scale well on parallel distributed-memory computers. However, current pipeline visualization frameworks have a critical flaw: they are unable to manage time varying data. As data flows through the pipeline, each algorithm has access to only a single snapshot in time of the data. This prevents the implementation of algorithms that do any temporal processing such as particle tracing; plotting over time; or interpolation, fitting, or smoothing of time series data. As data acquisition technology improves, as simulation time-integration techniques become more complex, and as simulations save less frequently and regularly, the ability to analyze the time-behavior of data becomes more important. This paper describes a modification to the traditional pipeline architecture that allows it to accommodate temporal algorithms. Furthermore, the architecture allows temporal algorithms to be used in conjunction with algorithms expecting a single time snapshot, thus simplifying software design and allowing adoption into existing pipeline frameworks. Our architecture also continues to work well in parallel distributed-memory environments. We demonstrate our architecture by modifying the popular VTK framework and exposing the functionality to the ParaView application. We use this framework to apply time-dependent algorithms on large data with a parallel cluster computer and thereby exercise a functionality that previously did not exist.
Computational electromagnetics and parallel dense matrix computations
Forsman, K.; Kettunen, L.; Gropp, W.; Levine, D.
1995-06-01
We present computational results using CORAL, a parallel, three-dimensional, nonlinear magnetostatic code based on a volume integral equation formulation. A key feature of CORAL is the ability to solve, in parallel, the large, dense systems of linear equations that are inherent in the use of integral equation methods. Using the Chameleon and PSLES libraries ensures portability and access to the latest linear algebra solution technology.
Computational electromagnetics and parallel dense matrix computations
Forsman, K.; Kettunen, L.; Gropp, W.
1995-12-01
We present computational results using CORAL, a parallel, three-dimensional, nonlinear magnetostatic code based on a volume integral equation formulation. A key feature of CORAL is the ability to solve, in parallel, the large, dense systems of linear equations that are inherent in the use of integral equation methods. Using the Chameleon and PSLES libraries ensures portability and access to the latest linear algebra solution technology.
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.
CFD Research, Parallel Computation and Aerodynamic Optimization
NASA Technical Reports Server (NTRS)
Ryan, James S.
1995-01-01
During the last five years, CFD has matured substantially. Pure CFD research remains to be done, but much of the focus has shifted to integration of CFD into the design process. The work under these cooperative agreements reflects this trend. The recent work, and work which is planned, is designed to enhance the competitiveness of the US aerospace industry. CFD and optimization approaches are being developed and tested, so that the industry can better choose which methods to adopt in their design processes. The range of computer architectures has been dramatically broadened, as the assumption that only huge vector supercomputers could be useful has faded. Today, researchers and industry can trade off time, cost, and availability, choosing vector supercomputers, scalable parallel architectures, networked workstations, or heterogenous combinations of these to complete required computations efficiently.
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.
Application of parallelized software architecture to an autonomous ground vehicle
NASA Astrophysics Data System (ADS)
Shakya, Rahul; Wright, Adam; Shin, Young Ho; Momin, Orko; Petkovsek, Steven; Wortman, Paul; Gautam, Prasanna; Norton, Adam
2011-01-01
This paper presents improvements made to Q, an autonomous ground vehicle designed to participate in the Intelligent Ground Vehicle Competition (IGVC). For the 2010 IGVC, Q was upgraded with a new parallelized software architecture and a new vision processor. Improvements were made to the power system reducing the number of batteries required for operation from six to one. In previous years, a single state machine was used to execute the bulk of processing activities including sensor interfacing, data processing, path planning, navigation algorithms and motor control. This inefficient approach led to poor software performance and made it difficult to maintain or modify. For IGVC 2010, the team implemented a modular parallel architecture using the National Instruments (NI) LabVIEW programming language. The new architecture divides all the necessary tasks - motor control, navigation, sensor data collection, etc. into well-organized components that execute in parallel, providing considerable flexibility and facilitating efficient use of processing power. Computer vision is used to detect white lines on the ground and determine their location relative to the robot. With the new vision processor and some optimization of the image processing algorithm used last year, two frames can be acquired and processed in 70ms. With all these improvements, Q placed 2nd in the autonomous challenge.
Computing architecture for autonomous microgrids
Goldsmith, Steven Y.
2015-09-29
A computing architecture that facilitates autonomously controlling operations of a microgrid is described herein. A microgrid network includes numerous computing devices that execute intelligent agents, each of which is assigned to a particular entity (load, source, storage device, or switch) in the microgrid. The intelligent agents can execute in accordance with predefined protocols to collectively perform computations that facilitate uninterrupted control of the .
Layered Architecture for Quantum Computing
NASA Astrophysics Data System (ADS)
Jones, N. Cody; Van Meter, Rodney; Fowler, Austin G.; McMahon, Peter L.; Kim, Jungsang; Ladd, Thaddeus D.; Yamamoto, Yoshihisa
2012-07-01
We develop a layered quantum-computer architecture, which is a systematic framework for tackling the individual challenges of developing a quantum computer while constructing a cohesive device design. We discuss many of the prominent techniques for implementing circuit-model quantum computing and introduce several new methods, with an emphasis on employing surface-code quantum error correction. In doing so, we propose a new quantum-computer architecture based on optical control of quantum dots. The time scales of physical-hardware operations and logical, error-corrected quantum gates differ by several orders of magnitude. By dividing functionality into layers, we can design and analyze subsystems independently, demonstrating the value of our layered architectural approach. Using this concrete hardware platform, we provide resource analysis for executing fault-tolerant quantum algorithms for integer factoring and quantum simulation, finding that the quantum-dot architecture we study could solve such problems on the time scale of days.
Advanced high-performance computer system architectures
NASA Astrophysics Data System (ADS)
Vinogradov, V. I.
2007-02-01
Convergence of computer systems and communication technologies are moving to switched high-performance modular system architectures on the basis of high-speed switched interconnections. Multi-core processors become more perspective way to high-performance system, and traditional parallel bus system architectures (VME/VXI, cPCI/PXI) are moving to new higher speed serial switched interconnections. Fundamentals in system architecture development are compact modular component strategy, low-power processor, new serial high-speed interface chips on the board, and high-speed switched fabric for SAN architectures. Overview of advanced modular concepts and new international standards for development high-performance embedded and compact modular systems for real-time applications are described.
Visualizing Parallel Computer System Performance
NASA Technical Reports Server (NTRS)
Malony, Allen D.; Reed, Daniel A.
1988-01-01
Parallel computer systems are among the most complex of man's creations, making satisfactory performance characterization difficult. Despite this complexity, there are strong, indeed, almost irresistible, incentives to quantify parallel system performance using a single metric. The fallacy lies in succumbing to such temptations. A complete performance characterization requires not only an analysis of the system's constituent levels, it also requires both static and dynamic characterizations. Static or average behavior analysis may mask transients that dramatically alter system performance. Although the human visual system is remarkedly adept at interpreting and identifying anomalies in false color data, the importance of dynamic, visual scientific data presentation has only recently been recognized Large, complex parallel system pose equally vexing performance interpretation problems. Data from hardware and software performance monitors must be presented in ways that emphasize important events while eluding irrelevant details. Design approaches and tools for performance visualization are the subject of this paper.
Kalman Filter Tracking on Parallel Architectures
NASA Astrophysics Data System (ADS)
Cerati, Giuseppe; Elmer, Peter; Lantz, Steven; McDermott, Kevin; Riley, Dan; Tadel, Matevž; Wittich, Peter; Würthwein, Frank; Yagil, Avi
2015-12-01
Power density constraints are limiting the performance improvements of modern CPUs. To address this we have seen the introduction of lower-power, multi-core processors, but the future will be even more exciting. In order to stay within the power density limits but still obtain Moore's Law performance/price gains, it will be necessary to parallelize algorithms to exploit larger numbers of lightweight cores and specialized functions like large vector units. Example technologies today include Intel's Xeon Phi and GPGPUs. Track finding and fitting is one of the most computationally challenging problems for event reconstruction in particle physics. At the High Luminosity LHC, for example, this will be by far the dominant problem. The need for greater parallelism has driven investigations of very different track finding techniques including Cellular Automata or returning to Hough Transform. The most common track finding techniques in use today are however those based on the Kalman Filter [2]. Significant experience has been accumulated with these techniques on real tracking detector systems, both in the trigger and offline. They are known to provide high physics performance, are robust and are exactly those being used today for the design of the tracking system for HL-LHC. Our previous investigations showed that, using optimized data structures, track fitting with Kalman Filter can achieve large speedup both with Intel Xeon and Xeon Phi. We report here our further progress towards an end-to-end track reconstruction algorithm fully exploiting vectorization and parallelization techniques in a realistic simulation setup.
High Performance Parallel Computational Nanotechnology
NASA Technical Reports Server (NTRS)
Saini, Subhash; Craw, James M. (Technical Monitor)
1995-01-01
At a recent press conference, NASA Administrator Dan Goldin encouraged NASA Ames Research Center to take a lead role in promoting research and development of advanced, high-performance computer technology, including nanotechnology. Manufacturers of leading-edge microprocessors currently perform large-scale simulations in the design and verification of semiconductor devices and microprocessors. Recently, the need for this intensive simulation and modeling analysis has greatly increased, due in part to the ever-increasing complexity of these devices, as well as the lessons of experiences such as the Pentium fiasco. Simulation, modeling, testing, and validation will be even more important for designing molecular computers because of the complex specification of millions of atoms, thousands of assembly steps, as well as the simulation and modeling needed to ensure reliable, robust and efficient fabrication of the molecular devices. The software for this capacity does not exist today, but it can be extrapolated from the software currently used in molecular modeling for other applications: semi-empirical methods, ab initio methods, self-consistent field methods, Hartree-Fock methods, molecular mechanics; and simulation methods for diamondoid structures. In as much as it seems clear that the application of such methods in nanotechnology will require powerful, highly powerful systems, this talk will discuss techniques and issues for performing these types of computations on parallel systems. We will describe system design issues (memory, I/O, mass storage, operating system requirements, special user interface issues, interconnects, bandwidths, and programming languages) involved in parallel methods for scalable classical, semiclassical, quantum, molecular mechanics, and continuum models; molecular nanotechnology computer-aided designs (NanoCAD) techniques; visualization using virtual reality techniques of structural models and assembly sequences; software required to
Parallel distributed computing using Python
NASA Astrophysics Data System (ADS)
Dalcin, Lisandro D.; Paz, Rodrigo R.; Kler, Pablo A.; Cosimo, Alejandro
2011-09-01
This work presents two software components aimed to relieve the costs of accessing high-performance parallel computing resources within a Python programming environment: MPI for Python and PETSc for Python. MPI for Python is a general-purpose Python package that provides bindings for the Message Passing Interface (MPI) standard using any back-end MPI implementation. Its facilities allow parallel Python programs to easily exploit multiple processors using the message passing paradigm. PETSc for Python provides access to the Portable, Extensible Toolkit for Scientific Computation (PETSc) libraries. Its facilities allow sequential and parallel Python applications to exploit state of the art algorithms and data structures readily available in PETSc for the solution of large-scale problems in science and engineering. MPI for Python and PETSc for Python are fully integrated to PETSc-FEM, an MPI and PETSc based parallel, multiphysics, finite elements code developed at CIMEC laboratory. This software infrastructure supports research activities related to simulation of fluid flows with applications ranging from the design of microfluidic devices for biochemical analysis to modeling of large-scale stream/aquifer interactions.
NASA Technical Reports Server (NTRS)
Fijany, Amir (Inventor); Bejczy, Antal K. (Inventor)
1994-01-01
In a computer having a large number of single-instruction multiple data (SIMD) processors, each of the SIMD processors has two sets of three individual processor elements controlled by a master control unit and interconnected among a plurality of register file units where data is stored. The register files input and output data in synchronism with a minor cycle clock under control of two slave control units controlling the register file units connected to respective ones of the two sets of processor elements. Depending upon which ones of the register file units are enabled to store or transmit data during a particular minor clock cycle, the processor elements within an SIMD processor are connected in rings or in pipeline arrays, and may exchange data with the internal bus or with neighboring SIMD processors through interface units controlled by respective ones of the two slave control units.
Parallel processing for scientific computations
NASA Technical Reports Server (NTRS)
Alkhatib, Hasan S.
1995-01-01
The scope of this project dealt with the investigation of the requirements to support distributed computing of scientific computations over a cluster of cooperative workstations. Various experiments on computations for the solution of simultaneous linear equations were performed in the early phase of the project to gain experience in the general nature and requirements of scientific applications. A specification of a distributed integrated computing environment, DICE, based on a distributed shared memory communication paradigm has been developed and evaluated. The distributed shared memory model facilitates porting existing parallel algorithms that have been designed for shared memory multiprocessor systems to the new environment. The potential of this new environment is to provide supercomputing capability through the utilization of the aggregate power of workstations cooperating in a cluster interconnected via a local area network. Workstations, generally, do not have the computing power to tackle complex scientific applications, making them primarily useful for visualization, data reduction, and filtering as far as complex scientific applications are concerned. There is a tremendous amount of computing power that is left unused in a network of workstations. Very often a workstation is simply sitting idle on a desk. A set of tools can be developed to take advantage of this potential computing power to create a platform suitable for large scientific computations. The integration of several workstations into a logical cluster of distributed, cooperative, computing stations presents an alternative to shared memory multiprocessor systems. In this project we designed and evaluated such a system.
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.
Programming parallel architectures - The BLAZE family of languages
NASA Technical Reports Server (NTRS)
Mehrotra, Piyush
1989-01-01
This paper gives an overview of the various approaches to programming multiprocessor architectures that are currently being explored. It is argued that two of these approaches, interactive programming environments and functional parallel languages, are particularly attractive, since they remove much of the burden of exploiting parallel architectures from the user. This paper also describes recent work in the design of parallel languages. Research on languages for both shared and nonshared memory multiprocessors is described.
Fluid dynamics parallel computer development at NASA Langley Research Center
NASA Technical Reports Server (NTRS)
Townsend, James C.; Zang, Thomas A.; Dwoyer, Douglas L.
1987-01-01
To accomplish more detailed simulations of highly complex flows, such as the transition to turbulence, fluid dynamics research requires computers much more powerful than any available today. Only parallel processing on multiple-processor computers offers hope for achieving the required effective speeds. Looking ahead to the use of these machines, the fluid dynamicist faces three issues: algorithm development for near-term parallel computers, architecture development for future computer power increases, and assessment of possible advantages of special purpose designs. Two projects at NASA Langley address these issues. Software development and algorithm exploration is being done on the FLEX/32 Parallel Processing Research Computer. New architecture features are being explored in the special purpose hardware design of the Navier-Stokes Computer. These projects are complementary and are producing promising results.
NASA Technical Reports Server (NTRS)
Metcalfe, A. G.; Bodenheimer, R. E.
1976-01-01
A parallel algorithm for counting the number of logic-l elements in a binary array or image developed during preliminary investigation of the Tse concept is described. The counting algorithm is implemented using a basic combinational structure. Modifications which improve the efficiency of the basic structure are also presented. A programmable Tse computer structure is proposed, along with a hardware control unit, Tse instruction set, and software program for execution of the counting algorithm. Finally, a comparison is made between the different structures in terms of their more important characteristics.
Design of a massively parallel computer using bit serial processing elements
NASA Technical Reports Server (NTRS)
Aburdene, Maurice F.; Khouri, Kamal S.; Piatt, Jason E.; Zheng, Jianqing
1995-01-01
A 1-bit serial processor designed for a parallel computer architecture is described. This processor is used to develop a massively parallel computational engine, with a single instruction-multiple data (SIMD) architecture. The computer is simulated and tested to verify its operation and to measure its performance for further development.
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.
Software Defined Radio with Parallelized Software Architecture
NASA Technical Reports Server (NTRS)
Heckler, Greg
2013-01-01
This software implements software-defined radio procession over multi-core, multi-CPU systems in a way that maximizes the use of CPU resources in the system. The software treats each processing step in either a communications or navigation modulator or demodulator system as an independent, threaded block. Each threaded block is defined with a programmable number of input or output buffers; these buffers are implemented using POSIX pipes. In addition, each threaded block is assigned a unique thread upon block installation. A modulator or demodulator system is built by assembly of the threaded blocks into a flow graph, which assembles the processing blocks to accomplish the desired signal processing. This software architecture allows the software to scale effortlessly between single CPU/single-core computers or multi-CPU/multi-core computers without recompilation. NASA spaceflight and ground communications systems currently rely exclusively on ASICs or FPGAs. This software allows low- and medium-bandwidth (100 bps to .50 Mbps) software defined radios to be designed and implemented solely in C/C++ software, while lowering development costs and facilitating reuse and extensibility.
Software Defined Radio with Parallelized Software Architecture
NASA Technical Reports Server (NTRS)
Heckler, Greg
2013-01-01
This software implements software-defined radio procession over multicore, multi-CPU systems in a way that maximizes the use of CPU resources in the system. The software treats each processing step in either a communications or navigation modulator or demodulator system as an independent, threaded block. Each threaded block is defined with a programmable number of input or output buffers; these buffers are implemented using POSIX pipes. In addition, each threaded block is assigned a unique thread upon block installation. A modulator or demodulator system is built by assembly of the threaded blocks into a flow graph, which assembles the processing blocks to accomplish the desired signal processing. This software architecture allows the software to scale effortlessly between single CPU/single-core computers or multi-CPU/multi-core computers without recompilation. NASA spaceflight and ground communications systems currently rely exclusively on ASICs or FPGAs. This software allows low- and medium-bandwidth (100 bps to approx.50 Mbps) software defined radios to be designed and implemented solely in C/C++ software, while lowering development costs and facilitating reuse and extensibility.
Savannah River Site computing architecture
Not Available
1991-03-29
A computing architecture is a framework for making decisions about the implementation of computer technology and the supporting infrastructure. Because of the size, diversity, and amount of resources dedicated to computing at the Savannah River Site (SRS), there must be an overall strategic plan that can be followed by the thousands of site personnel who make decisions daily that directly affect the SRS computing environment and impact the site's production and business systems. This plan must address the following requirements: There must be SRS-wide standards for procurement or development of computing systems (hardware and software). The site computing organizations must develop systems that end users find easy to use. Systems must be put in place to support the primary function of site information workers. The developers of computer systems must be given tools that automate and speed up the development of information systems and applications based on computer technology. This document describes a proposal for a site-wide computing architecture that addresses the above requirements. In summary, this architecture is standards-based data-driven, and workstation-oriented with larger systems being utilized for the delivery of needed information to users in a client-server relationship.
Savannah River Site computing architecture
Not Available
1991-03-29
A computing architecture is a framework for making decisions about the implementation of computer technology and the supporting infrastructure. Because of the size, diversity, and amount of resources dedicated to computing at the Savannah River Site (SRS), there must be an overall strategic plan that can be followed by the thousands of site personnel who make decisions daily that directly affect the SRS computing environment and impact the site`s production and business systems. This plan must address the following requirements: There must be SRS-wide standards for procurement or development of computing systems (hardware and software). The site computing organizations must develop systems that end users find easy to use. Systems must be put in place to support the primary function of site information workers. The developers of computer systems must be given tools that automate and speed up the development of information systems and applications based on computer technology. This document describes a proposal for a site-wide computing architecture that addresses the above requirements. In summary, this architecture is standards-based data-driven, and workstation-oriented with larger systems being utilized for the delivery of needed information to users in a client-server relationship.
A distributed parallel storage architecture and its potential application within EOSDIS
NASA Technical Reports Server (NTRS)
Johnston, William E.; Tierney, Brian; Feuquay, Jay; Butzer, Tony
1994-01-01
We describe the architecture, implementation, use of a scalable, high performance, distributed-parallel data storage system developed in the ARPA funded MAGIC gigabit testbed. A collection of wide area distributed disk servers operate in parallel to provide logical block level access to large data sets. Operated primarily as a network-based cache, the architecture supports cooperation among independently owned resources to provide fast, large-scale, on-demand storage to support data handling, simulation, and computation.
A distributed parallel storage architecture and its potential application within EOSDIS
Johnston, W.E.; Tierney, B.; Feuquay, J.; Butzer, T.
1995-01-01
We describe the architecture, implementation, use, and potential use of a scale, high-performance, distributed-parallel data storage system developed in the ARPA funded MAGIC gigabit testbed. A collection of wide area distributed disk servers operate in parallel to provide logical block level access to large data sets. Operated primarily as a network-based cache, the architecture supports cooperation among independently owned resources to provide fast, large-scale, on-demand storage to support data handling, simulation, and computation.
Efficient tree codes on SIMD computer architectures
NASA Astrophysics Data System (ADS)
Olson, Kevin M.
1996-11-01
This paper describes changes made to a previous implementation of an N -body tree code developed for a fine-grained, SIMD computer architecture. These changes include (1) switching from a balanced binary tree to a balanced oct tree, (2) addition of quadrupole corrections, and (3) having the particles search the tree in groups rather than individually. An algorithm for limiting errors is also discussed. In aggregate, these changes have led to a performance increase of over a factor of 10 compared to the previous code. For problems several times larger than the processor array, the code now achieves performance levels of ~ 1 Gflop on the Maspar MP-2 or roughly 20% of the quoted peak performance of this machine. This percentage is competitive with other parallel implementations of tree codes on MIMD architectures. This is significant, considering the low relative cost of SIMD architectures.
Parallel Computing for Brain Simulation.
Pastur-Romay, L A; Porto-Pazos, A B; Cedrón, F; Pazos, A
2016-11-04
The human brain is the most complex system in the known universe, but it is the most unknown system. It allows the human beings to possess extraordinary capacities. However, we don´t understand yet how and why most of these capacities are produced. For decades, it have been tried that the computers reproduces these capacities. On one hand, to help understanding the nervous system. On the other hand, to process the data in a more efficient way than before. It is intended to make the computers process the information like the brain does it. The important technological developments and the big multidisciplinary projects have allowed create the first simulation with a number of neurons similar to the human brain neurons number. This paper presents an update review about the main research projects that are trying of simulate and/or emulate the human brain. They employ different types of computational models using parallel computing: digital models, analog models and hybrid models. This review includes the actual applications of these works and also the future trends. We have reviewed some works that look for a step forward in Neuroscience and other ones that look for a breakthrough in Computer Science (neuromorphic hardware, machine learning techniques). We summarize the most outstanding characteristics of them and present the latest advances and future plans. In addition, this review remarks the importance of considering not only neurons: the computational models of the brain should include glial cells, given the proven importance of the astrocytes in the information processing.
Trajectory optimization using parallel shooting method on parallel computer
Wirthman, D.J.; Park, S.Y.; Vadali, S.R.
1995-03-01
The efficiency of a parallel shooting method on a parallel computer for solving a variety of optimal control guidance problems is studied. Several examples are considered to demonstrate that a speedup of nearly 7 to 1 is achieved with the use of 16 processors. It is suggested that further improvements in performance can be achieved by parallelizing in the state domain. 10 refs.
Parallelized reliability estimation of reconfigurable computer networks
NASA Technical Reports Server (NTRS)
Nicol, David M.; Das, Subhendu; Palumbo, Dan
1990-01-01
A parallelized system, ASSURE, for computing the reliability of embedded avionics flight control systems which are able to reconfigure themselves in the event of failure is described. ASSURE accepts a grammar that describes a reliability semi-Markov state-space. From this it creates a parallel program that simultaneously generates and analyzes the state-space, placing upper and lower bounds on the probability of system failure. ASSURE is implemented on a 32-node Intel iPSC/860, and has achieved high processor efficiencies on real problems. Through a combination of improved algorithms, exploitation of parallelism, and use of an advanced microprocessor architecture, ASSURE has reduced the execution time on substantial problems by a factor of one thousand over previous workstation implementations. Furthermore, ASSURE's parallel execution rate on the iPSC/860 is an order of magnitude faster than its serial execution rate on a Cray-2 supercomputer. While dynamic load balancing is necessary for ASSURE's good performance, it is needed only infrequently; the particular method of load balancing used does not substantially affect performance.
Kagawa, K; Nitta, K; Ogura, Y; Tanida, J; Ichioka, Y
2001-01-10
We propose an optoelectronic parallel-matching architecture (PMA) that provides powerful processing capabilities in global processing compared with conventional parallel-computing architectures. The PMA is composed of a global processor called a parallel-matching (PM) module and multiple processing elements (PE's). The PM module is implemented by a large-fan-out free-space optical interconnection and a PM smart-pixel array (PM-SPA). In the proposed architecture, by means of the PM module each PE can monitor the other PE's by use of several kinds of global data matching as well as interprocessor communication. Theoretical evaluation of the performance shows that the proposed PMA provides tremendous improvement in global processing. A prototype demonstrator of the PM module is constructed on the basis of state-of-the-art optoelectronic devices and a diffractive optical element. The prototype is assumed for use in a multiple-processor system composed of 4 x 4 PE's that are completely connected through bit-serial optical communication channels. The PM-SPA is emulated by a complex programmable device and a complementary metal-oxide semiconductor photodetector array. On the prototype demonstrator the fundamental operations of the PM module were verified at 15 MHz.
Parallel Pascal - An extended Pascal for parallel computers
NASA Technical Reports Server (NTRS)
Reeves, A. P.
1984-01-01
Parallel Pascal is an extended version of the conventional serial Pascal programming language which includes a convenient syntax for specifying array operations. It is upward compatible with standard Pascal and involves only a small number of carefully chosen new features. Parallel Pascal was developed to reduce the semantic gap between standard Pascal and a large range of highly parallel computers. Two important design goals of Parallel Pascal were efficiency and portability. Portability is particularly difficult to achieve since different parallel computers frequently have very different capabilities.
Parallel computing in enterprise modeling.
Goldsby, Michael E.; Armstrong, Robert C.; Shneider, Max S.; Vanderveen, Keith; Ray, Jaideep; Heath, Zach; Allan, Benjamin A.
2008-08-01
This report presents the results of our efforts to apply high-performance computing to entity-based simulations with a multi-use plugin for parallel computing. We use the term 'Entity-based simulation' to describe a class of simulation which includes both discrete event simulation and agent based simulation. What simulations of this class share, and what differs from more traditional models, is that the result sought is emergent from a large number of contributing entities. Logistic, economic and social simulations are members of this class where things or people are organized or self-organize to produce a solution. Entity-based problems never have an a priori ergodic principle that will greatly simplify calculations. Because the results of entity-based simulations can only be realized at scale, scalable computing is de rigueur for large problems. Having said that, the absence of a spatial organizing principal makes the decomposition of the problem onto processors problematic. In addition, practitioners in this domain commonly use the Java programming language which presents its own problems in a high-performance setting. The plugin we have developed, called the Parallel Particle Data Model, overcomes both of these obstacles and is now being used by two Sandia frameworks: the Decision Analysis Center, and the Seldon social simulation facility. While the ability to engage U.S.-sized problems is now available to the Decision Analysis Center, this plugin is central to the success of Seldon. Because Seldon relies on computationally intensive cognitive sub-models, this work is necessary to achieve the scale necessary for realistic results. With the recent upheavals in the financial markets, and the inscrutability of terrorist activity, this simulation domain will likely need a capability with ever greater fidelity. High-performance computing will play an important part in enabling that greater fidelity.
Parallel Proximity Detection for Computer Simulations
NASA Technical Reports Server (NTRS)
Steinman, Jeffrey S. (Inventor); Wieland, Frederick P. (Inventor)
1998-01-01
The present invention discloses a system for performing proximity detection in computer simulations on parallel processing architectures utilizing a distribution list which includes movers and sensor coverages which check in and out of grids. Each mover maintains a list of sensors that detect the mover's motion as the mover and sensor coverages check in and out of the grids. Fuzzy grids are included by fuzzy resolution parameters to allow movers and sensor coverages to check in and out of grids without computing exact grid crossings. The movers check in and out of grids while moving sensors periodically inform the grids of their coverage. In addition, a lookahead function is also included for providing a generalized capability without making any limiting assumptions about the particular application to which it is applied. The lookahead function is initiated so that risk-free synchronization strategies never roll back grid events. The lookahead function adds fixed delays as events are scheduled for objects on other nodes.
Parallel Proximity Detection for Computer Simulation
NASA Technical Reports Server (NTRS)
Steinman, Jeffrey S. (Inventor); Wieland, Frederick P. (Inventor)
1997-01-01
The present invention discloses a system for performing proximity detection in computer simulations on parallel processing architectures utilizing a distribution list which includes movers and sensor coverages which check in and out of grids. Each mover maintains a list of sensors that detect the mover's motion as the mover and sensor coverages check in and out of the grids. Fuzzy grids are includes by fuzzy resolution parameters to allow movers and sensor coverages to check in and out of grids without computing exact grid crossings. The movers check in and out of grids while moving sensors periodically inform the grids of their coverage. In addition, a lookahead function is also included for providing a generalized capability without making any limiting assumptions about the particular application to which it is applied. The lookahead function is initiated so that risk-free synchronization strategies never roll back grid events. The lookahead function adds fixed delays as events are scheduled for objects on other nodes.
Specialized computer architectures for computational aerodynamics
NASA Technical Reports Server (NTRS)
Stevenson, D. K.
1978-01-01
In recent years, computational fluid dynamics has made significant progress in modelling aerodynamic phenomena. Currently, one of the major barriers to future development lies in the compute-intensive nature of the numerical formulations and the relative high cost of performing these computations on commercially available general purpose computers, a cost high with respect to dollar expenditure and/or elapsed time. Today's computing technology will support a program designed to create specialized computing facilities to be dedicated to the important problems of computational aerodynamics. One of the still unresolved questions is the organization of the computing components in such a facility. The characteristics of fluid dynamic problems which will have significant impact on the choice of computer architecture for a specialized facility are reviewed.
Parallel Environment for Quantum Computing
NASA Astrophysics Data System (ADS)
Tabakin, Frank; Diaz, Bruno Julia
2009-03-01
To facilitate numerical study of noise and decoherence in QC algorithms,and of the efficacy of error correction schemes, we have developed a Fortran 90 quantum computer simulator with parallel processing capabilities. It permits rapid evaluation of quantum algorithms for a large number of qubits and for various ``noise'' scenarios. State vectors are distributed over many processors, to employ a large number of qubits. Parallel processing is implemented by the Message-Passing Interface protocol. A description of how to spread the wave function components over many processors, along with how to efficiently describe the action of general one- and two-qubit operators on these state vectors will be delineated.Grover's search and Shor's factoring algorithms with noise will be discussed as examples. A major feature of this work is that concurrent versions of the algorithms can be evaluated with each version subject to diverse noise effects, corresponding to solving a stochastic Schrodinger equation. The density matrix for the ensemble of such noise cases is constructed using parallel distribution methods to evaluate its associated entropy. Applications of this powerful tool is made to delineate the stability and correction of QC processes using Hamiltonian based dynamics.
Programming parallel architectures: The BLAZE family of languages
NASA Technical Reports Server (NTRS)
Mehrotra, Piyush
1988-01-01
Programming multiprocessor architectures is a critical research issue. An overview is given of the various approaches to programming these architectures that are currently being explored. It is argued that two of these approaches, interactive programming environments and functional parallel languages, are particularly attractive since they remove much of the burden of exploiting parallel architectures from the user. Also described is recent work by the author in the design of parallel languages. Research on languages for both shared and nonshared memory multiprocessors is described, as well as the relations of this work to other current language research projects.
Wireless Computing Architecture
2009-07-01
mechanisms are relevant to a broad spectrum of applications , but are particularly important to data broadcast in wireless distributed computing...significantly improve applications where reliable data broadcast is required. For example, unmanned aerial vehicles (UAVs) may use Rainbow to distribute ...68-74. 8. Dean, J., Ghemawat, S., “ MapReduce : simplified data processing on large clusters ”, Communications of the ACM, 51, 1, 2008, pp. 107-113
Wireless Computing Architecture II
2010-11-01
responsible for running computation tasks as well as storing HDFS data blocks. This arrangement is consistent with that of Amazon Elastic MapReduce clusters ...unpredictable application demands and large data sets. For example, application demands may change in response to sudden weather shifts or ―surprise...comparing TCP throughput distributions for model-generated traces against those for actual traces randomly sampled from field data . Our modeling
Computing architecture for telerobots in earth orbit
NASA Technical Reports Server (NTRS)
Bejczy, A. K.; Dotson, R. S.; Szakaly, Z.
1987-01-01
Based on generic operational and computational requirements associated with the control of telerobots in earth orbit, a multibus-based distributed but integrated computing architecture is proposed. An experimental system of that kind under development at the Jet Propulsion Laboratory (JPL) is briefly described. It uses Intel Multibus I at both control station and remote robot (telerobot) computing nodes. An essential element within each multibus is a Unified (or Universal) Computer Control Subsystem (UCCS) for telerobot and control station motor components. The two multibus-based computing nodes can be linked by parallel or high speed serial links for real-time data transmission and for closing the real-time bilateral (force-reflecting) control loop between telerobot and control station. The experimental system is briefly commented, followed by a brief discussion of future development plans and possibilities.
VLSI Architectures for Computing DFT's
NASA Technical Reports Server (NTRS)
Truong, T. K.; Chang, J. J.; Hsu, I. S.; Reed, I. S.; Pei, D. Y.
1986-01-01
Simplifications result from use of residue Fermat number systems. System of finite arithmetic over residue Fermat number systems enables calculation of discrete Fourier transform (DFT) of series of complex numbers with reduced number of multiplications. Computer architectures based on approach suitable for design of very-large-scale integrated (VLSI) circuits for computing DFT's. General approach not limited to DFT's; Applicable to decoding of error-correcting codes and other transform calculations. System readily implemented in VLSI.
Parallel computing techniques for rotorcraft aerodynamics
NASA Astrophysics Data System (ADS)
Ekici, Kivanc
The modification of unsteady three-dimensional Navier-Stokes codes for application on massively parallel and distributed computing environments is investigated. The Euler/Navier-Stokes code TURNS (Transonic Unsteady Rotor Navier-Stokes) was chosen as a test bed because of its wide use by universities and industry. For the efficient implementation of TURNS on parallel computing systems, two algorithmic changes are developed. First, main modifications to the implicit operator, Lower-Upper Symmetric Gauss Seidel (LU-SGS) originally used in TURNS, is performed. Second, application of an inexact Newton method, coupled with a Krylov subspace iterative method (Newton-Krylov method) is carried out. Both techniques have been tried previously for the Euler equations mode of the code. In this work, we have extended the methods to the Navier-Stokes mode. Several new implicit operators were tried because of convergence problems of traditional operators with the high cell aspect ratio (CAR) grids needed for viscous calculations on structured grids. Promising results for both Euler and Navier-Stokes cases are presented for these operators. For the efficient implementation of Newton-Krylov methods to the Navier-Stokes mode of TURNS, efficient preconditioners must be used. The parallel implicit operators used in the previous step are employed as preconditioners and the results are compared. The Message Passing Interface (MPI) protocol has been used because of its portability to various parallel architectures. It should be noted that the proposed methodology is general and can be applied to several other CFD codes (e.g. OVERFLOW).
Parallel Computing Using Web Servers and "Servlets".
ERIC Educational Resources Information Center
Lo, Alfred; Bloor, Chris; Choi, Y. K.
2000-01-01
Describes parallel computing and presents inexpensive ways to implement a virtual parallel computer with multiple Web servers. Highlights include performance measurement of parallel systems; models for using Java and intranet technology including single server, multiple clients and multiple servers, single client; and a comparison of CGI (common…
Broadcasting a message in a parallel computer
Berg, Jeremy E.; Faraj, Ahmad A.
2011-08-02
Methods, systems, and products are disclosed for broadcasting a message in a parallel computer. The parallel computer includes a plurality of compute nodes connected together using a data communications network. The data communications network optimized for point to point data communications and is characterized by at least two dimensions. The compute nodes are organized into at least one operational group of compute nodes for collective parallel operations of the parallel computer. One compute node of the operational group assigned to be a logical root. Broadcasting a message in a parallel computer includes: establishing a Hamiltonian path along all of the compute nodes in at least one plane of the data communications network and in the operational group; and broadcasting, by the logical root to the remaining compute nodes, the logical root's message along the established Hamiltonian path.
SIAM Conference on Parallel Processing for Scientific Computing - March 12-14, 2008
Kolata, William G.
2008-09-08
The themes of the 2008 conference included, but were not limited to: Programming languages, models, and compilation techniques; The transition to ubiquitous multicore/manycore processors; Scientific computing on special-purpose processors (Cell, GPUs, etc.); Architecture-aware algorithms; From scalable algorithms to scalable software; Tools for software development and performance evaluation; Global perspectives on HPC; Parallel computing in industry; Distributed/grid computing; Fault tolerance; Parallel visualization and large scale data management; and The future of parallel architectures.
CFD research, parallel computation and aerodynamic optimization
NASA Technical Reports Server (NTRS)
Ryan, James S.
1995-01-01
Over five years of research in Computational Fluid Dynamics and its applications are covered in this report. Using CFD as an established tool, aerodynamic optimization on parallel architectures is explored. The objective of this work is to provide better tools to vehicle designers. Submarine design requires accurate force and moment calculations in flow with thick boundary layers and large separated vortices. Low noise production is critical, so flow into the propulsor region must be predicted accurately. The High Speed Civil Transport (HSCT) has been the subject of recent work. This vehicle is to be a passenger vehicle with the capability of cutting overseas flight times by more than half. A successful design must surpass the performance of comparable planes. Fuel economy, other operational costs, environmental impact, and range must all be improved substantially. For all these reasons, improved design tools are required, and these tools must eventually integrate optimization, external aerodynamics, propulsion, structures, heat transfer and other disciplines.
The International Conference on Vector and Parallel Computing (2nd)
1989-01-17
in Reservoir Simulation "... . ................... 7 "ParaScope: A Parallel Programing Environment ........................ 8 "Current Directions and...built. "Large-Scale Computing in Reservoir Simulation " In addition, a new tri-level parallel architecture pro- Pchard Ewing, University of Wyomitg...viding a large array of simple processors for image pro- The objective of reservoir simulation is to understand cessing, a medium-sized array of more
NASA Technical Reports Server (NTRS)
Mavriplis, D. J.; Das, Raja; Saltz, Joel; Vermeland, R. E.
1992-01-01
An efficient three dimensional unstructured Euler solver is parallelized on a Cray Y-MP C90 shared memory computer and on an Intel Touchstone Delta distributed memory computer. This paper relates the experiences gained and describes the software tools and hardware used in this study. Performance comparisons between two differing architectures are made.
Implementing clips on a parallel computer
NASA Technical Reports Server (NTRS)
Riley, Gary
1987-01-01
The C language integrated production system (CLIPS) is a forward chaining rule based language to provide training and delivery for expert systems. Conceptually, rule based languages have great potential for benefiting from the inherent parallelism of the algorithms that they employ. During each cycle of execution, a knowledge base of information is compared against a set of rules to determine if any rules are applicable. Parallelism also can be employed for use with multiple cooperating expert systems. To investigate the potential benefits of using a parallel computer to speed up the comparison of facts to rules in expert systems, a parallel version of CLIPS was developed for the FLEX/32, a large grain parallel computer. The FLEX implementation takes a macroscopic approach in achieving parallelism by splitting whole sets of rules among several processors rather than by splitting the components of an individual rule among processors. The parallel CLIPS prototype demonstrates the potential advantages of integrating expert system tools with parallel computers.
A parallel Jacobson-Oksman optimization algorithm. [parallel processing (computers)
NASA Technical Reports Server (NTRS)
Straeter, T. A.; Markos, A. T.
1975-01-01
A gradient-dependent optimization technique which exploits the vector-streaming or parallel-computing capabilities of some modern computers is presented. The algorithm, derived by assuming that the function to be minimized is homogeneous, is a modification of the Jacobson-Oksman serial minimization method. In addition to describing the algorithm, conditions insuring the convergence of the iterates of the algorithm and the results of numerical experiments on a group of sample test functions are presented. The results of these experiments indicate that this algorithm will solve optimization problems in less computing time than conventional serial methods on machines having vector-streaming or parallel-computing capabilities.
Northeast Parallel Architectures Center (NPAC) at Syracuse University
1990-12-01
Computer Architecture Architecture: Alliant Principle Investigator: Sergio R R Chavez , Syracuse University This project is to convert the wait and signal...consist of a simpler 2D problem to test and define the computational model. The frame buffer of -the connection machine will display a Julia set
Evaluation of fault-tolerant parallel-processor architectures over long space missions
NASA Technical Reports Server (NTRS)
Johnson, Sally C.
1989-01-01
The impact of a five year space mission environment on fault-tolerant parallel processor architectures is examined. The target application is a Strategic Defense Initiative (SDI) satellite requiring 256 parallel processors to provide the computation throughput. The reliability requirements are that the system still be operational after five years with .99 probability and that the probability of system failure during one-half hour of full operation be less than 10(-7). The fault tolerance features an architecture must possess to meet these reliability requirements are presented, many potential architectures are briefly evaluated, and one candidate architecture, the Charles Stark Draper Laboratory's Fault-Tolerant Parallel Processor (FTPP) is evaluated in detail. A methodology for designing a preliminary system configuration to meet the reliability and performance requirements of the mission is then presented and demonstrated by designing an FTPP configuration.
Partitioning problems in parallel, pipelined and distributed computing
NASA Technical Reports Server (NTRS)
Bokhari, S.
1985-01-01
The problem of optimally assigning the modules of a parallel program over the processors of a multiple computer system is addressed. A Sum-Bottleneck path algorithm is developed that permits the efficient solution of many variants of this problem under some constraints on the structure of the partitions. In particular, the following problems are solved optimally for a single-host, multiple satellite system: partitioning multiple chain structured parallel programs, multiple arbitrarily structured serial programs and single tree structured parallel programs. In addition, the problems of partitioning chain structured parallel programs across chain connected systems and across shared memory (or shared bus) systems are also solved under certain constraints. All solutions for parallel programs are equally applicable to pipelined programs. These results extend prior research in this area by explicitly taking concurrency into account and permit the efficient utilization of multiple computer architectures for a wide range of problems of practical interest.
Partitioning problems in parallel, pipelined, and distributed computing
NASA Technical Reports Server (NTRS)
Bokhari, Shahid H.
1988-01-01
The problem of optimally assigning the modules of a parallel program over the processors of a multiple-computer system is addressed. A sum-bottleneck path algorithm is developed that permits the efficient solution of many variants of this problem under some constraints on the structure of the partitions. In particular, the following problems are solved optimally for a single-host, multiple-satellite system: partitioning multiple chain-structured parallel programs, multiple arbitrarily structured serial programs, and single-tree structured parallel programs. In addition, the problem of partitioning chain-structured parallel programs across chain-connected systems is solved under certain constraints. All solutions for parallel programs are equally applicable to pipelined programs. These results extend prior research in this area by explicitly taking concurrency into account and permit the efficient utilization of multiple-computer architectures for a wide range of problems of practical interest.
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.
Parallel machine architecture for production rule systems
Allen, Jr., John D.; Butler, Philip L.
1989-01-01
A parallel processing system for production rule programs utilizes a host processor for storing production rule right hand sides (RHS) and a plurality of rule processors for storing left hand sides (LHS). The rule processors operate in parallel in the recognize phase of the system recognize -Act Cycle to match their respective LHS's against a stored list of working memory elements (WME) in order to find a self consistent set of WME's. The list of WME is dynamically varied during the Act phase of the system in which the host executes or fires rule RHS's for those rules for which a self-consistent set has been found by the rule processors. The host transmits instructions for creating or deleting working memory elements as dictated by the rule firings until the rule processors are unable to find any further self-consistent working memory element sets at which time the production rule system is halted.
Research in Parallel Algorithms and Software for Computational Aerosciences
NASA Technical Reports Server (NTRS)
Domel, Neal D.
1996-01-01
Phase I is complete for the development of a Computational Fluid Dynamics parallel code with automatic grid generation and adaptation for the Euler analysis of flow over complex geometries. SPLITFLOW, an unstructured Cartesian grid code developed at Lockheed Martin Tactical Aircraft Systems, has been modified for a distributed memory/massively parallel computing environment. The parallel code is operational on an SGI network, Cray J90 and C90 vector machines, SGI Power Challenge, and Cray T3D and IBM SP2 massively parallel machines. Parallel Virtual Machine (PVM) is the message passing protocol for portability to various architectures. A domain decomposition technique was developed which enforces dynamic load balancing to improve solution speed and memory requirements. A host/node algorithm distributes the tasks. The solver parallelizes very well, and scales with the number of processors. Partially parallelized and non-parallelized tasks consume most of the wall clock time in a very fine grain environment. Timing comparisons on a Cray C90 demonstrate that Parallel SPLITFLOW runs 2.4 times faster on 8 processors than its non-parallel counterpart autotasked over 8 processors.
Research in Parallel Algorithms and Software for Computational Aerosciences
NASA Technical Reports Server (NTRS)
Domel, Neal D.
1996-01-01
Phase 1 is complete for the development of a computational fluid dynamics CFD) parallel code with automatic grid generation and adaptation for the Euler analysis of flow over complex geometries. SPLITFLOW, an unstructured Cartesian grid code developed at Lockheed Martin Tactical Aircraft Systems, has been modified for a distributed memory/massively parallel computing environment. The parallel code is operational on an SGI network, Cray J90 and C90 vector machines, SGI Power Challenge, and Cray T3D and IBM SP2 massively parallel machines. Parallel Virtual Machine (PVM) is the message passing protocol for portability to various architectures. A domain decomposition technique was developed which enforces dynamic load balancing to improve solution speed and memory requirements. A host/node algorithm distributes the tasks. The solver parallelizes very well, and scales with the number of processors. Partially parallelized and non-parallelized tasks consume most of the wall clock time in a very fine grain environment. Timing comparisons on a Cray C90 demonstrate that Parallel SPLITFLOW runs 2.4 times faster on 8 processors than its non-parallel counterpart autotasked over 8 processors.
Parallel computations and control of adaptive structures
NASA Technical Reports Server (NTRS)
Park, K. C.; Alvin, Kenneth F.; Belvin, W. Keith; Chong, K. P. (Editor); Liu, S. C. (Editor); Li, J. C. (Editor)
1991-01-01
The equations of motion for structures with adaptive elements for vibration control are presented for parallel computations to be used as a software package for real-time control of flexible space structures. A brief introduction of the state-of-the-art parallel computational capability is also presented. Time marching strategies are developed for an effective use of massive parallel mapping, partitioning, and the necessary arithmetic operations. An example is offered for the simulation of control-structure interaction on a parallel computer and the impact of the approach presented for applications in other disciplines than aerospace industry is assessed.
Malleable architecture generator for FPGA computing
NASA Astrophysics Data System (ADS)
Gokhale, Maya; Kaba, James; Marks, Aaron; Kim, Jang
1996-10-01
The malleable architecture generator (MARGE) is a tool set that translates high-level parallel C to configuration bit streams for field-programmable logic based computing systems. MARGE creates an application-specific instruction set and generates the custom hardware components required to perform exactly those computations specified by the C program. In contrast to traditional fixed-instruction processors, MARGE's dynamic instruction set creation provides for efficient use of hardware resources. MARGE processes intermediate code in which each operation is annotated by the bit lengths of the operands. Each basic block (sequence of straight line code) is mapped into a single custom instruction which contains all the operations and logic inherent in the block. A synthesis phase maps the operations comprising the instructions into register transfer level structural components and control logic which have been optimized to exploit functional parallelism and function unit reuse. As a final stage, commercial technology-specific tools are used to generate configuration bit streams for the desired target hardware. Technology- specific pre-placed, pre-routed macro blocks are utilized to implement as much of the hardware as possible. MARGE currently supports the Xilinx-based Splash-2 reconfigurable accelerator and National Semiconductor's CLAy-based parallel accelerator, MAPA. The MARGE approach has been demonstrated on systolic applications such as DNA sequence comparison.
Solving the Cauchy-Riemann equations on parallel computers
NASA Technical Reports Server (NTRS)
Fatoohi, Raad A.; Grosch, Chester E.
1987-01-01
Discussed is the implementation of a single algorithm on three parallel-vector computers. The algorithm is a relaxation scheme for the solution of the Cauchy-Riemann equations; a set of coupled first order partial differential equations. The computers were chosen so as to encompass a variety of architectures. They are: the MPP, and SIMD machine with 16K bit serial processors; FLEX/32, an MIMD machine with 20 processors; and CRAY/2, an MIMD machine with four vector processors. The machine architectures are briefly described. The implementation of the algorithm is discussed in relation to these architectures and measures of the performance on each machine are given. Simple performance models are used to describe the performance. These models highlight the bottlenecks and limiting factors for this algorithm on these architectures. Conclusions are presented.
Parallel reservoir computing using optical amplifiers.
Vandoorne, Kristof; Dambre, Joni; Verstraeten, David; Schrauwen, Benjamin; Bienstman, Peter
2011-09-01
Reservoir computing (RC), a computational paradigm inspired on neural systems, has become increasingly popular in recent years for solving a variety of complex recognition and classification problems. Thus far, most implementations have been software-based, limiting their speed and power efficiency. Integrated photonics offers the potential for a fast, power efficient and massively parallel hardware implementation. We have previously proposed a network of coupled semiconductor optical amplifiers as an interesting test case for such a hardware implementation. In this paper, we investigate the important design parameters and the consequences of process variations through simulations. We use an isolated word recognition task with babble noise to evaluate the performance of the photonic reservoirs with respect to traditional software reservoir implementations, which are based on leaky hyperbolic tangent functions. Our results show that the use of coherent light in a well-tuned reservoir architecture offers significant performance benefits. The most important design parameters are the delay and the phase shift in the system's physical connections. With optimized values for these parameters, coherent semiconductor optical amplifier (SOA) reservoirs can achieve better results than traditional simulated reservoirs. We also show that process variations hardly degrade the performance, but amplifier noise can be detrimental. This effect must therefore be taken into account when designing SOA-based RC implementations.
Massively Parallel Solution of Poisson Equation on Coarse Grain MIMD Architectures
NASA Technical Reports Server (NTRS)
Fijany, A.; Weinberger, D.; Roosta, R.; Gulati, S.
1998-01-01
In this paper a new algorithm, designated as Fast Invariant Imbedding algorithm, for solution of Poisson equation on vector and massively parallel MIMD architectures is presented. This algorithm achieves the same optimal computational efficiency as other Fast Poisson solvers while offering a much better structure for vector and parallel implementation. Our implementation on the Intel Delta and Paragon shows that a speedup of over two orders of magnitude can be achieved even for moderate size problems.
A parallel VLSI architecture for a digital filter of arbitrary length using Fermat number transforms
NASA Technical Reports Server (NTRS)
Truong, T. K.; Reed, I. S.; Yeh, C. S.; Shao, H. M.
1982-01-01
A parallel architecture for computation of the linear convolution of two sequences of arbitrary lengths using the Fermat number transform (FNT) is described. In particular a pipeline structure is designed to compute a 128-point FNT. In this FNT, only additions and bit rotations are required. A standard barrel shifter circuit is modified so that it performs the required bit rotation operation. The overlap-save method is generalized for the FNT to compute a linear convolution of arbitrary length. A parallel architecture is developed to realize this type of overlap-save method using one FNT and several inverse FNTs of 128 points. The generalized overlap save method alleviates the usual dynamic range limitation in FNTs of long transform lengths. Its architecture is regular, simple, and expandable, and therefore naturally suitable for VLSI implementation.
New computer architectures as tools for ecological thought.
Villa, F
1992-06-01
Recent achievements of computer science provide unrivaled power for the advancement of ecology. This power is not merely computational: parallel computers, having hierarchical organization as their architectural principle, also provide metaphors for understanding complex systems. In this sense they might play for a science of ecological complexity a role like equilibrium-based metaphors had in the development of dynamic systems ecology. Parallel computers provide this opportunity through an informational view of ecological reality and multilevel modelling paradigms. Spatial and individual-oriented models allow application and full understanding of the new metaphors in the ecological context.
Performance variability of highly parallel architectures
Kramer, William T.C.; Ryan, Clint
2003-05-01
The design and evaluation of high performance computers has concentrated on increasing computational speed for applications. This performance is often measured on a well configured dedicated system to show the best case. In the real environment, resources are not always dedicated to a single task, and systems run tasks that may influence each other, so run times vary, sometimes to an unreasonably large extent. This paper explores the amount of variation seen across four large distributed memory systems in a systematic manner. It then analyzes the causes for the variations seen and discusses what can be done to decrease the variation without impacting performance.
IPython: components for interactive and parallel computing across disciplines. (Invited)
NASA Astrophysics Data System (ADS)
Perez, F.; Bussonnier, M.; Frederic, J. D.; Froehle, B. M.; Granger, B. E.; Ivanov, P.; Kluyver, T.; Patterson, E.; Ragan-Kelley, B.; Sailer, Z.
2013-12-01
Scientific computing is an inherently exploratory activity that requires constantly cycling between code, data and results, each time adjusting the computations as new insights and questions arise. To support such a workflow, good interactive environments are critical. The IPython project (http://ipython.org) provides a rich architecture for interactive computing with: 1. Terminal-based and graphical interactive consoles. 2. A web-based Notebook system with support for code, text, mathematical expressions, inline plots and other rich media. 3. Easy to use, high performance tools for parallel computing. Despite its roots in Python, the IPython architecture is designed in a language-agnostic way to facilitate interactive computing in any language. This allows users to mix Python with Julia, R, Octave, Ruby, Perl, Bash and more, as well as to develop native clients in other languages that reuse the IPython clients. In this talk, I will show how IPython supports all stages in the lifecycle of a scientific idea: 1. Individual exploration. 2. Collaborative development. 3. Production runs with parallel resources. 4. Publication. 5. Education. In particular, the IPython Notebook provides an environment for "literate computing" with a tight integration of narrative and computation (including parallel computing). These Notebooks are stored in a JSON-based document format that provides an "executable paper": notebooks can be version controlled, exported to HTML or PDF for publication, and used for teaching.
Image Processing Using a Parallel Architecture.
1987-12-01
Computer," Byte, 3: 14-25 (December 1978). McGraw-Hill, 1985 24. Trussell, H. Joel . "Processing of X-ray Images," Proceedings of the IEEE, 69: 615-627...Services Electronics Program contract N00014-79-C-0424 (AD-085-846). 107 Therrien , Charles W. et al. "A Multiprocessor System for Simulation of
Solution of partial differential equations on vector and parallel computers
NASA Technical Reports Server (NTRS)
Ortega, J. M.; Voigt, R. G.
1985-01-01
The present status of numerical methods for partial differential equations on vector and parallel computers was reviewed. The relevant aspects of these computers are discussed and a brief review of their development is included, with particular attention paid to those characteristics that influence algorithm selection. Both direct and iterative methods are given for elliptic equations as well as explicit and implicit methods for initial boundary value problems. The intent is to point out attractive methods as well as areas where this class of computer architecture cannot be fully utilized because of either hardware restrictions or the lack of adequate algorithms. Application areas utilizing these computers are briefly discussed.
Molecular dynamics on hypercube parallel computers
NASA Astrophysics Data System (ADS)
Smith, W.
1991-03-01
The implementation of molecular dynamics on parallel computers is described, with particular reference to hypercube computers. Three particular algorithms are described: replicated data (RD); systolic loop (SLS-G), and parallelised link-cells (PLC), all of which have good load balancing. The performance characteristics of each algorithm and the factors affecting their scaling properties are discussed. The article is pedagogic in intent, to introduce a novice to the main aspects of parallel computing in molecular dynamics.
Parallel and Distributed Computing Combinatorial Algorithms
1993-10-01
FUPNDKC %2,•, PARALLEL AND DISTRIBUTED COMPUTING COMBINATORIAL ALGORITHMS 6. AUTHOR(S) 2304/DS F49620-92-J-0125 DR. LEIGHTON 7 PERFORMING ORGANIZATION NAME...on several problems involving parallel and distributed computing and combinatorial optimization. This research is reported in the numerous papers that...network decom- position. In Proceedings of the Eleventh Annual ACM Symposium on Principles of Distributed Computing , August 1992. [15] B. Awerbuch, B
Direct-execution parallel architecture for the Advanced Continuous Simulation Language (ACSL)
Carroll, C.C.; Owen, J.E.
1988-05-01
A direct-execution parallel architecture for the Advanced Continuous Simulation Language (ACSL) is presented which overcomes the traditional disadvantages of simulations executed on a digital computer. The incorporation of parallel processing allows the mapping of simulations into a digital computer to be done in the same inherently parallel manner as they are currently mapped onto an analog computer. The direct-execution format maximizes the efficiency of the executed code since the need for a high level language compiler is eliminated. Resolution is greatly increased over that which is available with an analog computer without the sacrifice in execution speed normally expected with digitial computer simulations. Although this report covers all aspects of the new architecture, key emphasis is placed on the processing element configuration and the microprogramming of the ACLS constructs. The execution times for all ACLS constructs are computed using a model of a processing element based on the AMD 29000 CPU and the AMD 29027 FPU. The increase in execution speed provided by parallel processing is exemplified by comparing the derived execution times of two ACSL programs with the execution times for the same programs executed on a similar sequential architecture.
A direct-execution parallel architecture for the Advanced Continuous Simulation Language (ACSL)
NASA Technical Reports Server (NTRS)
Carroll, Chester C.; Owen, Jeffrey E.
1988-01-01
A direct-execution parallel architecture for the Advanced Continuous Simulation Language (ACSL) is presented which overcomes the traditional disadvantages of simulations executed on a digital computer. The incorporation of parallel processing allows the mapping of simulations into a digital computer to be done in the same inherently parallel manner as they are currently mapped onto an analog computer. The direct-execution format maximizes the efficiency of the executed code since the need for a high level language compiler is eliminated. Resolution is greatly increased over that which is available with an analog computer without the sacrifice in execution speed normally expected with digitial computer simulations. Although this report covers all aspects of the new architecture, key emphasis is placed on the processing element configuration and the microprogramming of the ACLS constructs. The execution times for all ACLS constructs are computed using a model of a processing element based on the AMD 29000 CPU and the AMD 29027 FPU. The increase in execution speed provided by parallel processing is exemplified by comparing the derived execution times of two ACSL programs with the execution times for the same programs executed on a similar sequential architecture.
Fast semivariogram computation using FPGA architectures
NASA Astrophysics Data System (ADS)
Lagadapati, Yamuna; Shirvaikar, Mukul; Dong, Xuanliang
2015-02-01
The semivariogram is a statistical measure of the spatial distribution of data and is based on Markov Random Fields (MRFs). Semivariogram analysis is a computationally intensive algorithm that has typically seen applications in the geosciences and remote sensing areas. Recently, applications in the area of medical imaging have been investigated, resulting in the need for efficient real time implementation of the algorithm. The semivariogram is a plot of semivariances for different lag distances between pixels. A semi-variance, γ(h), is defined as the half of the expected squared differences of pixel values between any two data locations with a lag distance of h. Due to the need to examine each pair of pixels in the image or sub-image being processed, the base algorithm complexity for an image window with n pixels is O(n2). Field Programmable Gate Arrays (FPGAs) are an attractive solution for such demanding applications due to their parallel processing capability. FPGAs also tend to operate at relatively modest clock rates measured in a few hundreds of megahertz, but they can perform tens of thousands of calculations per clock cycle while operating in the low range of power. This paper presents a technique for the fast computation of the semivariogram using two custom FPGA architectures. The design consists of several modules dedicated to the constituent computational tasks. A modular architecture approach is chosen to allow for replication of processing units. This allows for high throughput due to concurrent processing of pixel pairs. The current implementation is focused on isotropic semivariogram computations only. Anisotropic semivariogram implementation is anticipated to be an extension of the current architecture, ostensibly based on refinements to the current modules. The algorithm is benchmarked using VHDL on a Xilinx XUPV5-LX110T development Kit, which utilizes the Virtex5 FPGA. Medical image data from MRI scans are utilized for the experiments
NASA Technical Reports Server (NTRS)
Weeks, Cindy Lou
1986-01-01
Experiments were conducted at NASA Ames Research Center to define multi-tasking software requirements for multiple-instruction, multiple-data stream (MIMD) computer architectures. The focus was on specifying solutions for algorithms in the field of computational fluid dynamics (CFD). The program objectives were to allow researchers to produce usable parallel application software as soon as possible after acquiring MIMD computer equipment, to provide researchers with an easy-to-learn and easy-to-use parallel software language which could be implemented on several different MIMD machines, and to enable researchers to list preferred design specifications for future MIMD computer architectures. Analysis of CFD algorithms indicated that extensions of an existing programming language, adaptable to new computer architectures, provided the best solution to meeting program objectives. The CoFORTRAN Language was written in response to these objectives and to provide researchers a means to experiment with parallel software solutions to CFD algorithms on machines with parallel architectures.
Collectively loading an application in a parallel computer
Aho, Michael E.; Attinella, John E.; Gooding, Thomas M.; Miller, Samuel J.; Mundy, Michael B.
2016-01-05
Collectively loading an application in a parallel computer, the parallel computer comprising a plurality of compute nodes, including: identifying, by a parallel computer control system, a subset of compute nodes in the parallel computer to execute a job; selecting, by the parallel computer control system, one of the subset of compute nodes in the parallel computer as a job leader compute node; retrieving, by the job leader compute node from computer memory, an application for executing the job; and broadcasting, by the job leader to the subset of compute nodes in the parallel computer, the application for executing the job.
NASA Astrophysics Data System (ADS)
Lee, Mike M.; Cho, Byung Lok
2001-11-01
In this paper, we proposed a new First Partial product Addition (FPA) architecture with new compressor (or parallel counter) to CSA tree built in the process of adding partial product for improving speed in the fast parallel multiplier to improve the speed of calculating partial product by about 20% compared with existing parallel counter using full Adder. The new circuit reduces the CLA bit finding final sum by N/2 using the novel FPA architecture. A 5.14ns of multiplication speed of the 16X16 multiplier is obtained using 0.25um CMOS technology. The architecture of the multiplier is easily opted for pipeline design and demonstrates high speed performance.
Savannah River Site computing architecture migration guide
Not Available
1991-07-30
The SRS Computing Architecture is a vision statement for site computing which enumerates the strategies which will guide SRS computing efforts for the 1990s. Each strategy is supported by a number of feature statements which clarify the strategy by providing additional detail. Since it is a strategic planning document, the Architecture has sitewide applicability and endorsement but does not attempt to specify implementation details. It does, however, specify that a document will be developed to guide the migration from the current site environment to that envisioned by the new architecture. The goal of this document, the SRS Computing Architecture Migration Guide, is to identify specific strategic and tactical tasks which would have to be completed to fully implement the architectural vision for site computing as well as a recommended sequence and timeframe for addressing these tasks. It takes into account the expected availability of technology, the existing installed base, and interdependencies among architectural components and objectives.
Parallel Algorithms for Computer Vision.
1987-01-01
73 755 P fiu.LEL ALORITHMS FOR CO PUTER VISIO (U) /MASSACHUSETTS INST OF TECH CRMORIDGE T P00010 ET AL.JAN 8? ETL-0456 DACA7-05-C-8IIO m 7E F/0 1...regularization principles, such as edge detection, stereo , motion, surface interpolation and shape from shading. The basic members of class I are convolution...them in collabo- ration with Thinking Machines Corporation): * Parallel convolution * Zero-crossing detection * Stereo -matching * Surface reconstruction
Parallel Algorithms for Computer Vision.
1989-01-01
demonstrated the Vision Machine system processing images and recognizing objects through the inte- gration of several visual cues. The first version of the...achievements. n 2.1 The Vision Machine The overall organization of tie Vision Machine systeliis ased. o parallel processing of tie images by independent...smoothed and made dense by exploiting known constraints within each process (for example., that disparity is smooth). This is the stage of approximation
Parallel VLSI architecture emulation and the organization of APSA/MPP
NASA Technical Reports Server (NTRS)
Odonnell, John T.
1987-01-01
The Applicative Programming System Architecture (APSA) combines an applicative language interpreter with a novel parallel computer architecture that is well suited for Very Large Scale Integration (VLSI) implementation. The Massively Parallel Processor (MPP) can simulate VLSI circuits by allocating one processing element in its square array to an area on a square VLSI chip. As long as there are not too many long data paths, the MPP can simulate a VLSI clock cycle very rapidly. The APSA circuit contains a binary tree with a few long paths and many short ones. A skewed H-tree layout allows every processing element to simulate a leaf cell and up to four tree nodes, with no loss in parallelism. Emulation of a key APSA algorithm on the MPP resulted in performance 16,000 times faster than a Vax. This speed will make it possible for the APSA language interpreter to run fast enough to support research in parallel list processing algorithms.
Parallel computation with the spectral element method
Ma, Hong
1995-12-01
Spectral element models for the shallow water equations and the Navier-Stokes equations have been successfully implemented on a data parallel supercomputer, the Connection Machine model CM-5. The nonstaggered grid formulations for both models are described, which are shown to be especially efficient in data parallel computing environment.
Parallel unstructured grid generation for computational aerosciences
NASA Technical Reports Server (NTRS)
Shephard, Mark S.
1993-01-01
The objective of this research project is to develop efficient parallel automatic grid generation procedures for use in computational aerosciences. This effort is focused on a parallel version of the Finite Octree grid generator. Progress made during the first six months is reported.
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.
NASA Astrophysics Data System (ADS)
Decker, K. M.; Jayewardena, C.; Rehmann, R.
We describe the library lgtlib, and lgttool, the corresponding development environment for Monte Carlo simulations of lattice gauge theory on multiprocessor vector computers with shared memory. We explain why distributed memory parallel processor (DMPP) architectures are particularly appealing for compute-intensive scientific applications, and introduce the design of a general application and program development environment system for scientific applications on DMPP architectures.
NASA Technical Reports Server (NTRS)
Lee, J.; Kim, K.
1991-01-01
A Very Large Scale Integration (VLSI) architecture for robot direct kinematic computation suitable for industrial robot manipulators was investigated. The Denavit-Hartenberg transformations are reviewed to exploit a proper processing element, namely an augmented CORDIC. Specifically, two distinct implementations are elaborated on, such as the bit-serial and parallel. Performance of each scheme is analyzed with respect to the time to compute one location of the end-effector of a 6-links manipulator, and the number of transistors required.
Parallel, Asynchronous Executive (PAX): System concepts, facilities, and architecture
NASA Technical Reports Server (NTRS)
Jones, W. H.
1983-01-01
The Parallel, Asynchronous Executive (PAX) is a software operating system simulation that allows many computers to work on a single problem at the same time. PAX is currently implemented on a UNIVAC 1100/42 computer system. Independent UNIVAC runstreams are used to simulate independent computers. Data are shared among independent UNIVAC runstreams through shared mass-storage files. PAX has achieved the following: (1) applied several computing processes simultaneously to a single, logically unified problem; (2) resolved most parallel processor conflicts by careful work assignment; (3) resolved by means of worker requests to PAX all conflicts not resolved by work assignment; (4) provided fault isolation and recovery mechanisms to meet the problems of an actual parallel, asynchronous processing machine. Additionally, one real-life problem has been constructed for the PAX environment. This is CASPER, a collection of aerodynamic and structural dynamic problem simulation routines. CASPER is not discussed in this report except to provide examples of parallel-processing techniques.
Computing NLTE Opacities -- Node Level Parallel
Holladay, Daniel
2015-09-11
Presentation. The goal: to produce a robust library capable of computing reasonably accurate opacities inline with the assumption of LTE relaxed (non-LTE). Near term: demonstrate acceleration of non-LTE opacity computation. Far term (if funded): connect to application codes with in-line capability and compute opacities. Study science problems. Use efficient algorithms that expose many levels of parallelism and utilize good memory access patterns for use on advanced architectures. Portability to multiple types of hardware including multicore processors, manycore processors such as KNL, GPUs, etc. Easily coupled to radiation hydrodynamics and thermal radiative transfer codes.
A Parallel Saturation Algorithm on Shared Memory Architectures
NASA Technical Reports Server (NTRS)
Ezekiel, Jonathan; Siminiceanu
2007-01-01
Symbolic state-space generators are notoriously hard to parallelize. However, the Saturation algorithm implemented in the SMART verification tool differs from other sequential symbolic state-space generators in that it exploits the locality of ring events in asynchronous system models. This paper explores whether event locality can be utilized to efficiently parallelize Saturation on shared-memory architectures. Conceptually, we propose to parallelize the ring of events within a decision diagram node, which is technically realized via a thread pool. We discuss the challenges involved in our parallel design and conduct experimental studies on its prototypical implementation. On a dual-processor dual core PC, our studies show speed-ups for several example models, e.g., of up to 50% for a Kanban model, when compared to running our algorithm only on a single core.
NASA Astrophysics Data System (ADS)
Hegde, Ganapathi; Vaya, Pukhraj
2013-10-01
This article presents a parallel architecture for 3-D discrete wavelet transform (3-DDWT). The proposed design is based on the 1-D pipelined lifting scheme. The architecture is fully scalable beyond the present coherent Daubechies filter bank (9, 7). This 3-DDWT architecture has advantages such as no group of pictures restriction and reduced memory referencing. It offers low power consumption, low latency and high throughput. The computing technique is based on the concept that lifting scheme minimises the storage requirement. The application specific integrated circuit implementation of the proposed architecture is done by synthesising it using 65 nm Taiwan Semiconductor Manufacturing Company standard cell library. It offers a speed of 486 MHz with a power consumption of 2.56 mW. This architecture is suitable for real-time video compression even with large frame dimensions.
Fast combinatorial optimization with parallel digital computers.
Kakeya, H; Okabe, Y
2000-01-01
This paper presents an algorithm which realizes fast search for the solutions of combinatorial optimization problems with parallel digital computers.With the standard weight matrices designed for combinatorial optimization, many iterations are required before convergence to a quasioptimal solution even when many digital processors can be used in parallel. By removing the components of the eingenvectors with eminent negative eigenvalues of the weight matrix, the proposed algorithm avoids oscillation and realizes energy reduction under synchronous discrete dynamics, which enables parallel digital computers to obtain quasi-optimal solutions with much less time than the conventional algorithm.
Parallel hypergraph partitioning for scientific computing.
Heaphy, Robert; Devine, Karen Dragon; Catalyurek, Umit; Bisseling, Robert; Hendrickson, Bruce Alan; Boman, Erik Gunnar
2005-07-01
Graph partitioning is often used for load balancing in parallel computing, but it is known that hypergraph partitioning has several advantages. First, hypergraphs more accurately model communication volume, and second, they are more expressive and can better represent nonsymmetric problems. Hypergraph partitioning is particularly suited to parallel sparse matrix-vector multiplication, a common kernel in scientific computing. We present a parallel software package for hypergraph (and sparse matrix) partitioning developed at Sandia National Labs. The algorithm is a variation on multilevel partitioning. Our parallel implementation is novel in that it uses a two-dimensional data distribution among processors. We present empirical results that show our parallel implementation achieves good speedup on several large problems (up to 33 million nonzeros) with up to 64 processors on a Linux cluster.
Beyond the Renderer: Software Architecture for Parallel Graphics and Visualization
NASA Technical Reports Server (NTRS)
Crockett, Thomas W.
1996-01-01
As numerous implementations have demonstrated, software-based parallel rendering is an effective way to obtain the needed computational power for a variety of challenging applications in computer graphics and scientific visualization. To fully realize their potential, however, parallel renderers need to be integrated into a complete environment for generating, manipulating, and delivering visual data. We examine the structure and components of such an environment, including the programming and user interfaces, rendering engines, and image delivery systems. We consider some of the constraints imposed by real-world applications and discuss the problems and issues involved in bringing parallel rendering out of the lab and into production.
Adaptive Explicitly Parallel Instruction Computing
2000-12-16
1993. [17] James F. Blinn. Jim Blinn’s corner: Fugue for MMX. IEEE Computer Graphics and Applications, 17(2):88– 93, March/April 1997. Makes several...processors. IEEE Transactions on Computers, C-29(4):308–316, April 1980. [22] Doug Burger and James R. Goodman. Guest editors introduction: Billion...sequencing and scheduling: A survey. Ann. Discrete Mathematics, 5:287–326, 1979. [58] C. Ebeling D. C. Green and P. Franklin . RaPiD – reconfigurable
Traffic simulations on parallel computers using domain decomposition techniques
Hanebutte, U.R.; Tentner, A.M.
1995-12-31
Large scale simulations of Intelligent Transportation Systems (ITS) can only be achieved by using the computing resources offered by parallel computing architectures. Domain decomposition techniques are proposed which allow the performance of traffic simulations with the standard simulation package TRAF-NETSIM on a 128 nodes IBM SPx parallel supercomputer as well as on a cluster of SUN workstations. Whilst this particular parallel implementation is based on NETSIM, a microscopic traffic simulation model, the presented strategy is applicable to a broad class of traffic simulations. An outer iteration loop must be introduced in order to converge to a global solution. A performance study that utilizes a scalable test network that consist of square-grids is presented, which addresses the performance penalty introduced by the additional iteration loop.
Fault Tolerant Statistical Signal Processing Algorithms for Parallel Architectures.
2014-09-26
AD-fi57 393 FAULT TOLERANT STATISTICAL SIGNAL PROCESSING ALGORITHMS i/i FOR PARALLEL ARCH U) JOHNS HOPKINS UNIV BALTIMORE MD DEPT OF ELECTRICAL...COVERED * ’ Fault Tolerant Statistical Signal Processing Technical A l g o r i t h m s f o r P a r a l l e l A r c h i t e c t u r e s a ._ P E R F O R M I...Identify by block number) , Fault Tolerance, Signal Processing, Parallel Architecture 0 20. ABSTRACT (Continue on reveree side It neceseary and identify by
Computer-Aided Parallelizer and Optimizer
NASA Technical Reports Server (NTRS)
Jin, Haoqiang
2011-01-01
The Computer-Aided Parallelizer and Optimizer (CAPO) automates the insertion of compiler directives (see figure) to facilitate parallel processing on Shared Memory Parallel (SMP) machines. While CAPO currently is integrated seamlessly into CAPTools (developed at the University of Greenwich, now marketed as ParaWise), CAPO was independently developed at Ames Research Center as one of the components for the Legacy Code Modernization (LCM) project. The current version takes serial FORTRAN programs, performs interprocedural data dependence analysis, and generates OpenMP directives. Due to the widely supported OpenMP standard, the generated OpenMP codes have the potential to run on a wide range of SMP machines. CAPO relies on accurate interprocedural data dependence information currently provided by CAPTools. Compiler directives are generated through identification of parallel loops in the outermost level, construction of parallel regions around parallel loops and optimization of parallel regions, and insertion of directives with automatic identification of private, reduction, induction, and shared variables. Attempts also have been made to identify potential pipeline parallelism (implemented with point-to-point synchronization). Although directives are generated automatically, user interaction with the tool is still important for producing good parallel codes. A comprehensive graphical user interface is included for users to interact with the parallelization process.
A Parallel Trade Study Architecture for Design Optimization of Complex Systems
NASA Technical Reports Server (NTRS)
Kim, Hongman; Mullins, James; Ragon, Scott; Soremekun, Grant; Sobieszczanski-Sobieski, Jaroslaw
2005-01-01
Design of a successful product requires evaluating many design alternatives in a limited design cycle time. This can be achieved through leveraging design space exploration tools and available computing resources on the network. This paper presents a parallel trade study architecture to integrate trade study clients and computing resources on a network using Web services. The parallel trade study solution is demonstrated to accelerate design of experiments, genetic algorithm optimization, and a cost as an independent variable (CAIV) study for a space system application.
Performance analysis of parallel branch and bound search with the hypercube architecture
NASA Technical Reports Server (NTRS)
Mraz, Richard T.
1987-01-01
With the availability of commercial parallel computers, researchers are examining new classes of problems which might benefit from parallel computing. This paper presents results of an investigation of the class of search intensive problems. The specific problem discussed is the Least-Cost Branch and Bound search method of deadline job scheduling. The object-oriented design methodology was used to map the problem into a parallel solution. While the initial design was good for a prototype, the best performance resulted from fine-tuning the algorithm for a specific computer. The experiments analyze the computation time, the speed up over a VAX 11/785, and the load balance of the problem when using loosely coupled multiprocessor system based on the hypercube architecture.
Middleware in Modern High Performance Computing System Architectures
Engelmann, Christian; Ong, Hong Hoe; Scott, Stephen L
2007-01-01
A recent trend in modern high performance computing (HPC) system architectures employs ''lean'' compute nodes running a lightweight operating system (OS). Certain parts of the OS as well as other system software services are moved to service nodes in order to increase performance and scalability. This paper examines the impact of this HPC system architecture trend on HPC ''middleware'' software solutions, which traditionally equip HPC systems with advanced features, such as parallel and distributed programming models, appropriate system resource management mechanisms, remote application steering and user interaction techniques. Since the approach of keeping the compute node software stack small and simple is orthogonal to the middleware concept of adding missing OS features between OS and application, the role and architecture of middleware in modern HPC systems needs to be revisited. The result is a paradigm shift in HPC middleware design, where single middleware services are moved to service nodes, while runtime environments (RTEs) continue to reside on compute nodes.
Parallel Modem Architectures for High-Data-Rate Space Modems
NASA Astrophysics Data System (ADS)
Satorius, E.
2014-08-01
Existing software-defined radios (SDRs) for space are limited in data volume by several factors, including bandwidth, space-qualified analog-to-digital converter (ADC) technology, and processor throughput, e.g., the throughput of a space-qualified field-programmable gate array (FPGA). In an attempt to further improve the throughput of space-based SDRs and to fully exploit the newer and more capable space-qualified technology (ADCs, FPGAs), we are evaluating parallel transmitter/receiver architectures for space SDRs. These architectures would improve data volume for both deep-space and particularly proximity (e.g., relay) links. In this article, designs for FPGA implementation of a high-rate parallel modem are presented as well as both fixed- and floating-point simulated performance results based on a functional design that is suitable for FPGA implementation.
Case Studies of Software Development Tools for Parallel Architectures
1993-06-01
RL-TR-93-114 Final Technical Report AD-A269 193I M N11 Nal I U l iE rr ll Hllll CASE STUDIES OF SOFTWARE DEVELOPMENT TOOLS FOR PARALLEL ARCHITECTURES...65 Om ega/ PegaSys ..................................................................................... 66 PARET...Pisces Rn BALSA II TANGO PARET VMMP Omega/ PegaSys PSG POKER ISSOS Unity -4- PADWB Schedule Tool Degn Graph= Alg I/gr- Sol Pormbil- Ptform Pan/don Debug
Graph Partitioning Models for Parallel Computing
Hendrickson, B.; Kolda, T.G.
1999-03-02
Calculations can naturally be described as graphs in which vertices represent computation and edges reflect data dependencies. By partitioning the vertices of a graph, the calculation can be divided among processors of a parallel computer. However, the standard methodology for graph partitioning minimizes the wrong metric and lacks expressibility. We survey several recently proposed alternatives and discuss their relative merits.
NASA Astrophysics Data System (ADS)
Nishiura, Daisuke; Furuichi, Mikito; Sakaguchi, Hide
2015-09-01
The computational performance of a smoothed particle hydrodynamics (SPH) simulation is investigated for three types of current shared-memory parallel computer devices: many integrated core (MIC) processors, graphics processing units (GPUs), and multi-core CPUs. We are especially interested in efficient shared-memory allocation methods for each chipset, because the efficient data access patterns differ between compute unified device architecture (CUDA) programming for GPUs and OpenMP programming for MIC processors and multi-core CPUs. We first introduce several parallel implementation techniques for the SPH code, and then examine these on our target computer architectures to determine the most effective algorithms for each processor unit. In addition, we evaluate the effective computing performance and power efficiency of the SPH simulation on each architecture, as these are critical metrics for overall performance in a multi-device environment. In our benchmark test, the GPU is found to produce the best arithmetic performance as a standalone device unit, and gives the most efficient power consumption. The multi-core CPU obtains the most effective computing performance. The computational speed of the MIC processor on Xeon Phi approached that of two Xeon CPUs. This indicates that using MICs is an attractive choice for existing SPH codes on multi-core CPUs parallelized by OpenMP, as it gains computational acceleration without the need for significant changes to the source code.
Locating hardware faults in a parallel computer
Archer, Charles J.; Megerian, Mark G.; Ratterman, Joseph D.; Smith, Brian E.
2010-04-13
Locating hardware faults in a parallel computer, including defining within a tree network of the parallel computer two or more sets of non-overlapping test levels of compute nodes of the network that together include all the data communications links of the network, each non-overlapping test level comprising two or more adjacent tiers of the tree; defining test cells within each non-overlapping test level, each test cell comprising a subtree of the tree including a subtree root compute node and all descendant compute nodes of the subtree root compute node within a non-overlapping test level; performing, separately on each set of non-overlapping test levels, an uplink test on all test cells in a set of non-overlapping test levels; and performing, separately from the uplink tests and separately on each set of non-overlapping test levels, a downlink test on all test cells in a set of non-overlapping test levels.
Internode data communications in a parallel computer
Archer, Charles J; Blocksome, Michael A; Miller, Douglas R; Parker, Jeffrey J; Ratterman, Joseph D; Smith, Brian E
2014-02-11
Internode data communications in a parallel computer that includes compute nodes that each include main memory and a messaging unit, the messaging unit including computer memory and coupling compute nodes for data communications, in which, for each compute node at compute node boot time: a messaging unit allocates, in the messaging unit's computer memory, a predefined number of message buffers, each message buffer associated with a process to be initialized on the compute node; receives, prior to initialization of a particular process on the compute node, a data communications message intended for the particular process; and stores the data communications message in the message buffer associated with the particular process. Upon initialization of the particular process, the process establishes a messaging buffer in main memory of the compute node and copies the data communications message from the message buffer of the messaging unit into the message buffer of main memory.
Internode data communications in a parallel computer
Archer, Charles J.; Blocksome, Michael A.; Miller, Douglas R.; Parker, Jeffrey J.; Ratterman, Joseph D.; Smith, Brian E.
2013-09-03
Internode data communications in a parallel computer that includes compute nodes that each include main memory and a messaging unit, the messaging unit including computer memory and coupling compute nodes for data communications, in which, for each compute node at compute node boot time: a messaging unit allocates, in the messaging unit's computer memory, a predefined number of message buffers, each message buffer associated with a process to be initialized on the compute node; receives, prior to initialization of a particular process on the compute node, a data communications message intended for the particular process; and stores the data communications message in the message buffer associated with the particular process. Upon initialization of the particular process, the process establishes a messaging buffer in main memory of the compute node and copies the data communications message from the message buffer of the messaging unit into the message buffer of main memory.
Link failure detection in a parallel computer
Archer, Charles J.; Blocksome, Michael A.; Megerian, Mark G.; Smith, Brian E.
2010-11-09
Methods, apparatus, and products are disclosed for link failure detection in a parallel computer including compute nodes connected in a rectangular mesh network, each pair of adjacent compute nodes in the rectangular mesh network connected together using a pair of links, that includes: assigning each compute node to either a first group or a second group such that adjacent compute nodes in the rectangular mesh network are assigned to different groups; sending, by each of the compute nodes assigned to the first group, a first test message to each adjacent compute node assigned to the second group; determining, by each of the compute nodes assigned to the second group, whether the first test message was received from each adjacent compute node assigned to the first group; and notifying a user, by each of the compute nodes assigned to the second group, whether the first test message was received.
Methodology of modeling and measuring computer architectures for plasma simulations
NASA Technical Reports Server (NTRS)
Wang, L. P. T.
1977-01-01
A brief introduction to plasma simulation using computers and the difficulties on currently available computers is given. Through the use of an analyzing and measuring methodology - SARA, the control flow and data flow of a particle simulation model REM2-1/2D are exemplified. After recursive refinements the total execution time may be greatly shortened and a fully parallel data flow can be obtained. From this data flow, a matched computer architecture or organization could be configured to achieve the computation bound of an application problem. A sequential type simulation model, an array/pipeline type simulation model, and a fully parallel simulation model of a code REM2-1/2D are proposed and analyzed. This methodology can be applied to other application problems which have implicitly parallel nature.
Tyagi, Neelam; Bose, Abhijit; Chetty, Indrin J
2004-09-01
We have parallelized the Dose Planning Method (DPM), a Monte Carlo code optimized for radiotherapy class problems, on distributed-memory processor architectures using the Message Passing Interface (MPI). Parallelization has been investigated on a variety of parallel computing architectures at the University of Michigan-Center for Advanced Computing, with respect to efficiency and speedup as a function of the number of processors. We have integrated the parallel pseudo random number generator from the Scalable Parallel Pseudo-Random Number Generator (SPRNG) library to run with the parallel DPM. The Intel cluster consisting of 800 MHz Intel Pentium III processor shows an almost linear speedup up to 32 processors for simulating 1 x 10(8) or more particles. The speedup results are nearly linear on an Athlon cluster (up to 24 processors based on availability) which consists of 1.8 GHz+ Advanced Micro Devices (AMD) Athlon processors on increasing the problem size up to 8 x 10(8) histories. For a smaller number of histories (1 x 10(8)) the reduction of efficiency with the Athlon cluster (down to 83.9% with 24 processors) occurs because the processing time required to simulate 1 x 10(8) histories is less than the time associated with interprocessor communication. A similar trend was seen with the Opteron Cluster (consisting of 1400 MHz, 64-bit AMD Opteron processors) on increasing the problem size. Because of the 64-bit architecture Opteron processors are capable of storing and processing instructions at a faster rate and hence are faster as compared to the 32-bit Athlon processors. We have validated our implementation with an in-phantom dose calculation study using a parallel pencil monoenergetic electron beam of 20 MeV energy. The phantom consists of layers of water, lung, bone, aluminum, and titanium. The agreement in the central axis depth dose curves and profiles at different depths shows that the serial and parallel codes are equivalent in accuracy.
A Simple Physical Optics Algorithm Perfect for Parallel Computing
NASA Technical Reports Server (NTRS)
Imbriale, W. A.; Cwik, T.
1993-01-01
One of the simplest reflector antenna computer programs is based upon a discrete approximation of the radiation integral. This calculation replaces the actual reflector surface with a triangular facet representation so that the reflector resembles a geodesic dome. The Physical Optics (PO) current is assumed to be constant in magnitude and phase over each facet so the radiation integral is reduced to a simple summation. This program has proven to be surprisingly robust and useful for the analysis of arbitrary reflectors, particularly when the near-field is desired and surface derivatives are not known. Because of its simplicity, the algorithm has proven to be extremely easy to adapt to the parallel computing architecture of a modest number of large-grain computing elements such as are used in the Intel iPSC and Touchstone Delta parallel machines.
Fast Parallel Computation Of Multibody Dynamics
NASA Technical Reports Server (NTRS)
Fijany, Amir; Kwan, Gregory L.; Bagherzadeh, Nader
1996-01-01
Constraint-force algorithm fast, efficient, parallel-computation algorithm for solving forward dynamics problem of multibody system like robot arm or vehicle. Solves problem in minimum time proportional to log(N) by use of optimal number of processors proportional to N, where N is number of dynamical degrees of freedom: in this sense, constraint-force algorithm both time-optimal and processor-optimal parallel-processing algorithm.
Instant well-log inversion with a parallel computer
Kimminau, S.J.; Trivedi, H.
1993-08-01
Well-log analysis requires several vectors of input data to be inverted with a physical model that produces more vectors of output data. The problem is inherently suited to either vectorization or parallelization. PLATO (parallel log analysis, timely output) is a research prototype system that uses a parallel architecture computer with memory-mapped graphics to invert vector data and display the result rapidly. By combining this high-performance computing and display system with a graphical user interface, the analyst can interact with the system in real time'' and can visualize the result of changing parameters on up to 1,000 levels of computed volumes and reconstructed logs. It is expected that such instant'' inversion will remove the main disadvantages frequently cited for simultaneous analysis methods, namely difficulty in assessing sensitivity to different parameters and slow output response. Although the prototype system uses highly specific features of a parallel processor, a subsequent version has been implemented on a conventional (Serial) workstation with less performance but adequate functionality to preserve the apparently instant response. PLATO demonstrates the feasibility of petroleum computing applications combining an intuitive graphical interface, high-performance computing of physical models, and real-time output graphics.
NASA Astrophysics Data System (ADS)
Ford, Eric B.; Dindar, Saleh; Peters, Jorg
2015-08-01
The realism of astrophysical simulations and statistical analyses of astronomical data are set by the available computational resources. Thus, astronomers and astrophysicists are constantly pushing the limits of computational capabilities. For decades, astronomers benefited from massive improvements in computational power that were driven primarily by increasing clock speeds and required relatively little attention to details of the computational hardware. For nearly a decade, increases in computational capabilities have come primarily from increasing the degree of parallelism, rather than increasing clock speeds. Further increases in computational capabilities will likely be led by many-core architectures such as Graphical Processing Units (GPUs) and Intel Xeon Phi. Successfully harnessing these new architectures, requires significantly more understanding of the hardware architecture, cache hierarchy, compiler capabilities and network network characteristics.I will provide an astronomer's overview of the opportunities and challenges provided by modern many-core architectures and elastic cloud computing. The primary goal is to help an astronomical audience understand what types of problems are likely to yield more than order of magnitude speed-ups and which problems are unlikely to parallelize sufficiently efficiently to be worth the development time and/or costs.I will draw on my experience leading a team in developing the Swarm-NG library for parallel integration of large ensembles of small n-body systems on GPUs, as well as several smaller software projects. I will share lessons learned from collaborating with computer scientists, including both technical and soft skills. Finally, I will discuss the challenges of training the next generation of astronomers to be proficient in this new era of high-performance computing, drawing on experience teaching a graduate class on High-Performance Scientific Computing for Astrophysics and organizing a 2014 advanced summer
Parallel processing for computer vision and display
Dew, P.M. . Dept. of Computer Studies); Earnshaw, R.A. ); Heywood, T.R. )
1989-01-01
The widespread availability of high performance computers has led to an increased awareness of the importance of visualization techniques particularly in engineering and science. However, many visualization tasks involve processing large amounts of data or manipulating complex computer models of 3D objects. For example, in the field of computer aided engineering it is often necessary to display an edit solid object (see Plate 1) which can take many minutes even on the fastest serial processors. Another example of a computationally intensive problem, this time from computer vision, is the recognition of objects in a 3D scene from a stereo image pair. To perform visualization tasks of this type in real and reasonable time it is necessary to exploit the advances in parallel processing that have taken place over the last decade. This book uniquely provides a collection of papers from leading visualization researchers with a common interest in the application and exploitation of parallel processing techniques.
Wing-Body Aeroelasticity on Parallel Computers
NASA Technical Reports Server (NTRS)
Guruswamy, Guru P.; Byun, Chansup
1996-01-01
This article presents a procedure for computing the aeroelasticity of wing-body configurations on multiple-instruction, multiple-data parallel computers. In this procedure, fluids are modeled using Euler equations discretized by a finite difference method, and structures are modeled using finite element equations. The procedure is designed in such a way that each discipline can be developed and maintained independently by using a domain decomposition approach. A parallel integration scheme is used to compute aeroelastic responses by solving the coupled fluid and structural equations concurrently while keeping modularity of each discipline. The present procedure is validated by computing the aeroelastic response of a wing and comparing with experiment. Aeroelastic computations are illustrated for a high speed civil transport type wing-body configuration.
Reconfigurable Parallel Computer Architectures for Space Applications
2012-08-07
manifold”, “harness”, and “assembly” interchangeably, though the latter term will also be used to refer otherwise to aggregations of components...Hypertransport pairs. Although serial data transfers up to 3Gbps have been measured in short length LVDS lines, speeds of 600 to 800 Mbps are commonly...incremental data value test saves different numbers in different memory positions. Commonly, it is used to tag each memory position with the value of its
NASA Astrophysics Data System (ADS)
Hou, Zhen-Long; Wei, Xiao-Hui; Huang, Da-Nian; Sun, Xu
2015-09-01
We apply reweighted inversion focusing to full tensor gravity gradiometry data using message-passing interface (MPI) and compute unified device architecture (CUDA) parallel computing algorithms, and then combine MPI with CUDA to formulate a hybrid algorithm. Parallel computing performance metrics are introduced to analyze and compare the performance of the algorithms. We summarize the rules for the performance evaluation of parallel algorithms. We use model and real data from the Vinton salt dome to test the algorithms. We find good match between model and real density data, and verify the high efficiency and feasibility of parallel computing algorithms in the inversion of full tensor gravity gradiometry data.
Toward a science of parallel computation
Worlton, W.J.
1986-01-01
The evolution of parallel processing over the past several decades can be viewed as the development of a new scientific discipline. Parallel processing has been, and is, undergoing the same evolutionary stages that are common to the development of scientific disciplines in general: exploration, focusing, and maturity. That parallel processing is not yet a science can readily be appreciated by its lack of some of the characteristics typical of mature sciences, such as prescriptive terminology, comprehensive taxonomies, and authoritative fundamental principles. A great deal of outstanding work has been done and the field is experiencing the beginnings of its ''focusing'' phase, i.e., support is being concentrated in a set of the more promising approaches selected from among the larger set of exploratory projects. However, the possible set of parallel-processing concepts is so extensive that exploratory work will probably continue for one or two more decades. In the meantime, the growing maturity of the field will be reflected in the increasing clarity and precision of the terminology, the development of systematic classification of the domain of discourse, the development of basic principles, and the growing number of commercial products that are the outcome of the research and development projects on which support is being focused. In this paper we develop some generalizations of taxonomies and use basic principles to draw conclusions about the extensibility of parallel processor architectures. 7 refs., 5 figs., 2 tabs.
Efficient parallel architecture for highly coupled real-time linear system applications
NASA Technical Reports Server (NTRS)
Carroll, Chester C.; Homaifar, Abdollah; Barua, Soumavo
1988-01-01
A systematic procedure is developed for exploiting the parallel constructs of computation in a highly coupled, linear system application. An overall top-down design approach is adopted. Differential equations governing the application under consideration are partitioned into subtasks on the basis of a data flow analysis. The interconnected task units constitute a task graph which has to be computed in every update interval. Multiprocessing concepts utilizing parallel integration algorithms are then applied for efficient task graph execution. A simple scheduling routine is developed to handle task allocation while in the multiprocessor mode. Results of simulation and scheduling are compared on the basis of standard performance indices. Processor timing diagrams are developed on the basis of program output accruing to an optimal set of processors. Basic architectural attributes for implementing the system are discussed together with suggestions for processing element design. Emphasis is placed on flexible architectures capable of accommodating widely varying application specifics.
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.
Electro-Optic Computing Architectures: Volume II. Components and System Design and Analysis
1998-02-01
The objective of the Electro - Optic Computing Architecture (EOCA) program was to develop multi-function electro - optic interfaces and optical...interconnect units to enhance the performance of parallel processor systems and form the building blocks for future electro - optic computing architectures...Specifically, three multi-function interface modules were targeted for development - an Electro - Optic Interface (EOI), an Optical Interconnection Unit
Archer, Charles J; Blocksome, Michael E; Ratterman, Joseph D; Smith, Brian E
2014-02-11
Endpoint-based parallel data processing in a parallel active messaging interface ('PAMI') of a parallel computer, the PAMI composed of data communications endpoints, each endpoint including a specification of data communications parameters for a thread of execution on a compute node, including specifications of a client, a context, and a task, the compute nodes coupled for data communications through the PAMI, including establishing a data communications geometry, the geometry specifying, for tasks representing processes of execution of the parallel application, a set of endpoints that are used in collective operations of the PAMI including a plurality of endpoints for one of the tasks; receiving in endpoints of the geometry an instruction for a collective operation; and executing the instruction for a collective opeartion through the endpoints in dependence upon the geometry, including dividing data communications operations among the plurality of endpoints for one of the tasks.
Archer, Charles J.; Blocksome, Michael A.; Ratterman, Joseph D.; Smith, Brian E.
2014-08-12
Endpoint-based parallel data processing in a parallel active messaging interface (`PAMI`) of a parallel computer, the PAMI composed of data communications endpoints, each endpoint including a specification of data communications parameters for a thread of execution on a compute node, including specifications of a client, a context, and a task, the compute nodes coupled for data communications through the PAMI, including establishing a data communications geometry, the geometry specifying, for tasks representing processes of execution of the parallel application, a set of endpoints that are used in collective operations of the PAMI including a plurality of endpoints for one of the tasks; receiving in endpoints of the geometry an instruction for a collective operation; and executing the instruction for a collective operation through the endpoints in dependence upon the geometry, including dividing data communications operations among the plurality of endpoints for one of the tasks.
Design of a real-time wind turbine simulator using a custom parallel architecture
NASA Technical Reports Server (NTRS)
Hoffman, John A.; Gluck, R.; Sridhar, S.
1995-01-01
The design of a new parallel-processing digital simulator is described. The new simulator has been developed specifically for analysis of wind energy systems in real time. The new processor has been named: the Wind Energy System Time-domain simulator, version 3 (WEST-3). Like previous WEST versions, WEST-3 performs many computations in parallel. The modules in WEST-3 are pure digital processors, however. These digital processors can be programmed individually and operated in concert to achieve real-time simulation of wind turbine systems. Because of this programmability, WEST-3 is very much more flexible and general than its two predecessors. The design features of WEST-3 are described to show how the system produces high-speed solutions of nonlinear time-domain equations. WEST-3 has two very fast Computational Units (CU's) that use minicomputer technology plus special architectural features that make them many times faster than a microcomputer. These CU's are needed to perform the complex computations associated with the wind turbine rotor system in real time. The parallel architecture of the CU causes several tasks to be done in each cycle, including an IO operation and the combination of a multiply, add, and store. The WEST-3 simulator can be expanded at any time for additional computational power. This is possible because the CU's interfaced to each other and to other portions of the simulation using special serial buses. These buses can be 'patched' together in essentially any configuration (in a manner very similar to the programming methods used in analog computation) to balance the input/ output requirements. CU's can be added in any number to share a given computational load. This flexible bus feature is very different from many other parallel processors which usually have a throughput limit because of rigid bus architecture.
Computing association probabilities using parallel Boltzmann machines.
Iltis, R A; Ting, P Y
1993-01-01
A new computational method is presented for solving the data association problem using parallel Boltzmann machines. It is shown that the association probabilities can be computed with arbitrarily small errors if a sufficient number of parallel Boltzmann machines are available. The probability beta(i)(j) that the i th measurement emanated from the jth target can be obtained simply by observing the relative frequency with which neuron v(i,j) in a two-dimensional network is on throughout the layers. Some simple tracking examples comparing the performance of the Boltzmann algorithm to the exact data association solution and with the performance of an alternative parallel method using the Hopfield neural network are also presented.
Construction Morphology and the Parallel Architecture of Grammar.
Booij, Geert; Audring, Jenny
2015-11-24
This article presents a systematic exposition of how the basic ideas of Construction Grammar (CxG) (Goldberg, ) and the Parallel Architecture (PA) of grammar (Jackendoff, ) provide the framework for a proper account of morphological phenomena, in particular word formation. This framework is referred to as Construction Morphology (CxM). As to the implications of CxM for the architecture of grammar, the article provides evidence against a split between lexicon and grammar, in line with CxG. In addition, it shows that the PA approach makes it possible to be explicit about what happens on which level of the grammar, and thus to give an insightful account of interface phenomena. These interface phenomena appear to require that various types of information are accessible simultaneously, and it is argued that constructional schemas have the right format for expressing these mutual dependencies between different types of information.
Probabilistic structural mechanics research for parallel processing computers
NASA Technical Reports Server (NTRS)
Sues, Robert H.; Chen, Heh-Chyun; Twisdale, Lawrence A.; Martin, William R.
1991-01-01
Aerospace structures and spacecraft are a complex assemblage of structural components that are subjected to a variety of complex, cyclic, and transient loading conditions. Significant modeling uncertainties are present in these structures, in addition to the inherent randomness of material properties and loads. To properly account for these uncertainties in evaluating and assessing the reliability of these components and structures, probabilistic structural mechanics (PSM) procedures must be used. Much research has focused on basic theory development and the development of approximate analytic solution methods in random vibrations and structural reliability. Practical application of PSM methods was hampered by their computationally intense nature. Solution of PSM problems requires repeated analyses of structures that are often large, and exhibit nonlinear and/or dynamic response behavior. These methods are all inherently parallel and ideally suited to implementation on parallel processing computers. New hardware architectures and innovative control software and solution methodologies are needed to make solution of large scale PSM problems practical.
Parallel k-means++ for Multiple Shared-Memory Architectures
Mackey, Patrick S.; Lewis, Robert R.
2016-09-22
In recent years k-means++ has become a popular initialization technique for improved k-means clustering. To date, most of the work done to improve its performance has involved parallelizing algorithms that are only approximations of k-means++. In this paper we present a parallelization of the exact k-means++ algorithm, with a proof of its correctness. We develop implementations for three distinct shared-memory architectures: multicore CPU, high performance GPU, and the massively multithreaded Cray XMT platform. We demonstrate the scalability of the algorithm on each platform. In addition we present a visual approach for showing which platform performed k-means++ the fastest for varying data sizes.
User-microprogrammable, local host computer with low-level parallelism
Tomita, S.; Shibayama, K.; Kitamura, T.; Nakata, T.; Hagiwara, H.
1983-01-01
This paper describes the architecture of a dynamically microprogrammable computer with low-level parallelism, called QA-2, which is designed as a high-performance, local host computer for laboratory use. The architectural principle of the QA-2 is the marriage of high-speed, parallel processing capability offered by four powerful arithmetic and logic units (ALUS) with architectural flexibility provided by large scale, dynamic user-microprogramming. By changing its writable control storage dynamically, the QA-2 can be tailored to a wide spectrum of research-oriented applications covering high-level language processing and real-time processing. 11 references.
NASA Technical Reports Server (NTRS)
Smith, Garrett; Phillips, Alan
2002-01-01
There are currently three dominant TSTO class architectures. These are Series Burn (SB), Parallel Burn with crossfeed (PBw/cf), and Parallel Burn without crossfeed (PBncf). The goal of this study was to determine what factors uniquely affect PBncf architectures, how each of these factors interact, and to determine from a performance perspective whether a PBncf vehicle could be competitive with a PBw/cf or SB vehicle using equivalent technology and assumptions. In all cases, performance was evaluated on a relative basis for a fixed payload and mission by comparing gross and dry vehicle masses of a closed vehicle. Propellant combinations studied were LOX: LH2 propelled orbiter and booster (HH) and LOX: Kerosene booster with LOX: LH2 orbiter (KH). The study conclusions were: 1) a PBncf orbiter should be throttled as deeply as possible after launch until the staging point. 2) a detailed structural model is essential to accurate architecture analysis and evaluation. 3) a PBncf TSTO architecture is feasible for systems that stage at mach 7. 3a) HH architectures can achieve a mass growth relative to PBw/cf of < 20%. 3b) KH architectures can achieve a mass growth relative to Series Burn of < 20%. 4) center of gravity (CG) control will be a major issue for a PBncf vehicle, due to the low orbiter specific thrust to weight ratio and to the position of the orbiter required to align the nozzle heights at liftoff. 5 ) thrust to weight ratios of 1.3 at liftoff and between 1.0 and 0.9 when staging at mach 7 appear to be close to ideal for PBncf vehicles. 6) performance for all vehicles studied is better when staged at mach 7 instead of mach 5. The study showed that a Series Burn architecture has the lowest gross mass for HH cases, and has the lowest dry mass for KH cases. The potential disadvantages of SB are the required use of an air-start for the orbiter engines and potential CG control issues. A Parallel Burn with crossfeed architecture solves both these problems, but the
Heterogeneous computer architecture for embedded real-time image interpretation
NASA Astrophysics Data System (ADS)
Salinger, Jeremy A.
1993-10-01
A heterogeneous parallel-processing computer architecture is being developed for embedded real-time interpretation of images and other data collected from sensors on mobile platforms. The Advanced Target Cueing and Recognition Engine (ATCURE) architecture includes specialized subsystems for input/output, image processing, numeric processing, and symbolic processing. Different specialization is provided for each subsystem to exploit distinctive demands for data storage, data representation, mixes of operations, and program control structures. The characteristics of each subsystem are described, with the Image Processing Subsystem (IPS) used to illustrate how the design is driven by careful analysis of current and projected computational requirements from many applications. These considerations led to a programming model for the Image Processing Subsystem in which images and their subsets are the fundamental unit of data. The processor implementation incorporates a scalable synchronous pipeline of processing elements that eliminates many of the bottlenecks found in MIMD and SIMD architectures.
A computer architecture for intelligent machines
NASA Technical Reports Server (NTRS)
Lefebvre, D. R.; Saridis, G. N.
1991-01-01
The Theory of Intelligent Machines proposes a hierarchical organization for the functions of an autonomous robot based on the Principle of Increasing Precision With Decreasing Intelligence. An analytic formulation of this theory using information-theoretic measures of uncertainty for each level of the intelligent machine has been developed in recent years. A computer architecture that implements the lower two levels of the intelligent machine is presented. The architecture supports an event-driven programming paradigm that is independent of the underlying computer architecture and operating system. Details of Execution Level controllers for motion and vision systems are addressed, as well as the Petri net transducer software used to implement Coordination Level functions. Extensions to UNIX and VxWorks operating systems which enable the development of a heterogeneous, distributed application are described. A case study illustrates how this computer architecture integrates real-time and higher-level control of manipulator and vision systems.
Designing a meta-level architecture in Java for adaptive parallelism by mobile software agents
NASA Astrophysics Data System (ADS)
Dominic, Stephen Victor
Adaptive parallelism refers to a parallel computation that runs on a pool of processors that may join or withdraw from a running computation. In this dissertation, a functional system of agents and agent behaviors for adaptive parallelism is developed. Software agents have the properties of robustness and have capacity for fault-tolerance. Adaptation and fault-tolerance emerge from the interaction of self-directed autonomous software agents for a parallel computation application. The multi-agent system can be considered an object-oriented system with a higher-level architectural component, i.e., a meta level for agent behavior. The meta-level object architecture is based on patterns of behavior and communication for mobile agents, which are developed to support cooperative problem solving in a distributed-heterogeneous computing environment. Although parallel processing is a suggested application domain for mobile agents implemented in the Java language, the development of robust agent behaviors implemented in an efficient manner is an active research area. Performance characteristics for three versions of a pattern recognition problem are used to demonstrate a linear speed-up with efficiency that is compared to research using a traditional client-server protocol in the C language. The best ideas from existing approaches to adaptive parallelism are used to create a single general-purpose paradigm that overcomes problems associated with nodefailure, the use of a single-centralized or shared resource, requirements for clients to actively join a computation, and a variety of other limitations that are associated with existing systems. The multi-agent system, and experiments, show how adaptation and parallelism can be exploited by a meta-architecture for a distributed-scientific application that is of particular interest to design of signal-processing ground stations. To a large extent the framework separates concern for algorithmic design from concern for where and
A Component Architecture for High-Performance Computing
Bernholdt, D E; Elwasif, W R; Kohl, J A; Epperly, T G W
2003-01-21
The Common Component Architecture (CCA) provides a means for developers to manage the complexity of large-scale scientific software systems and to move toward a ''plug and play'' environment for high-performance computing. The CCA model allows for a direct connection between components within the same process to maintain performance on inter-component calls. It is neutral with respect to parallelism, allowing components to use whatever means they desire to communicate within their parallel ''cohort.'' We will discuss in detail the importance of performance in the design of the CCA and will analyze the performance costs associated with features of the CCA.
An improved spectral graph partitioning algorithm for mapping parallel computations
Hendrickson, B.; Leland, R.
1992-09-01
Efficient use of a distributed memory parallel computer requires that the computational load be balanced across processors in a way that minimizes interprocessor communication. We present a new domain mapping algorithm that extends recent work in which ideas from spectral graph theory have been applied to this problem. Our generalization of spectral graph bisection involves a novel use of multiple eigenvectors to allow for division of a computation into four or eight parts at each stage of a recursive decomposition. The resulting method is suitable for scientific computations like irregular finite elements or differences performed on hypercube or mesh architecture machines. Experimental results confirm that the new method provides better decompositions arrived at more economically and robustly than with previous spectral methods. We have also improved upon the known spectral lower bound for graph bisection.
Unsteady flow simulation on a parallel computer
NASA Astrophysics Data System (ADS)
Faden, M.; Pokorny, S.; Engel, K.
For the simulation of the flow through compressor stages, an interactive flow simulation system is set up on an MIMD-type parallel computer. An explicit scheme is used in order to resolve the time-dependent interaction between the blades. The 2D Navier-Stokes equations are transformed into their general moving coordinates. The parallelization of the solver is based on the idea of domain decomposition. Results are presented for a problem of fixed size (4096 grid nodes for the Hakkinen case).
Design Issues in Parallel Architectures for Artificial Intelligence.
1983-11-01
procedures for taking action. 5. The Apiary Approach We are developing an experimental machine architecture. called the Apiary . based on theory [Hewitt 801...To date, much o1 _,e implementation work on the Apiary has centered around simulating the Apiary on a network of current-generation sequential...Instead. we model the Apiary as a set of workers, each worker being analogous to a single computer executing instructions serially, together with its own
Intranode data communications in a parallel computer
Archer, Charles J; Blocksome, Michael A; Miller, Douglas R; Ratterman, Joseph D; Smith, Brian E
2013-07-23
Intranode data communications in a parallel computer that includes compute nodes configured to execute processes, where the data communications include: allocating, upon initialization of a first process of a compute node, a region of shared memory; establishing, by the first process, a predefined number of message buffers, each message buffer associated with a process to be initialized on the compute node; sending, to a second process on the same compute node, a data communications message without determining whether the second process has been initialized, including storing the data communications message in the message buffer of the second process; and upon initialization of the second process: retrieving, by the second process, a pointer to the second process's message buffer; and retrieving, by the second process from the second process's message buffer in dependence upon the pointer, the data communications message sent by the first process.
Intranode data communications in a parallel computer
Archer, Charles J; Blocksome, Michael A; Miller, Douglas R; Ratterman, Joseph D; Smith, Brian E
2014-01-07
Intranode data communications in a parallel computer that includes compute nodes configured to execute processes, where the data communications include: allocating, upon initialization of a first process of a computer node, a region of shared memory; establishing, by the first process, a predefined number of message buffers, each message buffer associated with a process to be initialized on the compute node; sending, to a second process on the same compute node, a data communications message without determining whether the second process has been initialized, including storing the data communications message in the message buffer of the second process; and upon initialization of the second process: retrieving, by the second process, a pointer to the second process's message buffer; and retrieving, by the second process from the second process's message buffer in dependence upon the pointer, the data communications message sent by the first process.
Parallel computing in atmospheric chemistry models
Rotman, D.
1996-02-01
Studies of atmospheric chemistry are of high scientific interest, involve computations that are complex and intense, and require enormous amounts of I/O. Current supercomputer computational capabilities are limiting the studies of stratospheric and tropospheric chemistry and will certainly not be able to handle the upcoming coupled chemistry/climate models. To enable such calculations, the authors have developed a computing framework that allows computations on a wide range of computational platforms, including massively parallel machines. Because of the fast paced changes in this field, the modeling framework and scientific modules have been developed to be highly portable and efficient. Here, the authors present the important features of the framework and focus on the atmospheric chemistry module, named IMPACT, and its capabilities. Applications of IMPACT to aircraft studies will be presented.
Switching from Computer to Microcomputer Architecture Education
ERIC Educational Resources Information Center
Bolanakis, Dimosthenis E.; Kotsis, Konstantinos T.; Laopoulos, Theodore
2010-01-01
In the last decades, the technological and scientific evolution of the computing discipline has been widely affecting research in software engineering education, which nowadays advocates more enlightened and liberal ideas. This article reviews cross-disciplinary research on a computer architecture class in consideration of its switching to…
THE COMPUTER AND THE ARCHITECTURAL PROFESSION.
ERIC Educational Resources Information Center
HAVILAND, DAVID S.
THE ROLE OF ADVANCING TECHNOLOGY IN THE FIELD OF ARCHITECTURE IS DISCUSSED IN THIS REPORT. PROBLEMS IN COMMUNICATION AND THE DESIGN PROCESS ARE IDENTIFIED. ADVANTAGES AND DISADVANTAGES OF COMPUTERS ARE MENTIONED IN RELATION TO MAN AND MACHINE INTERACTION. PRESENT AND FUTURE IMPLICATIONS OF COMPUTER USAGE ARE IDENTIFIED AND DISCUSSED WITH RESPECT…
LIBRA: A high-performance balanced computer architecture for Prolog
Mills, J.W.
1988-01-01
Four reduced-instruction-set computer (RISC) architectures for Prolog are presented: the Simple Abstract Machine (SAM), the Logic Programming Windowed RISC I (LOW RISC I), the LOW RISC II, and the Logical Inference Balanced RISC Architecture (LIBRA). An informal methodology for the semantic-based design of computer architectures relates the design of each architecture to its predecessor. The suitability of each architecture for Prolog is evaluated using macro expansions for each WAM instruction, from which execution speed, code density, memory usage, branch frequency, standard logical inferences per second, benchmark logical inferences per second and the semantic gap of each architecture relative to Prolog are calculated. The final design, the LIBRA, is 2.3 times as fast as the Berkeley PLM without interleaved memory, and 15 times as fast with eight-way instruction and data memory interleaving, reaching an estimated execution speed of 7.5 million standard logical inferences per second. The LIBRA's performance is due to parallelized tag and data operations, pipelining, reduced branch frequency, and complex single-cycle instructions.
Synchronizing compute node time bases in a parallel computer
Chen, Dong; Faraj, Daniel A; Gooding, Thomas M; Heidelberger, Philip
2014-12-30
Synchronizing time bases in a parallel computer that includes compute nodes organized for data communications in a tree network, where one compute node is designated as a root, and, for each compute node: calculating data transmission latency from the root to the compute node; configuring a thread as a pulse waiter; initializing a wakeup unit; and performing a local barrier operation; upon each node completing the local barrier operation, entering, by all compute nodes, a global barrier operation; upon all nodes entering the global barrier operation, sending, to all the compute nodes, a pulse signal; and for each compute node upon receiving the pulse signal: waking, by the wakeup unit, the pulse waiter; setting a time base for the compute node equal to the data transmission latency between the root node and the compute node; and exiting the global barrier operation.
Synchronizing compute node time bases in a parallel computer
Chen, Dong; Faraj, Daniel A; Gooding, Thomas M; Heidelberger, Philip
2015-01-27
Synchronizing time bases in a parallel computer that includes compute nodes organized for data communications in a tree network, where one compute node is designated as a root, and, for each compute node: calculating data transmission latency from the root to the compute node; configuring a thread as a pulse waiter; initializing a wakeup unit; and performing a local barrier operation; upon each node completing the local barrier operation, entering, by all compute nodes, a global barrier operation; upon all nodes entering the global barrier operation, sending, to all the compute nodes, a pulse signal; and for each compute node upon receiving the pulse signal: waking, by the wakeup unit, the pulse waiter; setting a time base for the compute node equal to the data transmission latency between the root node and the compute node; and exiting the global barrier operation.
Parallel processing architecture for H.264 deblocking filter on multi-core platforms
NASA Astrophysics Data System (ADS)
Prasad, Durga P.; Sonachalam, Sekar; Kunchamwar, Mangesh K.; Gunupudi, Nageswara Rao
2012-03-01
Massively parallel computing (multi-core) chips offer outstanding new solutions that satisfy the increasing demand for high resolution and high quality video compression technologies such as H.264. Such solutions not only provide exceptional quality but also efficiency, low power, and low latency, previously unattainable in software based designs. While custom hardware and Application Specific Integrated Circuit (ASIC) technologies may achieve lowlatency, low power, and real-time performance in some consumer devices, many applications require a flexible and scalable software-defined solution. The deblocking filter in H.264 encoder/decoder poses difficult implementation challenges because of heavy data dependencies and the conditional nature of the computations. Deblocking filter implementations tend to be fixed and difficult to reconfigure for different needs. The ability to scale up for higher quality requirements such as 10-bit pixel depth or a 4:2:2 chroma format often reduces the throughput of a parallel architecture designed for lower feature set. A scalable architecture for deblocking filtering, created with a massively parallel processor based solution, means that the same encoder or decoder will be deployed in a variety of applications, at different video resolutions, for different power requirements, and at higher bit-depths and better color sub sampling patterns like YUV, 4:2:2, or 4:4:4 formats. Low power, software-defined encoders/decoders may be implemented using a massively parallel processor array, like that found in HyperX technology, with 100 or more cores and distributed memory. The large number of processor elements allows the silicon device to operate more efficiently than conventional DSP or CPU technology. This software programing model for massively parallel processors offers a flexible implementation and a power efficiency close to that of ASIC solutions. This work describes a scalable parallel architecture for an H.264 compliant deblocking
Efficient Parallel Engineering Computing on Linux Workstations
NASA Technical Reports Server (NTRS)
Lou, John Z.
2010-01-01
A C software module has been developed that creates lightweight processes (LWPs) dynamically to achieve parallel computing performance in a variety of engineering simulation and analysis applications to support NASA and DoD project tasks. The required interface between the module and the application it supports is simple, minimal and almost completely transparent to the user applications, and it can achieve nearly ideal computing speed-up on multi-CPU engineering workstations of all operating system platforms. The module can be integrated into an existing application (C, C++, Fortran and others) either as part of a compiled module or as a dynamically linked library (DLL).
Pi: A Parallel Architecture Interface for Multi-Model Execution
1990-07-01
VON [52], the Transputer [31], the Connection Machine [56]. WARP [4], the NCUBE 2 [43], RP3 [46], J-Machine [IS]. the BBN Butterfly [8], and the BBN... Monarch [48]). In this class, novel machine organizations and new technological advances are combined in a machine design. The machines often sport...Potter, editor, The Aassively Parallel Processor, pages 142-149. MIT Press, 1985. [8] BBN, Advanced Computers, Inc., Cambridge, MA. Butterfly Product
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.
Use Computer-Aided Tools to Parallelize Large CFD Applications
NASA Technical Reports Server (NTRS)
Jin, H.; Frumkin, M.; Yan, J.
2000-01-01
Porting applications to high performance parallel computers is always a challenging task. It is time consuming and costly. With rapid progressing in hardware architectures and increasing complexity of real applications in recent years, the problem becomes even more sever. Today, scalability and high performance are mostly involving handwritten parallel programs using message-passing libraries (e.g. MPI). However, this process is very difficult and often error-prone. The recent reemergence of shared memory parallel (SMP) architectures, such as the cache coherent Non-Uniform Memory Access (ccNUMA) architecture used in the SGI Origin 2000, show good prospects for scaling beyond hundreds of processors. Programming on an SMP is simplified by working in a globally accessible address space. The user can supply compiler directives, such as OpenMP, to parallelize the code. As an industry standard for portable implementation of parallel programs for SMPs, OpenMP is a set of compiler directives and callable runtime library routines that extend Fortran, C and C++ to express shared memory parallelism. It promises an incremental path for parallel conversion of existing software, as well as scalability and performance for a complete rewrite or an entirely new development. Perhaps the main disadvantage of programming with directives is that inserted directives may not necessarily enhance performance. In the worst cases, it can create erroneous results. While vendors have provided tools to perform error-checking and profiling, automation in directive insertion is very limited and often failed on large programs, primarily due to the lack of a thorough enough data dependence analysis. To overcome the deficiency, we have developed a toolkit, CAPO, to automatically insert OpenMP directives in Fortran programs and apply certain degrees of optimization. CAPO is aimed at taking advantage of detailed inter-procedural dependence analysis provided by CAPTools, developed by the University of
Investigating Architectural Issues in Neuromorphic Computing
2009-06-01
approaching other difficult to scale applications like Parallel Discrete Event Simulation (PDES). PDES applications are models of physical processes...architectures with the need to communicate events to all affected elements 4 within the simulation . PDES applications typically do not scale well...dendrites with axons at junctures called synapses. Neurons produce electrical signals along these pathways. The signals may either excite or inhibit
Evaluation of leading scalar and vector architectures for scientific computations
Simon, Horst D.; Oliker, Leonid; Canning, Andrew; Carter, Jonathan; Ethier, Stephane; Shalf, John
2004-04-20
The growing gap between sustained and peak performance for scientific applications is a well-known problem in high performance computing. The recent development of parallel vector systems offers the potential to reduce this gap for many computational science codes and deliver a substantial increase in computing capabilities. This project examines the performance of the cacheless vector Earth Simulator (ES) and compares it to superscalar cache-based IBM Power3 system. Results demonstrate that the ES is significantly faster than the Power3 architecture, highlighting the tremendous potential advantage of the ES for numerical simulation. However, vectorization of a particle-in-cell application (GTC) greatly increased the memory footprint preventing loop-level parallelism and limiting scalability potential.
Barrett, Richard Frederick; Heroux, Michael Allen; Vaughan, Courtenay Thomas
2012-04-01
A broad range of scientific computation involves the use of difference stencils. In a parallel computing environment, this computation is typically implemented by decomposing the spacial domain, inducing a 'halo exchange' of process-owned boundary data. This approach adheres to the Bulk Synchronous Parallel (BSP) model. Because commonly available architectures provide strong inter-node bandwidth relative to latency costs, many codes 'bulk up' these messages by aggregating data into a message as a means of reducing the number of messages. A renewed focus on non-traditional architectures and architecture features provides new opportunities for exploring alternatives to this programming approach. In this report we describe miniGhost, a 'miniapp' designed for exploration of the capabilities of current as well as emerging and future architectures within the context of these sorts of applications. MiniGhost joins the suite of miniapps developed as part of the Mantevo project.
Efficient solid state NMR powder simulations using SMP and MPP parallel computation
NASA Astrophysics Data System (ADS)
Kristensen, Jørgen Holm; Farnan, Ian
2003-04-01
Methods for parallel simulation of solid state NMR powder spectra are presented for both shared and distributed memory parallel supercomputers. For shared memory architectures the performance of simulation programs implementing the OpenMP application programming interface is evaluated. It is demonstrated that the design of correct and efficient shared memory parallel programs is difficult as the performance depends on data locality and cache memory effects. The distributed memory parallel programming model is examined for simulation programs using the MPI message passing interface. The results reveal that both shared and distributed memory parallel computation are very efficient with an almost perfect application speedup and may be applied to the most advanced powder simulations.
Parallel Computational Environment for Substructure Optimization
NASA Technical Reports Server (NTRS)
Gendy, Atef S.; Patnaik, Surya N.; Hopkins, Dale A.; Berke, Laszlo
1995-01-01
Design optimization of large structural systems can be attempted through a substructure strategy when convergence difficulties are encountered. When this strategy is used, the large structure is divided into several smaller substructures and a subproblem is defined for each substructure. The solution of the large optimization problem can be obtained iteratively through repeated solutions of the modest subproblems. Substructure strategies, in sequential as well as in parallel computational modes on a Cray YMP multiprocessor computer, have been incorporated in the optimization test bed CometBoards. CometBoards is an acronym for Comparative Evaluation Test Bed of Optimization and Analysis Routines for Design of Structures. Three issues, intensive computation, convergence of the iterative process, and analytically superior optimum, were addressed in the implementation of substructure optimization into CometBoards. Coupling between subproblems as well as local and global constraint grouping are essential for convergence of the iterative process. The substructure strategy can produce an analytically superior optimum different from what can be obtained by regular optimization. For the problems solved, substructure optimization in a parallel computational mode made effective use of all assigned processors.
Architectural Implications of Cloud Computing
2011-10-24
Mellon University Final Thoughts 1 Cloud Computing is in essence an economic model • It is a different way to acquire and manage IT resources...Cloud (EC2): http://aws.amazon.com/ec2/ • Amazon Simple Storage Solution (S3): http://aws.amazon.com/s3/ • Eucalyptus Systems: http
Computational chaos in massively parallel neural networks
NASA Technical Reports Server (NTRS)
Barhen, Jacob; Gulati, Sandeep
1989-01-01
A fundamental issue which directly impacts the scalability of current theoretical neural network models to massively parallel embodiments, in both software as well as hardware, is the inherent and unavoidable concurrent asynchronicity of emerging fine-grained computational ensembles and the possible emergence of chaotic manifestations. Previous analyses attributed dynamical instability to the topology of the interconnection matrix, to parasitic components or to propagation delays. However, researchers have observed the existence of emergent computational chaos in a concurrently asynchronous framework, independent of the network topology. Researcher present a methodology enabling the effective asynchronous operation of large-scale neural networks. Necessary and sufficient conditions guaranteeing concurrent asynchronous convergence are established in terms of contracting operators. Lyapunov exponents are computed formally to characterize the underlying nonlinear dynamics. Simulation results are presented to illustrate network convergence to the correct results, even in the presence of large delays.
Computation and parallel implementation for early vision
NASA Technical Reports Server (NTRS)
Gualtieri, J. Anthony
1990-01-01
The problem of early vision is to transform one or more retinal illuminance images-pixel arrays-to image representations built out of such primitive visual features such as edges, regions, disparities, and clusters. These transformed representations form the input to later vision stages that perform higher level vision tasks including matching and recognition. Researchers developed algorithms for: (1) edge finding in the scale space formulation; (2) correlation methods for computing matches between pairs of images; and (3) clustering of data by neural networks. These algorithms are formulated for parallel implementation of SIMD machines, such as the Massively Parallel Processor, a 128 x 128 array processor with 1024 bits of local memory per processor. For some cases, researchers can show speedups of three orders of magnitude over serial implementations.
An Expert Assistant for Computer Aided Parallelization
NASA Technical Reports Server (NTRS)
Jost, Gabriele; Chun, Robert; Jin, Haoqiang; Labarta, Jesus; Gimenez, Judit
2004-01-01
The prototype implementation of an expert system was developed to assist the user in the computer aided parallelization process. The system interfaces to tools for automatic parallelization and performance analysis. By fusing static program structure information and dynamic performance analysis data the expert system can help the user to filter, correlate, and interpret the data gathered by the existing tools. Sections of the code that show poor performance and require further attention are rapidly identified and suggestions for improvements are presented to the user. In this paper we describe the components of the expert system and discuss its interface to the existing tools. We present a case study to demonstrate the successful use in full scale scientific applications.
Performance evaluation of the SX-6 vector architecture forscientific computations
Oliker, Leonid; Canning, Andrew; Carter, Jonathan Carter; Shalf,John; Skinner, David; Ethier, Stephane; Biswas, Rupak; Djomehri,Jahed; Van der Wijngaart, Rob
2005-01-01
The growing gap between sustained and peak performance for scientific applications is a well-known problem in high performance computing. The recent development of parallel vector systems offers the potential to reduce this gap for many computational science codes and deliver a substantial increase in computing capabilities. This paper examines the intranode performance of the NEC SX-6 vector processor, and compares it against the cache-based IBMPower3 and Power4 superscalar architectures, across a number of key scientific computing areas. First, we present the performance of a microbenchmark suite that examines many low-level machine characteristics. Next, we study the behavior of the NAS Parallel Benchmarks. Finally, we evaluate the performance of several scientific computing codes. Overall results demonstrate that the SX-6 achieves high performance on a large fraction of our application suite and often significantly outperforms the cache-based architectures. However, certain classes of applications are not easily amenable to vectorization and would require extensive algorithm and implementation reengineering to utilize the SX-6 effectively.
Orthogonal topography in the parallel input architecture of songbird HVC.
Elliott, Kevin C; Wu, Wei; Bertram, Richard; Hyson, Richard L; Johnson, Frank
2017-02-11
Neural activity within the cortical premotor nucleus HVC (acronym is name) encodes the learned songs of adult male zebra finches (Taeniopygia guttata). HVC activity is driven and/or modulated by a group of five afferent nuclei (the Medial Magnocellular nucleus of the Anterior Nidopallium, MMAN; Nucleus Interface, NIf; nucleus Avalanche, Av; the Robust nucleus of the Arcopallium, RA; the Uvaeform nucleus, Uva). While earlier evidence suggested that HVC receives a uniformly distributed and nontopographic pattern of afferent input, recent evidence suggests this view is incorrect (Basista et al., ). Here, we used a double-labeling strategy (varying both the distance between and the axial orientation of dual tracer injections into HVC) to reveal a massively parallel and in some cases topographic pattern of afferent input. Afferent neurons target only one rostral or caudal location within medial or lateral HVC, and each HVC location receives convergent input from each afferent nucleus in parallel. Quantifying the distributions of single-labeled cells revealed an orthogonal topography in the organization of afferent input from MMAN and NIf, two cortical nuclei necessary for song learning. MMAN input is organized across the lateral-medial axis whereas NIf input is organized across the rostral-caudal axis. To the extent that HVC activity is influenced by afferent input during the learning, perception, or production of song, functional models of HVC activity may need revision to account for the parallel input architecture of HVC, along with the orthogonal input topography of MMAN and NIf. J. Comp. Neurol., 2016. © 2016 Wiley Periodicals, Inc.
Parallel algorithm for computing points on a computation front hyperplane
NASA Astrophysics Data System (ADS)
Krasnov, M. M.
2015-01-01
A parallel algorithm for computing points on a computation front hyperplane is described. This task arises in the computation of a quantity defined on a multidimensional rectangular domain. Three-dimensional domains are usually discussed, but the material is given in the general form when the number of measurements is at least two. When the values of a quantity at different points are internally independent (which is frequently the case), the corresponding computations are independent as well and can be performed in parallel. However, if there are internal dependences (as, for example, in the Gauss-Seidel method for systems of linear equations), then the order of scanning points of the domain is an important issue. A conventional approach in this case is to form a computation front hyperplane (a usual plane in the three-dimensional case and a line in the two-dimensional case) that moves linearly across the domain at a certain angle. At every step in the course of motion of this hyperplane, its intersection points with the domain can be treated independently and, hence, in parallel, but the steps themselves are executed sequentially. At different steps, the intersection of the hyperplane with the entire domain can have a rather complex geometry and the search for all points of the domain lying on the hyperplane at a given step is a nontrivial problem. This problem (i.e., the computation of the coordinates of points lying in the intersection of the domain with the hyperplane at a given step in the course of hyperplane motion) is addressed below. The computations over the points of the hyperplane can be executed in parallel.
FFT Computation with Systolic Arrays, A New Architecture
NASA Technical Reports Server (NTRS)
Boriakoff, Valentin
1994-01-01
The use of the Cooley-Tukey algorithm for computing the l-d FFT lends itself to a particular matrix factorization which suggests direct implementation by linearly-connected systolic arrays. Here we present a new systolic architecture that embodies this algorithm. This implementation requires a smaller number of processors and a smaller number of memory cells than other recent implementations, as well as having all the advantages of systolic arrays. For the implementation of the decimation-in-frequency case, word-serial data input allows continuous real-time operation without the need of a serial-to-parallel conversion device. No control or data stream switching is necessary. Computer simulation of this architecture was done in the context of a 1024 point DFT with a fixed point processor, and CMOS processor implementation has started.
Algorithms for parallel flow solvers on message passing architectures
NASA Technical Reports Server (NTRS)
Vanderwijngaart, Rob F.
1995-01-01
The purpose of this project has been to identify and test suitable technologies for implementation of fluid flow solvers -- possibly coupled with structures and heat equation solvers -- on MIMD parallel computers. In the course of this investigation much attention has been paid to efficient domain decomposition strategies for ADI-type algorithms. Multi-partitioning derives its efficiency from the assignment of several blocks of grid points to each processor in the parallel computer. A coarse-grain parallelism is obtained, and a near-perfect load balance results. In uni-partitioning every processor receives responsibility for exactly one block of grid points instead of several. This necessitates fine-grain pipelined program execution in order to obtain a reasonable load balance. Although fine-grain parallelism is less desirable on many systems, especially high-latency networks of workstations, uni-partition methods are still in wide use in production codes for flow problems. Consequently, it remains important to achieve good efficiency with this technique that has essentially been superseded by multi-partitioning for parallel ADI-type algorithms. Another reason for the concentration on improving the performance of pipeline methods is their applicability in other types of flow solver kernels with stronger implied data dependence. Analytical expressions can be derived for the size of the dynamic load imbalance incurred in traditional pipelines. From these it can be determined what is the optimal first-processor retardation that leads to the shortest total completion time for the pipeline process. Theoretical predictions of pipeline performance with and without optimization match experimental observations on the iPSC/860 very well. Analysis of pipeline performance also highlights the effect of uncareful grid partitioning in flow solvers that employ pipeline algorithms. If grid blocks at boundaries are not at least as large in the wall-normal direction as those
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.
Hypercluster - Parallel processing for computational mechanics
NASA Technical Reports Server (NTRS)
Blech, Richard A.
1988-01-01
An account is given of the development status, performance capabilities and implications for further development of NASA-Lewis' testbed 'hypercluster' parallel computer network, in which multiple processors communicate through a shared memory. Processors have local as well as shared memory; the hypercluster is expanded in the same manner as the hypercube, with processor clusters replacing the normal single processor node. The NASA-Lewis machine has three nodes with a vector personality and one node with a scalar personality. Each of the vector nodes uses four board-level vector processors, while the scalar node uses four general-purpose microcomputer boards.
Architectures for parallel DSP-based adaptive optics feedback control
NASA Astrophysics Data System (ADS)
McCarthy, Daniel F.
1999-11-01
We have developed a digital image processing system for real-time digital image processing feedback control of adaptive optics systems and simulation of optical image processing algorithms. The system uses multi-computer architecture to capture data from an imaging device such as a charge coupled device camera, process the image data, and control a spatial light-modulator, typically a liquid crystal modulator or a micro-electro mechanical system. The system is a Windows NT Pentium-based system combined with a commercial off-the-shelf peripheral component interconnect bus multi-processor system. The multi-processor is based on the Analog Devices super Harvard architecture computer (SHARC) processor, and field programmable gate arrays (FPGAs). The SHARCs provide a scalable reconfigurable C language-based digital signal processing (DSP) development environment. The FPGAs are typically used as reprogrammable interface controllers designed to integrate several off-the- shelf and custom imagers and light modulators into the system. The FPGAs can also be used in concert with the SHARCs for implementation of application-specific high-speed DSP algorithms.
Evaluation of Visual Computer Simulator for Computer Architecture Education
ERIC Educational Resources Information Center
Imai, Yoshiro; Imai, Masatoshi; Moritoh, Yoshio
2013-01-01
This paper presents trial evaluation of a visual computer simulator in 2009-2011, which has been developed to play some roles of both instruction facility and learning tool simultaneously. And it illustrates an example of Computer Architecture education for University students and usage of e-Learning tool for Assembly Programming in order to…
Iterative algorithms for large sparse linear systems on parallel computers
NASA Technical Reports Server (NTRS)
Adams, L. M.
1982-01-01
Algorithms for assembling in parallel the sparse system of linear equations that result from finite difference or finite element discretizations of elliptic partial differential equations, such as those that arise in structural engineering are developed. Parallel linear stationary iterative algorithms and parallel preconditioned conjugate gradient algorithms are developed for solving these systems. In addition, a model for comparing parallel algorithms on array architectures is developed and results of this model for the algorithms are given.
Bustamam, Alhadi; Burrage, Kevin; Hamilton, Nicholas A
2012-01-01
Markov clustering (MCL) is becoming a key algorithm within bioinformatics for determining clusters in networks. However,with increasing vast amount of data on biological networks, performance and scalability issues are becoming a critical limiting factor in applications. Meanwhile, GPU computing, which uses CUDA tool for implementing a massively parallel computing environment in the GPU card, is becoming a very powerful, efficient, and low-cost option to achieve substantial performance gains over CPU approaches. The use of on-chip memory on the GPU is efficiently lowering the latency time, thus, circumventing a major issue in other parallel computing environments, such as MPI. We introduce a very fast Markov clustering algorithm using CUDA (CUDA-MCL) to perform parallel sparse matrix-matrix computations and parallel sparse Markov matrix normalizations, which are at the heart of MCL. We utilized ELLPACK-R sparse format to allow the effective and fine-grain massively parallel processing to cope with the sparse nature of interaction networks data sets in bioinformatics applications. As the results show, CUDA-MCL is significantly faster than the original MCL running on CPU. Thus, large-scale parallel computation on off-the-shelf desktop-machines, that were previously only possible on supercomputing architectures, can significantly change the way bioinformaticians and biologists deal with their data.
Optimized data communications in a parallel computer
Faraj, Daniel A.
2014-08-19
A parallel computer includes nodes that include a network adapter that couples the node in a point-to-point network and supports communications in opposite directions of each dimension. Optimized communications include: receiving, by a network adapter of a receiving compute node, a packet--from a source direction--that specifies a destination node and deposit hints. Each hint is associated with a direction within which the packet is to be deposited. If a hint indicates the packet to be deposited in the opposite direction: the adapter delivers the packet to an application on the receiving node; forwards the packet to a next node in the opposite direction if the receiving node is not the destination; and forwards the packet to a node in a direction of a subsequent dimension if the hints indicate that the packet is to be deposited in the direction of the subsequent dimension.
Optimized data communications in a parallel computer
Faraj, Daniel A
2014-10-21
A parallel computer includes nodes that include a network adapter that couples the node in a point-to-point network and supports communications in opposite directions of each dimension. Optimized communications include: receiving, by a network adapter of a receiving compute node, a packet--from a source direction--that specifies a destination node and deposit hints. Each hint is associated with a direction within which the packet is to be deposited. If a hint indicates the packet to be deposited in the opposite direction: the adapter delivers the packet to an application on the receiving node; forwards the packet to a next node in the opposite direction if the receiving node is not the destination; and forwards the packet to a node in a direction of a subsequent dimension if the hints indicate that the packet is to be deposited in the direction of the subsequent dimension.
ATCA for Machines-- Advanced Telecommunications Computing Architecture
Larsen, R.S.; /SLAC
2008-04-22
The Advanced Telecommunications Computing Architecture is a new industry open standard for electronics instrument modules and shelves being evaluated for the International Linear Collider (ILC). It is the first industrial standard designed for High Availability (HA). ILC availability simulations have shown clearly that the capabilities of ATCA are needed in order to achieve acceptable integrated luminosity. The ATCA architecture looks attractive for beam instruments and detector applications as well. This paper provides an overview of ongoing R&D including application of HA principles to power electronics systems.
Implementing a computing architecture with WISDOM
Zebrowski, J.R.
1991-01-01
Over the past two years, the Savannah River Site (SRS) work force has expanded by more than 6000 employees. This large influx of personnel, in conjunction with the limited office space, has resulted in an overcrowding problem on site. To alleviate some of the overcrowding, Westinghouse Savannah River Company (WSRC) has been in the process of leasing space from several office buildings within Aiken, SC. Brookhaven, the latest off-site office building to be leased, is the starting point for a new direction in office automation which will eventually spread throughout SRS. The computing architecture in place at Brookhaven was designed to adhere to the SRS computer architecture guidelines as published by the WSRC Computer Architecture Standards Team (CAST). At the heart of the Brookhaven implementation is a Workstation Integration System for DOS, OS/2 and Macintosh (WISDOM). The key features of the WISDOM system include: it's utilization of a Local Area Network (LAN), it's Graphical User Interface (GUI), it's cross-platform capability, it's portable user interface, and the installation program. To begin, I will give an overview of the network architecture, then discuss WISDOM in detail, mention some platform integration problems that need to be addressed and conclude with a summary of the user benefits that WISDOM provides.
Implementing a computing architecture with WISDOM
Zebrowski, J.R.
1991-12-31
Over the past two years, the Savannah River Site (SRS) work force has expanded by more than 6000 employees. This large influx of personnel, in conjunction with the limited office space, has resulted in an overcrowding problem on site. To alleviate some of the overcrowding, Westinghouse Savannah River Company (WSRC) has been in the process of leasing space from several office buildings within Aiken, SC. Brookhaven, the latest off-site office building to be leased, is the starting point for a new direction in office automation which will eventually spread throughout SRS. The computing architecture in place at Brookhaven was designed to adhere to the SRS computer architecture guidelines as published by the WSRC Computer Architecture Standards Team (CAST). At the heart of the Brookhaven implementation is a Workstation Integration System for DOS, OS/2 and Macintosh (WISDOM). The key features of the WISDOM system include: it`s utilization of a Local Area Network (LAN), it`s Graphical User Interface (GUI), it`s cross-platform capability, it`s portable user interface, and the installation program. To begin, I will give an overview of the network architecture, then discuss WISDOM in detail, mention some platform integration problems that need to be addressed and conclude with a summary of the user benefits that WISDOM provides.
Computer graphics in architecture and engineering
NASA Technical Reports Server (NTRS)
Greenberg, D. P.
1975-01-01
The present status of the application of computer graphics to the building profession or architecture and its relationship to other scientific and technical areas were discussed. It was explained that, due to the fragmented nature of architecture and building activities (in contrast to the aerospace industry), a comprehensive, economic utilization of computer graphics in this area is not practical and its true potential cannot now be realized due to the present inability of architects and structural, mechanical, and site engineers to rely on a common data base. Future emphasis will therefore have to be placed on a vertical integration of the construction process and effective use of a three-dimensional data base, rather than on waiting for any technological breakthrough in interactive computing.
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.
Simple, parallel virtual machines for extreme computations
NASA Astrophysics Data System (ADS)
Chokoufe Nejad, Bijan; Ohl, Thorsten; Reuter, Jürgen
2015-11-01
We introduce a virtual machine (VM) written in a numerically fast language like Fortran or C for evaluating very large expressions. We discuss the general concept of how to perform computations in terms of a VM and present specifically a VM that is able to compute tree-level cross sections for any number of external legs, given the corresponding byte-code from the optimal matrix element generator, O'MEGA. Furthermore, this approach allows to formulate the parallel computation of a single phase space point in a simple and obvious way. We analyze hereby the scaling behavior with multiple threads as well as the benefits and drawbacks that are introduced with this method. Our implementation of a VM can run faster than the corresponding native, compiled code for certain processes and compilers, especially for very high multiplicities, and has in general runtimes in the same order of magnitude. By avoiding the tedious compile and link steps, which may fail for source code files of gigabyte sizes, new processes or complex higher order corrections that are currently out of reach could be evaluated with a VM given enough computing power.
A Component Architecture for High-Performance Scientific Computing
Bernholdt, D E; Allan, B A; Armstrong, R; Bertrand, F; Chiu, K; Dahlgren, T L; Damevski, K; Elwasif, W R; Epperly, T W; Govindaraju, M; Katz, D S; Kohl, J A; Krishnan, M; Kumfert, G; Larson, J W; Lefantzi, S; Lewis, M J; Malony, A D; McInnes, L C; Nieplocha, J; Norris, B; Parker, S G; Ray, J; Shende, S; Windus, T L; Zhou, S
2004-12-14
The Common Component Architecture (CCA) provides a means for software developers to manage the complexity of large-scale scientific simulations and to move toward a plug-and-play environment for high-performance computing. In the scientific computing context, component models also promote collaboration using independently developed software, thereby allowing particular individuals or groups to focus on the aspects of greatest interest to them. The CCA supports parallel and distributed computing as well as local high-performance connections between components in a language-independent manner. The design places minimal requirements on components and thus facilitates the integration of existing code into the CCA environment. The CCA model imposes minimal overhead to minimize the impact on application performance. The focus on high performance distinguishes the CCA from most other component models. The CCA is being applied within an increasing range of disciplines, including combustion research, global climate simulation, and computational chemistry.
A Component Architecture for High-Performance Scientific Computing
Bernholdt, David E; Allan, Benjamin A; Armstrong, Robert C; Bertrand, Felipe; Chiu, Kenneth; Dahlgren, Tamara L; Damevski, Kostadin; Elwasif, Wael R; Epperly, Thomas G; Govindaraju, Madhusudhan; Katz, Daniel S; Kohl, James A; Krishnan, Manoj Kumar; Kumfert, Gary K; Larson, J Walter; Lefantzi, Sophia; Lewis, Michael J; Malony, Allen D; McInnes, Lois C; Nieplocha, Jarek; Norris, Boyana; Parker, Steven G; Ray, Jaideep; Shende, Sameer; Windus, Theresa L; Zhou, Shujia
2006-07-03
The Common Component Architecture (CCA) provides a means for software developers to manage the complexity of large-scale scientific simulations and to move toward a plug-and-play environment for high-performance computing. In the scientific computing context, component models also promote collaboration using independently developed software, thereby allowing particular individuals or groups to focus on the aspects of greatest interest to them. The CCA supports parallel and distributed computing as well as local high-performance connections between components in a language-independent manner. The design places minimal requirements on components and thus facilitates the integration of existing code into the CCA environment. The CCA model imposes minimal overhead to minimize the impact on application performance. The focus on high performance distinguishes the CCA from most other component models. The CCA is being applied within an increasing range of disciplines, including combustion research, global climate simulation, and computational chemistry.
OS friendly microprocessor architecture: Hardware level computer security
NASA Astrophysics Data System (ADS)
Jungwirth, Patrick; La Fratta, Patrick
2016-05-01
We present an introduction to the patented OS Friendly Microprocessor Architecture (OSFA) and hardware level computer security. Conventional microprocessors have not tried to balance hardware performance and OS performance at the same time. Conventional microprocessors have depended on the Operating System for computer security and information assurance. The goal of the OS Friendly Architecture is to provide a high performance and secure microprocessor and OS system. We are interested in cyber security, information technology (IT), and SCADA control professionals reviewing the hardware level security features. The OS Friendly Architecture is a switched set of cache memory banks in a pipeline configuration. For light-weight threads, the memory pipeline configuration provides near instantaneous context switching times. The pipelining and parallelism provided by the cache memory pipeline provides for background cache read and write operations while the microprocessor's execution pipeline is running instructions. The cache bank selection controllers provide arbitration to prevent the memory pipeline and microprocessor's execution pipeline from accessing the same cache bank at the same time. This separation allows the cache memory pages to transfer to and from level 1 (L1) caching while the microprocessor pipeline is executing instructions. Computer security operations are implemented in hardware. By extending Unix file permissions bits to each cache memory bank and memory address, the OSFA provides hardware level computer security.
Data Parallel Bin-Based Indexing for Answering Queries on Multi-Core Architectures
Gosink, Luke; Wu, Kesheng; Bethel, E. Wes; Owens, John D.; Joy, Kenneth I.
2009-06-02
The multi-core trend in CPUs and general purpose graphics processing units (GPUs) offers new opportunities for the database community. The increase of cores at exponential rates is likely to affect virtually every server and client in the coming decade, and presents database management systems with a huge, compelling disruption that will radically change how processing is done. This paper presents a new parallel indexing data structure for answering queries that takes full advantage of the increasing thread-level parallelism emerging in multi-core architectures. In our approach, our Data Parallel Bin-based Index Strategy (DP-BIS) first bins the base data, and then partitions and stores the values in each bin as a separate, bin-based data cluster. In answering a query, the procedures for examining the bin numbers and the bin-based data clusters offer the maximum possible level of concurrency; each record is evaluated by a single thread and all threads are processed simultaneously in parallel. We implement and demonstrate the effectiveness of DP-BIS on two multi-core architectures: a multi-core CPU and a GPU. The concurrency afforded by DP-BIS allows us to fully utilize the thread-level parallelism provided by each architecture--for example, our GPU-based DP-BIS implementation simultaneously evaluates over 12,000 records with an equivalent number of concurrently executing threads. In comparing DP-BIS's performance across these architectures, we show that the GPU-based DP-BIS implementation requires significantly less computation time to answer a query than the CPU-based implementation. We also demonstrate in our analysis that DP-BIS provides better overall performance than the commonly utilized CPU and GPU-based projection index. Finally, due to data encoding, we show that DP-BIS accesses significantly smaller amounts of data than index strategies that operate solely on a column's base data; this smaller data footprint is critical for parallel processors that possess
Optimizing transformations of stencil operations for parallel cache-based architectures
Bassetti, F.; Davis, K.
1999-06-28
This paper describes a new technique for optimizing serial and parallel stencil- and stencil-like operations for cache-based architectures. This technique takes advantage of the semantic knowledge implicity in stencil-like computations. The technique is implemented as a source-to-source program transformation; because of its specificity it could not be expected of a conventional compiler. Empirical results demonstrate a uniform factor of two speedup. The experiments clearly show the benefits of this technique to be a consequence, as intended, of the reduction in cache misses. The test codes are based on a 5-point stencil obtained by the discretization of the Poisson equation and applied to a two-dimensional uniform grid using the Jacobi method as an iterative solver. Results are presented for a 1-D tiling for a single processor, and in parallel using 1-D data partition. For the parallel case both blocking and non-blocking communication are tested. The same scheme of experiments has bee n performed for the 2-D tiling case. However, for the parallel case the 2-D partitioning is not discussed here, so the parallel case handled for 2-D is 2-D tiling with 1-D data partitioning.
Parallel eigenanalysis of finite element models in a completely connected architecture
NASA Technical Reports Server (NTRS)
Akl, F. A.; Morel, M. R.
1989-01-01
A parallel algorithm is presented for the solution of the generalized eigenproblem in linear elastic finite element analysis, (K)(phi) = (M)(phi)(omega), where (K) and (M) are of order N, and (omega) is order of q. The concurrent solution of the eigenproblem is based on the multifrontal/modified subspace method and is achieved in a completely connected parallel architecture in which each processor is allowed to communicate with all other processors. The algorithm was successfully implemented on a tightly coupled multiple-instruction multiple-data parallel processing machine, Cray X-MP. A finite element model is divided into m domains each of which is assumed to process n elements. Each domain is then assigned to a processor or to a logical processor (task) if the number of domains exceeds the number of physical processors. The macrotasking library routines are used in mapping each domain to a user task. Computational speed-up and efficiency are used to determine the effectiveness of the algorithm. The effect of the number of domains, the number of degrees-of-freedom located along the global fronts and the dimension of the subspace on the performance of the algorithm are investigated. A parallel finite element dynamic analysis program, p-feda, is documented and the performance of its subroutines in parallel environment is analyzed.
Examining the architecture of cellular computing through a comparative study with a computer.
Wang, Degeng; Gribskov, Michael
2005-06-22
The computer and the cell both use information embedded in simple coding, the binary software code and the quadruple genomic code, respectively, to support system operations. A comparative examination of their system architecture as well as their information storage and utilization schemes is performed. On top of the code, both systems display a modular, multi-layered architecture, which, in the case of a computer, arises from human engineering efforts through a combination of hardware implementation and software abstraction. Using the computer as a reference system, a simplistic mapping of the architectural components between the two is easily detected. This comparison also reveals that a cell abolishes the software-hardware barrier through genomic encoding for the constituents of the biochemical network, a cell's "hardware" equivalent to the computer central processing unit (CPU). The information loading (gene expression) process acts as a major determinant of the encoded constituent's abundance, which, in turn, often determines the "bandwidth" of a biochemical pathway. Cellular processes are implemented in biochemical pathways in parallel manners. In a computer, on the other hand, the software provides only instructions and data for the CPU. A process represents just sequentially ordered actions by the CPU and only virtual parallelism can be implemented through CPU time-sharing. Whereas process management in a computer may simply mean job scheduling, coordinating pathway bandwidth through the gene expression machinery represents a major process management scheme in a cell. In summary, a cell can be viewed as a super-parallel computer, which computes through controlled hardware composition. While we have, at best, a very fragmented understanding of cellular operation, we have a thorough understanding of the computer throughout the engineering process. The potential utilization of this knowledge to the benefit of systems biology is discussed.
A Testbed of Parallel Kernels for Computer Science Research
Bailey, David; Demmel, James; Ibrahim, Khaled; Kaiser, Alex; Koniges, Alice; Madduri, Kamesh; Shalf, John; Strohmaier, Erich; Williams, Samuel
2010-04-30
For several decades, computer scientists have sought guidance on how to evolve architectures, languages, and programming models for optimal performance, efficiency, and productivity. Unfortunately, this guidance is most often taken from the existing software/hardware ecosystem. Architects attempt to provide micro-architectural solutions to improve performance on fixed binaries. Researchers tweak compilers to improve code generation for existing architectures and implementations, and they may invent new programming models for fixed processor and memory architectures and computational algorithms. In today's rapidly evolving world of on-chip parallelism, these isolated and iterative improvements to performance may miss superior solutions in the same way gradient descent optimization techniques may get stuck in local minima. In an initial study, we have developed an alternate approach that, rather than starting with an existing hardware/software solution laced with hidden assumptions, defines the computational problems of interest and invites architects, researchers and programmers to implement novel hardware/ software co-designed solutions. Our work builds on the previous ideas of computational dwarfs, motifs, and parallel patterns by selecting a representative set of essential problems for which we provide: An algorithmic description; scalable problem definition; illustrative reference implementations; verification schemes. For simplicity, we focus initially on the computational problems of interest to the scientific computing community but proclaim the methodology (and perhaps a subset of the problems) as applicable to other communities. We intend to broaden the coverage of this problem space through stronger community involvement. Previous work has established a broad categorization of numerical methods of interest to the scientific computing, in the spirit of the NAS Benchmarks, which pioneered the basic idea of a 'pencil and paper benchmark' in the 1990s. The
QCMPI: A parallel environment for quantum computing
NASA Astrophysics Data System (ADS)
Tabakin, Frank; Juliá-Díaz, Bruno
2009-06-01
QCMPI is a quantum computer (QC) simulation package written in Fortran 90 with parallel processing capabilities. It is an accessible research tool that permits rapid evaluation of quantum algorithms for a large number of qubits and for various "noise" scenarios. The prime motivation for developing QCMPI is to facilitate numerical examination of not only how QC algorithms work, but also to include noise, decoherence, and attenuation effects and to evaluate the efficacy of error correction schemes. The present work builds on an earlier Mathematica code QDENSITY, which is mainly a pedagogic tool. In that earlier work, although the density matrix formulation was featured, the description using state vectors was also provided. In QCMPI, the stress is on state vectors, in order to employ a large number of qubits. The parallel processing feature is implemented by using the Message-Passing Interface (MPI) protocol. A description of how to spread the wave function components over many processors is provided, along with how to efficiently describe the action of general one- and two-qubit operators on these state vectors. These operators include the standard Pauli, Hadamard, CNOT and CPHASE gates and also Quantum Fourier transformation. These operators make up the actions needed in QC. Codes for Grover's search and Shor's factoring algorithms are provided as examples. A major feature of this work is that concurrent versions of the algorithms can be evaluated with each version subject to alternate noise effects, which corresponds to the idea of solving a stochastic Schrödinger equation. The density matrix for the ensemble of such noise cases is constructed using parallel distribution methods to evaluate its eigenvalues and associated entropy. Potential applications of this powerful tool include studies of the stability and correction of QC processes using Hamiltonian based dynamics. Program summaryProgram title: QCMPI Catalogue identifier: AECS_v1_0 Program summary URL
Integration of nanoscale memristor synapses in neuromorphic computing architectures.
Indiveri, Giacomo; Linares-Barranco, Bernabé; Legenstein, Robert; Deligeorgis, George; Prodromakis, Themistoklis
2013-09-27
Conventional neuro-computing architectures and artificial neural networks have often been developed with no or loose connections to neuroscience. As a consequence, they have largely ignored key features of biological neural processing systems, such as their extremely low-power consumption features or their ability to carry out robust and efficient computation using massively parallel arrays of limited precision, highly variable, and unreliable components. Recent developments in nano-technologies are making available extremely compact and low power, but also variable and unreliable solid-state devices that can potentially extend the offerings of availing CMOS technologies. In particular, memristors are regarded as a promising solution for modeling key features of biological synapses due to their nanoscale dimensions, their capacity to store multiple bits of information per element and the low energy required to write distinct states. In this paper, we first review the neuro- and neuromorphic computing approaches that can best exploit the properties of memristor and scale devices, and then propose a novel hybrid memristor-CMOS neuromorphic circuit which represents a radical departure from conventional neuro-computing approaches, as it uses memristors to directly emulate the biophysics and temporal dynamics of real synapses. We point out the differences between the use of memristors in conventional neuro-computing architectures and the hybrid memristor-CMOS circuit proposed, and argue how this circuit represents an ideal building block for implementing brain-inspired probabilistic computing paradigms that are robust to variability and fault tolerant by design.
Integration of nanoscale memristor synapses in neuromorphic computing architectures
NASA Astrophysics Data System (ADS)
Indiveri, Giacomo; Linares-Barranco, Bernabé; Legenstein, Robert; Deligeorgis, George; Prodromakis, Themistoklis
2013-09-01
Conventional neuro-computing architectures and artificial neural networks have often been developed with no or loose connections to neuroscience. As a consequence, they have largely ignored key features of biological neural processing systems, such as their extremely low-power consumption features or their ability to carry out robust and efficient computation using massively parallel arrays of limited precision, highly variable, and unreliable components. Recent developments in nano-technologies are making available extremely compact and low power, but also variable and unreliable solid-state devices that can potentially extend the offerings of availing CMOS technologies. In particular, memristors are regarded as a promising solution for modeling key features of biological synapses due to their nanoscale dimensions, their capacity to store multiple bits of information per element and the low energy required to write distinct states. In this paper, we first review the neuro- and neuromorphic computing approaches that can best exploit the properties of memristor and scale devices, and then propose a novel hybrid memristor-CMOS neuromorphic circuit which represents a radical departure from conventional neuro-computing approaches, as it uses memristors to directly emulate the biophysics and temporal dynamics of real synapses. We point out the differences between the use of memristors in conventional neuro-computing architectures and the hybrid memristor-CMOS circuit proposed, and argue how this circuit represents an ideal building block for implementing brain-inspired probabilistic computing paradigms that are robust to variability and fault tolerant by design.
Problems Related to Parallelization of CFD Algorithms on GPU, Multi-GPU and Hybrid Architectures
NASA Astrophysics Data System (ADS)
Biazewicz, Marek; Kurowski, Krzysztof; Ludwiczak, Bogdan; Napieraia, Krystyna
2010-09-01
Computational Fluid Dynamics (CFD) is one of the branches of fluid mechanics, which uses numerical methods and algorithms to solve and analyze fluid flows. CFD is used in various domains, such as oil and gas reservoir uncertainty analysis, aerodynamic body shapes optimization (e.g. planes, cars, ships, sport helmets, skis), natural phenomena analysis, numerical simulation for weather forecasting or realistic visualizations. CFD problem is very complex and needs a lot of computational power to obtain the results in a reasonable time. We have implemented a parallel application for two-dimensional CFD simulation with a free surface approximation (MAC method) using new hardware architectures, in particular multi-GPU and hybrid computing environments. For this purpose we decided to use NVIDIA graphic cards with CUDA environment due to its simplicity of programming and good computations performance. We used finite difference discretization of Navier-Stokes equations, where fluid is propagated over an Eulerian Grid. In this model, the behavior of the fluid inside the cell depends only on the properties of local, surrounding cells, therefore it is well suited for the GPU-based architecture. In this paper we demonstrate how to use efficiently the computing power of GPUs for CFD. Additionally, we present some best practices to help users analyze and improve the performance of CFD applications executed on GPU. Finally, we discuss various challenges around the multi-GPU implementation on the example of matrix multiplication.
Parallel computing for simultaneous iterative tomographic imaging by graphics processing units
NASA Astrophysics Data System (ADS)
Bello-Maldonado, Pedro D.; López, Ricardo; Rogers, Colleen; Jin, Yuanwei; Lu, Enyue
2016-05-01
In this paper, we address the problem of accelerating inversion algorithms for nonlinear acoustic tomographic imaging by parallel computing on graphics processing units (GPUs). Nonlinear inversion algorithms for tomographic imaging often rely on iterative algorithms for solving an inverse problem, thus computationally intensive. We study the simultaneous iterative reconstruction technique (SIRT) for the multiple-input-multiple-output (MIMO) tomography algorithm which enables parallel computations of the grid points as well as the parallel execution of multiple source excitation. Using graphics processing units (GPUs) and the Compute Unified Device Architecture (CUDA) programming model an overall improvement of 26.33x was achieved when combining both approaches compared with sequential algorithms. Furthermore we propose an adaptive iterative relaxation factor and the use of non-uniform weights to improve the overall convergence of the algorithm. Using these techniques, fast computations can be performed in parallel without the loss of image quality during the reconstruction process.
Algorithms versus architectures for computational chemistry
NASA Technical Reports Server (NTRS)
Partridge, H.; Bauschlicher, C. W., Jr.
1986-01-01
The algorithms employed are computationally intensive and, as a result, increased performance (both algorithmic and architectural) is required to improve accuracy and to treat larger molecular systems. Several benchmark quantum chemistry codes are examined on a variety of architectures. While these codes are only a small portion of a typical quantum chemistry library, they illustrate many of the computationally intensive kernels and data manipulation requirements of some applications. Furthermore, understanding the performance of the existing algorithm on present and proposed supercomputers serves as a guide for future programs and algorithm development. The algorithms investigated are: (1) a sparse symmetric matrix vector product; (2) a four index integral transformation; and (3) the calculation of diatomic two electron Slater integrals. The vectorization strategies are examined for these algorithms for both the Cyber 205 and Cray XMP. In addition, multiprocessor implementations of the algorithms are looked at on the Cray XMP and on the MIT static data flow machine proposed by DENNIS.
Roadmap to the SRS computing architecture
Johnson, A.
1994-07-05
This document outlines the major steps that must be taken by the Savannah River Site (SRS) to migrate the SRS information technology (IT) environment to the new architecture described in the Savannah River Site Computing Architecture. This document proposes an IT environment that is {open_quotes}...standards-based, data-driven, and workstation-oriented, with larger systems being utilized for the delivery of needed information to users in a client-server relationship.{close_quotes} Achieving this vision will require many substantial changes in the computing applications, systems, and supporting infrastructure at the site. This document consists of a set of roadmaps which provide explanations of the necessary changes for IT at the site and describes the milestones that must be completed to finish the migration.
Broadcasting a message in a parallel computer
Archer, Charles J; Faraj, Daniel A
2014-11-18
Methods, systems, and products are disclosed for broadcasting a message in a parallel computer that includes: transmitting, by the logical root to all of the nodes directly connected to the logical root, a message; and for each node except the logical root: receiving the message; if that node is the physical root, then transmitting the message to all of the child nodes except the child node from which the message was received; if that node received the message from a parent node and if that node is not a leaf node, then transmitting the message to all of the child nodes; and if that node received the message from a child node and if that node is not the physical root, then transmitting the message to all of the child nodes except the child node from which the message was received and transmitting the message to the parent node.
Broadcasting a message in a parallel computer
Archer, Charles J; Faraj, Ahmad A
2013-04-16
Methods, systems, and products are disclosed for broadcasting a message in a parallel computer that includes: transmitting, by the logical root to all of the nodes directly connected to the logical root, a message; and for each node except the logical root: receiving the message; if that node is the physical root, then transmitting the message to all of the child nodes except the child node from which the message was received; if that node received the message from a parent node and if that node is not a leaf node, then transmitting the message to all of the child nodes; and if that node received the message from a child node and if that node is not the physical root, then transmitting the message to all of the child nodes except the child node from which the message was received and transmitting the message to the parent node.
Broadcasting collective operation contributions throughout a parallel computer
Faraj, Ahmad [Rochester, MN
2012-02-21
Methods, systems, and products are disclosed for broadcasting collective operation contributions throughout a parallel computer. The parallel computer includes a plurality of compute nodes connected together through a data communications network. Each compute node has a plurality of processors for use in collective parallel operations on the parallel computer. Broadcasting collective operation contributions throughout a parallel computer according to embodiments of the present invention includes: transmitting, by each processor on each compute node, that processor's collective operation contribution to the other processors on that compute node using intra-node communications; and transmitting on a designated network link, by each processor on each compute node according to a serial processor transmission sequence, that processor's collective operation contribution to the other processors on the other compute nodes using inter-node communications.
Novel Highly Parallel and Systolic Architectures Using Quantum Dot-Based Hardware
NASA Technical Reports Server (NTRS)
Fijany, Amir; Toomarian, Benny N.; Spotnitz, Matthew
1997-01-01
VLSI technology has made possible the integration of massive number of components (processors, memory, etc.) into a single chip. In VLSI design, memory and processing power are relatively cheap and the main emphasis of the design is on reducing the overall interconnection complexity since data routing costs dominate the power, time, and area required to implement a computation. Communication is costly because wires occupy the most space on a circuit and it can also degrade clock time. In fact, much of the complexity (and hence the cost) of VLSI design results from minimization of data routing. The main difficulty in VLSI routing is due to the fact that crossing of the lines carrying data, instruction, control, etc. is not possible in a plane. Thus, in order to meet this constraint, the VLSI design aims at keeping the architecture highly regular with local and short interconnection. As a result, while the high level of integration has opened the way for massively parallel computation, practical and full exploitation of such a capability in many applications of interest has been hindered by the constraints on interconnection pattern. More precisely. the use of only localized communication significantly simplifies the design of interconnection architecture but at the expense of somewhat restricted class of applications. For example, there are currently commercially available products integrating; hundreds of simple processor elements within a single chip. However, the lack of adequate interconnection pattern among these processing elements make them inefficient for exploiting a large degree of parallelism in many applications.
Architectural requirements for the Red Storm computing system.
Camp, William J.; Tomkins, James Lee
2003-10-01
This report is based on the Statement of Work (SOW) describing the various requirements for delivering 3 new supercomputer system to Sandia National Laboratories (Sandia) as part of the Department of Energy's (DOE) Accelerated Strategic Computing Initiative (ASCI) program. This system is named Red Storm and will be a distributed memory, massively parallel processor (MPP) machine built primarily out of commodity parts. The requirements presented here distill extensive architectural and design experience accumulated over a decade and a half of research, development and production operation of similar machines at Sandia. Red Storm will have an unusually high bandwidth, low latency interconnect, specially designed hardware and software reliability features, a light weight kernel compute node operating system and the ability to rapidly switch major sections of the machine between classified and unclassified computing environments. Particular attention has been paid to architectural balance in the design of Red Storm, and it is therefore expected to achieve an atypically high fraction of its peak speed of 41 TeraOPS on real scientific computing applications. In addition, Red Storm is designed to be upgradeable to many times this initial peak capability while still retaining appropriate balance in key design dimensions. Installation of the Red Storm computer system at Sandia's New Mexico site is planned for 2004, and it is expected that the system will be operated for a minimum of five years following installation.
Parallel CE/SE Computations via Domain Decomposition
NASA Technical Reports Server (NTRS)
Himansu, Ananda; Jorgenson, Philip C. E.; Wang, Xiao-Yen; Chang, Sin-Chung
2000-01-01
This paper describes the parallelization strategy and achieved parallel efficiency of an explicit time-marching algorithm for solving conservation laws. The Space-Time Conservation Element and Solution Element (CE/SE) algorithm for solving the 2D and 3D Euler equations is parallelized with the aid of domain decomposition. The parallel efficiency of the resultant algorithm on a Silicon Graphics Origin 2000 parallel computer is checked.
Joubert, W.; Carey, G.F.
1994-12-31
A great need exists for high performance numerical software libraries transportable across parallel machines. This talk concerns the PCG package, which solves systems of linear equations by iterative methods on parallel computers. The features of the package are discussed, as well as techniques used to obtain high performance as well as transportability across architectures. Representative numerical results are presented for several machines including the Connection Machine CM-5, Intel Paragon and Cray T3D parallel computers.
Architecture of the parallel hierarchical network for fast image recognition
NASA Astrophysics Data System (ADS)
Timchenko, Leonid; Wójcik, Waldemar; Kokriatskaia, Natalia; Kutaev, Yuriy; Ivasyuk, Igor; Kotyra, Andrzej; Smailova, Saule
2016-09-01
Multistage integration of visual information in the brain allows humans to respond quickly to most significant stimuli while maintaining their ability to recognize small details in the image. Implementation of this principle in technical systems can lead to more efficient processing procedures. The multistage approach to image processing includes main types of cortical multistage convergence. The input images are mapped into a flexible hierarchy that reflects complexity of image data. Procedures of the temporal image decomposition and hierarchy formation are described in mathematical expressions. The multistage system highlights spatial regularities, which are passed through a number of transformational levels to generate a coded representation of the image that encapsulates a structure on different hierarchical levels in the image. At each processing stage a single output result is computed to allow a quick response of the system. The result is presented as an activity pattern, which can be compared with previously computed patterns on the basis of the closest match. With regard to the forecasting method, its idea lies in the following. In the results synchronization block, network-processed data arrive to the database where a sample of most correlated data is drawn using service parameters of the parallel-hierarchical network.
Aerodynamic optimization studies on advanced architecture computers
NASA Technical Reports Server (NTRS)
Chawla, Kalpana
1995-01-01
The approach to carrying out multi-discipline aerospace design studies in the future, especially in massively parallel computing environments, comprises of choosing (1) suitable solvers to compute solutions to equations characterizing a discipline, and (2) efficient optimization methods. In addition, for aerodynamic optimization problems, (3) smart methodologies must be selected to modify the surface shape. In this research effort, a 'direct' optimization method is implemented on the Cray C-90 to improve aerodynamic design. It is coupled with an existing implicit Navier-Stokes solver, OVERFLOW, to compute flow solutions. The optimization method is chosen such that it can accomodate multi-discipline optimization in future computations. In the work , however, only single discipline aerodynamic optimization will be included.
Grigoryeva, Lyudmila; Henriques, Julie; Larger, Laurent; Ortega, Juan-Pablo
2016-07-01
This letter addresses the reservoir design problem in the context of delay-based reservoir computers for multidimensional input signals, parallel architectures, and real-time multitasking. First, an approximating reservoir model is presented in those frameworks that provides an explicit functional link between the reservoir architecture and its performance in the execution of a specific task. Second, the inference properties of the ridge regression estimator in the multivariate context are used to assess the impact of finite sample training on the decrease of the reservoir capacity. Finally, an empirical study is conducted that shows the adequacy of the theoretical results with the empirical performances exhibited by various reservoir architectures in the execution of several nonlinear tasks with multidimensional inputs. Our results confirm the robustness properties of the parallel reservoir architecture with respect to task misspecification and parameter choice already documented in the literature.
CFD Optimization on Network-Based Parallel Computer System
NASA Technical Reports Server (NTRS)
Cheung, Samson H.; Holst, Terry L. (Technical Monitor)
1994-01-01
Combining multiple engineering workstations into a network-based heterogeneous parallel computer allows application of aerodynamic optimization with advance computational fluid dynamics codes, which is computationally expensive in mainframe supercomputer. This paper introduces a nonlinear quasi-Newton optimizer designed for this network-based heterogeneous parallel computer on a software called Parallel Virtual Machine. This paper will introduce the methodology behind coupling a Parabolized Navier-Stokes flow solver to the nonlinear optimizer. This parallel optimization package has been applied to reduce the wave drag of a body of revolution and a wing/body configuration with results of 5% to 6% drag reduction.
Parallel CFD design on network-based computer
NASA Technical Reports Server (NTRS)
Cheung, Samson
1995-01-01
Combining multiple engineering workstations into a network-based heterogeneous parallel computer allows application of aerodynamic optimization with advanced computational fluid dynamics codes, which can be computationally expensive on mainframe supercomputers. This paper introduces a nonlinear quasi-Newton optimizer designed for this network-based heterogeneous parallel computing environment utilizing a software called Parallel Virtual Machine. This paper will introduce the methodology behind coupling a Parabolized Navier-Stokes flow solver to the nonlinear optimizer. This parallel optimization package is applied to reduce the wave drag of a body of revolution and a wing/body configuration with results of 5% to 6% drag reduction.
Real-time synthetic aperture sonar imaging using a parallel architecture.
Riyait, V S; Lawlor, M A; Adams, A E; Hinton, O; Sharif, B
1995-01-01
This paper describes a parallel architecture that has been developed to perform real-time synthetic aperture sonar imaging as part of the Acoustical Imaging Development (ACID) project. The project has successfully developed a synthetic aperture sonar system for producing high resolution images of the sea floor and that has been tested during a series of sea trials in May 1993 off the south coast of France. This paper describes the synthetic aperture processing system developed by the University of Newcastle upon Tyne and its use of transputer modules and associated devices in order to obtain real-time imaging performance, the software structure of the processing system and the load balancing techniques that have been developed in order to provide efficient processing. The use of a parallel distributed architecture has also allowed a processing system that can readily be extended to deliver greater computational power in the future. Images produced by the synthetic aperture processor from data collected from around the Toulon coastal region are presented. These images highlight the improvement in azimuth resolution that can be obtained from synthetic aperture processing over conventional sidescan sonars.
Review of An Introduction to Parallel and Vector Scientific Computing
Bailey, David H.; Lefton, Lew
2006-06-30
the publication of the book An Introduction to Parallel and Vector Scientic Computing, written by Ronald W. Shonkwiler and Lew Lefton, both of the Georgia Institute of Technology. They have taken the bull by the horns and produced a book that appears to be entirely satisfactory as an introductory textbook for use in such a course. It is also of interest to the much broader community of researchers who are already in the field, laboring day by day to improve the power and performance of their numerical simulations. The book is organized into 11 chapters, plus an appendix. The first three chapters describe the basics of system architecture including vector, parallel and distributed memory systems, the details of task dependence and synchronization, and the various programming models currently in use - threads, MPI and OpenMP. Chapters four through nine provide a competent introduction to floating-point arithmetic, numerical error and numerical linear algebra. Some of the topics presented include Gaussian elimination, LU decomposition, tridiagonal systems, Givens rotations, QR decompositions, Gauss-Seidel iterations and Householder transformations. Chapters 10 and 11 introduce Monte Carlo methods and schemes for discrete optimization such as genetic algorithms.
Developing a Distributed Computing Architecture at Arizona State University.
ERIC Educational Resources Information Center
Armann, Neil; And Others
1994-01-01
Development of Arizona State University's computing architecture, designed to ensure that all new distributed computing pieces will work together, is described. Aspects discussed include the business rationale, the general architectural approach, characteristics and objectives of the architecture, specific services, and impact on the university…
Frances: A Tool for Understanding Computer Architecture and Assembly Language
ERIC Educational Resources Information Center
Sondag, Tyler; Pokorny, Kian L.; Rajan, Hridesh
2012-01-01
Students in all areas of computing require knowledge of the computing device including software implementation at the machine level. Several courses in computer science curricula address these low-level details such as computer architecture and assembly languages. For such courses, there are advantages to studying real architectures instead of…
Yokohama, Noriya
2013-07-01
This report was aimed at structuring the design of architectures and studying performance measurement of a parallel computing environment using a Monte Carlo simulation for particle therapy using a high performance computing (HPC) instance within a public cloud-computing infrastructure. Performance measurements showed an approximately 28 times faster speed than seen with single-thread architecture, combined with improved stability. A study of methods of optimizing the system operations also indicated lower cost.
Performance Evaluation in Network-Based Parallel Computing
NASA Technical Reports Server (NTRS)
Dezhgosha, Kamyar
1996-01-01
Network-based parallel computing is emerging as a cost-effective alternative for solving many problems which require use of supercomputers or massively parallel computers. The primary objective of this project has been to conduct experimental research on performance evaluation for clustered parallel computing. First, a testbed was established by augmenting our existing SUNSPARCs' network with PVM (Parallel Virtual Machine) which is a software system for linking clusters of machines. Second, a set of three basic applications were selected. The applications consist of a parallel search, a parallel sort, a parallel matrix multiplication. These application programs were implemented in C programming language under PVM. Third, we conducted performance evaluation under various configurations and problem sizes. Alternative parallel computing models and workload allocations for application programs were explored. The performance metric was limited to elapsed time or response time which in the context of parallel computing can be expressed in terms of speedup. The results reveal that the overhead of communication latency between processes in many cases is the restricting factor to performance. That is, coarse-grain parallelism which requires less frequent communication between processes will result in higher performance in network-based computing. Finally, we are in the final stages of installing an Asynchronous Transfer Mode (ATM) switch and four ATM interfaces (each 155 Mbps) which will allow us to extend our study to newer applications, performance metrics, and configurations.
Monte Carlo simulations on SIMD computer architectures. [Single instruction multiple data (SIMD)
Burmester, C.P.; Gronsky, R. ); Wille, L.T. . Dept. of Physics)
1992-03-01
Algorithmic considerations regarding the implementation of various materials science applications of the Monte Carlo technique to single instruction multiple data (SMM) computer architectures are presented. In particular, implementation of the Ising model with nearest, next nearest, and long range screened Coulomb interactions on the SIMD architecture MasPar MP-1 (DEC mpp-12000) series of massively parallel computers is demonstrated. Methods of code development which optimize processor array use and minimize inter-processor communication are presented including lattice partitioning and the use of processor array spanning tree structures for data reduction. Both geometric and algorithmic parallel approaches are utilized. Benchmarks in terms of Monte Carlo updates per second for the MasPar architecture are presented and compared to values reported in the literature from comparable studies on other architectures.
Computing Architecture for the ngVLA
NASA Astrophysics Data System (ADS)
Kern, Jeffrey S.; Glendenning, Brian; Hiriart, R.
2017-01-01
Computing challenges for the Next Generation Very Large Array (ngVLA) are not always the ones that first come to mind. Current design concepts have visibility data rates which allow the permanent storage of the raw visibility data, and although challenging, the calibration and imaging processing for the ngVLA is not beyond the capabilities of existing systems (let alone those that will exist when ngVLA construction is completed). Design goals include a system that supports a wide range of PI-driven projects, end to end data management, and the production of science ready data products. This should be accomplished while minimizing the operating costs of an array consisting of hundreds of elements distributed over an area of nearly 100,000 km2. We discuss a proposed architecture of the computing system, design constraints for a detailed design, and some possible design choices and their implications.
Quantum computation architecture using optical tweezers
Weitenberg, Christof; Kuhr, Stefan; Moelmer, Klaus; Sherson, Jacob F.
2011-09-15
We present a complete architecture for scalable quantum computation with ultracold atoms in optical lattices using optical tweezers focused to the size of a lattice spacing. We discuss three different two-qubit gates based on local collisional interactions. The gates between arbitrary qubits require the transport of atoms to neighboring sites. We numerically optimize the nonadiabatic transport of the atoms through the lattice and the intensity ramps of the optical tweezer in order to maximize the gate fidelities. We find overall gate times of a few 100 {mu}s, while keeping the error probability due to vibrational excitations and spontaneous scattering below 10{sup -3}. The requirements on the positioning error and intensity noise of the optical tweezer and the magnetic field stability are analyzed and we show that atoms in optical lattices could meet the requirements for fault-tolerant scalable quantum computing.
Data communications in a parallel active messaging interface of a parallel computer
Archer, Charles J; Blocksome, Michael A; Ratterman, Joseph D; Smith, Brian E
2013-11-12
Data communications in a parallel active messaging interface (`PAMI`) of a parallel computer composed of compute nodes that execute a parallel application, each compute node including application processors that execute the parallel application and at least one management processor dedicated to gathering information regarding data communications. The PAMI is composed of data communications endpoints, each endpoint composed of a specification of data communications parameters for a thread of execution on a compute node, including specifications of a client, a context, and a task, the compute nodes and the endpoints coupled for data communications through the PAMI and through data communications resources. Embodiments function by gathering call site statistics describing data communications resulting from execution of data communications instructions and identifying in dependence upon the call cite statistics a data communications algorithm for use in executing a data communications instruction at a call site in the parallel application.
Architectural Adaptability in Parallel Programming via Control Abstraction
1991-01-01
Technical Report 359 January 1991 Abstract Parallel programming involves finding the potential parallelism in an application, choos - ing an...during the development of this paper. 34 References [Albert et ai, 1988] Eugene Albert, Kathleen Knobe, Joan D. Lukas, and Guy L. Steele, Jr
Woodruff, S.B.
1992-01-01
The Transient Reactor Analysis Code (TRAC), which features a two- fluid treatment of thermal-hydraulics, is designed to model transients in water reactors and related facilities. One of the major computational costs associated with TRAC and similar codes is calculating constitutive coefficients. Although the formulations for these coefficients are local the costs are flow-regime- or data-dependent; i.e., the computations needed for a given spatial node often vary widely as a function of time. Consequently, poor load balancing will degrade efficiency on either vector or data parallel architectures when the data are organized according to spatial location. Unfortunately, a general automatic solution to the load-balancing problem associated with data-dependent computations is not yet available for massively parallel architectures. This document discusses why developers algorithms, such as a neural net representation, that do not exhibit algorithms, such as a neural net representation, that do not exhibit load-balancing problems.
Advances in Domain Mapping of Massively Parallel Scientific Computations
Leland, Robert W.; Hendrickson, Bruce A.
2015-10-01
One of the most important concerns in parallel computing is the proper distribution of workload across processors. For most scientific applications on massively parallel machines, the best approach to this distribution is to employ data parallelism; that is, to break the datastructures supporting a computation into pieces and then to assign those pieces to different processors. Collectively, these partitioning and assignment tasks comprise the domain mapping problem.
Access and visualization using clusters and other parallel computers
NASA Technical Reports Server (NTRS)
Katz, D. S.; Bergou, A.; Berriman, B.; Block, G.; Collier, J.; Curkendall, D.; Good, J.; Husman, L.; Jacob, J.; Laity, A.; Li, P.; Miller, C.; Plesea, L.; Prince, T.; Siegel, H.; Williams, R.
2003-01-01
JPL's Parallel Applications Technologies Group has been exploring the issues of data access and visualization of very large data sets over the past 10 years. this work has used a number of types of parallel computers, and today includes the use of commodity clusters. This talk will highlight some of the applications and tools we have developed, including how they use parallel computing resources, and specifically how we are using modern clusters.
Reverse Computation for Rollback-based Fault Tolerance in Large Parallel Systems
Perumalla, Kalyan S; Park, Alfred J
2013-01-01
Reverse computation is presented here as an important future direction in addressing the challenge of fault tolerant execution on very large cluster platforms for parallel computing. As the scale of parallel jobs increases, traditional checkpointing approaches suffer scalability problems ranging from computational slowdowns to high congestion at the persistent stores for checkpoints. Reverse computation can overcome such problems and is also better suited for parallel computing on newer architectures with smaller, cheaper or energy-efficient memories and file systems. Initial evidence for the feasibility of reverse computation in large systems is presented with detailed performance data from a particle simulation scaling to 65,536 processor cores and 950 accelerators (GPUs). Reverse computation is observed to deliver very large gains relative to checkpointing schemes when nodes rely on their host processors/memory to tolerate faults at their accelerators. A comparison between reverse computation and checkpointing with measurements such as cache miss ratios, TLB misses and memory usage indicates that reverse computation is hard to ignore as a future alternative to be pursued in emerging architectures.
Center for Programming Models for Scalable Parallel Computing: Future Programming Models
Gao, Guang, R.
2008-07-24
The mission of the pmodel center project is to develop software technology to support scalable parallel programming models for terascale systems. The goal of the specific UD subproject is in the context developing an efficient and robust methodology and tools for HPC programming. More specifically, the focus is on developing new programming models which facilitate programmers in porting their application onto parallel high performance computing systems. During the course of the research in the past 5 years, the landscape of microprocessor chip architecture has witnessed a fundamental change – the emergence of multi-core/many-core chip architecture appear to become the mainstream technology and will have a major impact to for future generation parallel machines. The programming model for shared-address space machines is becoming critical to such multi-core architectures. Our research highlight is the in-depth study of proposed fine-grain parallelism/multithreading support on such future generation multi-core architectures. Our research has demonstrated the significant impact such fine-grain multithreading model can have on the productivity of parallel programming models and their efficient implementation.
The Design and Evaluation of "CAPTools"--A Computer Aided Parallelization Toolkit
NASA Technical Reports Server (NTRS)
Yan, Jerry; Frumkin, Michael; Hribar, Michelle; Jin, Haoqiang; Waheed, Abdul; Johnson, Steve; Cross, Jark; Evans, Emyr; Ierotheou, Constantinos; Leggett, Pete; Saini, Subhash (Technical Monitor)
1998-01-01
Writing applications for high performance computers is a challenging task. Although writing code by hand still offers the best performance, it is extremely costly and often not very portable. The Computer Aided Parallelization Tools (CAPTools) are a toolkit designed to help automate the mapping of sequential FORTRAN scientific applications onto multiprocessors. CAPTools consists of the following major components: an inter-procedural dependence analysis module that incorporates user knowledge; a 'self-propagating' data partitioning module driven via user guidance; an execution control mask generation and optimization module for the user to fine tune parallel processing of individual partitions; a program transformation/restructuring facility for source code clean up and optimization; a set of browsers through which the user interacts with CAPTools at each stage of the parallelization process; and a code generator supporting multiple programming paradigms on various multiprocessors. Besides describing the rationale behind the architecture of CAPTools, the parallelization process is illustrated via case studies involving structured and unstructured meshes. The programming process and the performance of the generated parallel programs are compared against other programming alternatives based on the NAS Parallel Benchmarks, ARC3D and other scientific applications. Based on these results, a discussion on the feasibility of constructing architectural independent parallel applications is presented.
On combining computational differentiation and toolkits for parallel scientific computing.
Bischof, C. H.; Buecker, H. M.; Hovland, P. D.
2000-06-08
Automatic differentiation is a powerful technique for evaluating derivatives of functions given in the form of a high-level programming language such as Fortran, C, or C++. The program is treated as a potentially very long sequence of elementary statements to which the chain rule of differential calculus is applied over and over again. Combining automatic differentiation and the organizational structure of toolkits for parallel scientific computing provides a mechanism for evaluating derivatives by exploiting mathematical insight on a higher level. In these toolkits, algorithmic structures such as BLAS-like operations, linear and nonlinear solvers, or integrators for ordinary differential equations can be identified by their standardized interfaces and recognized as high-level mathematical objects rather than as a sequence of elementary statements. In this note, the differentiation of a linear solver with respect to some parameter vector is taken as an example. Mathematical insight is used to reformulate this problem into the solution of multiple linear systems that share the same coefficient matrix but differ in their right-hand sides. The experiments reported here use ADIC, a tool for the automatic differentiation of C programs, and PETSC, an object-oriented toolkit for the parallel solution of scientific problems modeled by partial differential equations.
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.
Modern hardware architectures accelerate porous media flow computations
NASA Astrophysics Data System (ADS)
Kulczewski, Michal; Kurowski, Krzysztof; Kierzynka, Michal; Dohnalik, Marek; Kaczmarczyk, Jan; Borujeni, Ali Takbiri
2012-05-01
Investigation of rock properties, porosity and permeability particularly, which determines transport media characteristic, is crucial to reservoir engineering. Nowadays, micro-tomography (micro-CT) methods allow to obtain vast of petro-physical properties. The micro-CT method facilitates visualization of pores structures and acquisition of total porosity factor, determined by sticking together 2D slices of scanned rock and applying proper absorption cut-off point. Proper segmentation of pores representation in 3D is important to solve the permeability of porous media. This factor is recently determined by the means of Computational Fluid Dynamics (CFD), a popular method to analyze problems related to fluid flows, taking advantage of numerical methods and constantly growing computing powers. The recent advent of novel multi-, many-core and graphics processing unit (GPU) hardware architectures allows scientists to benefit even more from parallel processing and built-in new features. The high level of parallel scalability offers both, the time-to-solution decrease and greater accuracy - top factors in reservoir engineering. This paper aims to present research results related to fluid flow simulations, particularly solving the total porosity and permeability of porous media, taking advantage of modern hardware architectures. In our approach total porosity is calculated by the means of general-purpose computing on multiple GPUs. This application sticks together 2D slices of scanned rock and by the means of a marching tetrahedra algorithm, creates a 3D representation of pores and calculates the total porosity. Experimental results are compared with data obtained via other popular methods, including Nuclear Magnetic Resonance (NMR), helium porosity and nitrogen permeability tests. Then CFD simulations are performed on a large-scale high performance hardware architecture to solve the flow and permeability of porous media. In our experiments we used Lattice Boltzmann
Novel Architectures and Devices for Computing
NASA Astrophysics Data System (ADS)
Waugh, Frederick Rogers
1995-01-01
This thesis explores some of the more unusual architectures and devices being considered today as the basis for information processing, emphasizing architectures that are highly parallel and devices that are extremely small compared to current standards. The first part of this thesis theoretically and numerically analyzes analog electronic neural networks in which competition within neuron clusters leads to pattern classification and feature extraction abilities. Global stability theorems, derived using a Liapunov approach, provide general guidelines for network design and operation. The theorems state that with continuous-time updating, competitive networks converge only to fixed points, while with discrete -time, parallel updating, they converge to either fixed points or period-two limit cycles. A stability criterion guarantees that discrete-time networks converge only to fixed points when a quantity related to the neuron gain, or transfer function slope, is sufficiently small. A set of analytical phase diagrams for competitive associative memories is derived using a combination of statistical mechanics and nonlinear dynamics. The diagrams classify attractor types as a function of pattern storage fraction and neuron gain. Numerical tests agree well with the diagrams. Analog annealing, a technique for improving network performance by reducing neuron gain, is shown to improve performance in an analog associative memory by dramatically reducing the number of fixed points. The number of fixed points decreases exponentially with network size with a scaling exponent that decreases with neuron gain. Numerical data based on fixed-point counts in small networks support the results. The second part of this thesis discusses low-temperature tunneling measurements at zero magnetic field through double and triple quantum dots with adjustable inter-dot coupling, fabricated in a GaAs/AlGaAs heterostructure. The devices have capacitances so small that the charging energy of
Parallel image computation in clusters with task-distributor.
Baun, Christian
2016-01-01
Distributed systems, especially clusters, can be used to execute ray tracing tasks in parallel for speeding up the image computation. Because ray tracing is a computational expensive and memory consuming task, ray tracing can also be used to benchmark clusters. This paper introduces task-distributor, a free software solution for the parallel execution of ray tracing tasks in distributed systems. The ray tracing solution used for this work is the Persistence Of Vision Raytracer (POV-Ray). Task-distributor does not require any modification of the POV-Ray source code or the installation of an additional message passing library like the Message Passing Interface or Parallel Virtual Machine to allow parallel image computation, in contrast to various other projects. By analyzing the runtime of the sequential and parallel program parts of task-distributor, it becomes clear how the problem size and available hardware resources influence the scaling of the parallel application.
Distributing an executable job load file to compute nodes in a parallel computer
Gooding, Thomas M.
2016-08-09
Distributing an executable job load file to compute nodes in a parallel computer, the parallel computer comprising a plurality of compute nodes, including: determining, by a compute node in the parallel computer, whether the compute node is participating in a job; determining, by the compute node in the parallel computer, whether a descendant compute node is participating in the job; responsive to determining that the compute node is participating in the job or that the descendant compute node is participating in the job, communicating, by the compute node to a parent compute node, an identification of a data communications link over which the compute node receives data from the parent compute node; constructing a class route for the job, wherein the class route identifies all compute nodes participating in the job; and broadcasting the executable load file for the job along the class route for the job.
Distributing an executable job load file to compute nodes in a parallel computer
Gooding, Thomas M.
2016-09-13
Distributing an executable job load file to compute nodes in a parallel computer, the parallel computer comprising a plurality of compute nodes, including: determining, by a compute node in the parallel computer, whether the compute node is participating in a job; determining, by the compute node in the parallel computer, whether a descendant compute node is participating in the job; responsive to determining that the compute node is participating in the job or that the descendant compute node is participating in the job, communicating, by the compute node to a parent compute node, an identification of a data communications link over which the compute node receives data from the parent compute node; constructing a class route for the job, wherein the class route identifies all compute nodes participating in the job; and broadcasting the executable load file for the job along the class route for the job.
Quantum perceptron over a field and neural network architecture selection in a quantum computer.
da Silva, Adenilton José; Ludermir, Teresa Bernarda; de Oliveira, Wilson Rosa
2016-04-01
In this work, we propose a quantum neural network named quantum perceptron over a field (QPF). Quantum computers are not yet a reality and the models and algorithms proposed in this work cannot be simulated in actual (or classical) computers. QPF is a direct generalization of a classical perceptron and solves some drawbacks found in previous models of quantum perceptrons. We also present a learning algorithm named Superposition based Architecture Learning algorithm (SAL) that optimizes the neural network weights and architectures. SAL searches for the best architecture in a finite set of neural network architectures with linear time over the number of patterns in the training set. SAL is the first learning algorithm to determine neural network architectures in polynomial time. This speedup is obtained by the use of quantum parallelism and a non-linear quantum operator.
A High Performance COTS Based Computer Architecture
NASA Astrophysics Data System (ADS)
Patte, Mathieu; Grimoldi, Raoul; Trautner, Roland
2014-08-01
Using Commercial Off The Shelf (COTS) electronic components for space applications is a long standing idea. Indeed the difference in processing performance and energy efficiency between radiation hardened components and COTS components is so important that COTS components are very attractive for use in mass and power constrained systems. However using COTS components in space is not straightforward as one must account with the effects of the space environment on the COTS components behavior. In the frame of the ESA funded activity called High Performance COTS Based Computer, Airbus Defense and Space and its subcontractor OHB CGS have developed and prototyped a versatile COTS based architecture for high performance processing. The rest of the paper is organized as follows: in a first section we will start by recapitulating the interests and constraints of using COTS components for space applications; then we will briefly describe existing fault mitigation architectures and present our solution for fault mitigation based on a component called the SmartIO; in the last part of the paper we will describe the prototyping activities executed during the HiP CBC project.
Development of Message Passing Routines for High Performance Parallel Computations
NASA Technical Reports Server (NTRS)
Summers, Edward K.
2004-01-01
Computational Fluid Dynamics (CFD) calculations require a great deal of computing power for completing the detailed computations involved. In an effort shorten the time it takes to complete such calculations they are implemented on a parallel computer. In the case of a parallel computer some sort of message passing structure must be used to communicate between the computers because, unlike a single machine, each computer in a parallel computing cluster does not have access to all the data or run all the parts of the total program. Thus, message passing is used to divide up the data and send instructions to each machine. The nature of my work this summer involves programming the "message passing" aspect of the parallel computer. I am working on modifying an existing program, which was written with OpenMP, and does not use a multi-machine parallel computing structure, to work with Message Passing Interface (MPI) routines. The actual code is being written in the FORTRAN 90 programming language. My goal is to write a parameterized message passing structure that could be used for a variety of individual applications and implement it on Silicon Graphics Incorporated s (SGI) IRIX operating system. With this new parameterized structure engineers would be able to speed up computations for a wide variety of purposes without having to use larger and more expensive computing equipment from another division or another NASA center.
Ghosh, J.; Harrison, C.G.
1990-01-01
The present conference discusses topics in the fields of VLSI-based and real-time image-processing systems, parallel architectures for image processing, image-processing algorithms, and image processing on the basis of artificial neural networks. Attention is given to a fixed-point VLSI architecture for high-speed image reconstruction, an orthogonal multiprocessor for image processing with neural networks, massively parallel processors in real-time applications, the use of the adiabatic approximation as a tool in image estimation, parallel algorithms for contour-extraction and coding, and a parallel architecture for multidimensional image processing. Also discussed are concurrent image-processing on hypercube multicomputers, neural-network simulation on a reduced-mesh-of-trees organization, and a goal-seeking neural net for recall and recognition.
A scheme of optical interconnection for super high speed parallel computer
NASA Astrophysics Data System (ADS)
Mao, Youju; Lv, Yi; Liu, Jiang; Dang, Mingrui
2004-11-01
An optical cross connection network which adopts coarse wavelength division multiplexing (CWDM) and data packet is introduced. It can be used to realize communication between multi-CPU and multi-MEM in parallel computing system. It provides an effective way to upgrade the capability of parallel computer by combining optical wavelength division multiplexing (WDM) and data packet switching technology. CWDM used in network construction, optical cross connection (OXC) based on optical switch arrays, and data packet format used in network construction were analyzed. We have also done the optimizing analysis of the number of optical switches needed in different scales of network in this paper. The architecture of the optical interconnection for 8 wavelength channels and 128 bits parallel transmission has been researched. Finally, a parallel transmission system with 4 nodes, 8 channels per node, has been designed.
Data communications in a parallel active messaging interface of a parallel computer
Archer, Charles J; Blocksome, Michael A; Ratterman, Joseph D; Smith, Brian E
2014-02-11
Data communications in a parallel active messaging interface ('PAMI') or a parallel computer, the parallel computer including a plurality of compute nodes that execute a parallel application, the PAMI composed of data communications endpoints, each endpoint including a specification of data communications parameters for a thread of execution of a compute node, including specification of a client, a context, and a task, the compute nodes and the endpoints coupled for data communications instruction, the instruction characterized by instruction type, the instruction specifying a transmission of transfer data from the origin endpoint to a target endpoint and transmitting, in accordance witht the instruction type, the transfer data from the origin endpoin to the target endpoint.
Data communications in a parallel active messaging interface of a parallel computer
Archer, Charles J; Blocksome, Michael A; Ratterman, Joseph D; Smith, Brian E
2013-10-29
Data communications in a parallel active messaging interface (`PAMI`) of a parallel computer, the parallel computer including a plurality of compute nodes that execute a parallel application, the PAMI composed of data communications endpoints, each endpoint including a specification of data communications parameters for a thread of execution on a compute node, including specifications of a client, a context, and a task, the compute nodes and the endpoints coupled for data communications through the PAMI and through data communications resources, including receiving in an origin endpoint of the PAMI a data communications instruction, the instruction characterized by an instruction type, the instruction specifying a transmission of transfer data from the origin endpoint to a target endpoint and transmitting, in accordance with the instruction type, the transfer data from the origin endpoint to the target endpoint.
Evaluating the performance of the particle finite element method in parallel architectures
NASA Astrophysics Data System (ADS)
Gimenez, Juan M.; Nigro, Norberto M.; Idelsohn, Sergio R.
2014-05-01
This paper presents a high performance implementation for the particle-mesh based method called particle finite element method two (PFEM-2). It consists of a material derivative based formulation of the equations with a hybrid spatial discretization which uses an Eulerian mesh and Lagrangian particles. The main aim of PFEM-2 is to solve transport equations as fast as possible keeping some level of accuracy. The method was found to be competitive with classical Eulerian alternatives for these targets, even in their range of optimal application. To evaluate the goodness of the method with large simulations, it is imperative to use of parallel environments. Parallel strategies for Finite Element Method have been widely studied and many libraries can be used to solve Eulerian stages of PFEM-2. However, Lagrangian stages, such as streamline integration, must be developed considering the parallel strategy selected. The main drawback of PFEM-2 is the large amount of memory needed, which limits its application to large problems with only one computer. Therefore, a distributed-memory implementation is urgently needed. Unlike a shared-memory approach, using domain decomposition the memory is automatically isolated, thus avoiding race conditions; however new issues appear due to data distribution over the processes. Thus, a domain decomposition strategy for both particle and mesh is adopted, which minimizes the communication between processes. Finally, performance analysis running over multicore and multinode architectures are presented. The Courant-Friedrichs-Lewy number used influences the efficiency of the parallelization and, in some cases, a weighted partitioning can be used to improve the speed-up. However the total cputime for cases presented is lower than that obtained when using classical Eulerian strategies.
A scalable parallel black oil simulator on distributed memory parallel computers
NASA Astrophysics Data System (ADS)
Wang, Kun; Liu, Hui; Chen, Zhangxin
2015-11-01
This paper presents our work on developing a parallel black oil simulator for distributed memory computers based on our in-house parallel platform. The parallel simulator is designed to overcome the performance issues of common simulators that are implemented for personal computers and workstations. The finite difference method is applied to discretize the black oil model. In addition, some advanced techniques are employed to strengthen the robustness and parallel scalability of the simulator, including an inexact Newton method, matrix decoupling methods, and algebraic multigrid methods. A new multi-stage preconditioner is proposed to accelerate the solution of linear systems from the Newton methods. Numerical experiments show that our simulator is scalable and efficient, and is capable of simulating extremely large-scale black oil problems with tens of millions of grid blocks using thousands of MPI processes on parallel computers.
Algorithms for parallel and vector computations
NASA Technical Reports Server (NTRS)
Ortega, James M.
1995-01-01
This is a final report on work performed under NASA grant NAG-1-1112-FOP during the period March, 1990 through February 1995. Four major topics are covered: (1) solution of nonlinear poisson-type equations; (2) parallel reduced system conjugate gradient method; (3) orderings for conjugate gradient preconditioners, and (4) SOR as a preconditioner.
Dynamic traffic assignment on parallel computers
Nagel, K.; Frye, R.; Jakob, R.; Rickert, M.; Stretz, P.
1998-12-01
The authors describe part of the current framework of the TRANSIMS traffic research project at the Los Alamos National Laboratory. It includes parallel implementations of a route planner and a microscopic traffic simulation model. They present performance figures and results of an offline load-balancing scheme used in one of the iterative re-planning runs required for dynamic route assignment.
Performance issues for engineering analysis on MIMD parallel computers
Fang, H.E.; Vaughan, C.T.; Gardner, D.R.
1994-08-01
We discuss how engineering analysts can obtain greater computational resolution in a more timely manner from applications codes running on MIMD parallel computers. Both processor speed and memory capacity are important to achieving better performance than a serial vector supercomputer. To obtain good performance, a parallel applications code must be scalable. In addition, the aspect ratios of the subdomains in the decomposition of the simulation domain onto the parallel computer should be of order 1. We demonstrate these conclusions using simulations conducted with the PCTH shock wave physics code running on a Cray Y-MP, a 1024-node nCUBE 2, and an 1840-node Paragon.
An Efficient Objective Analysis System for Parallel Computers
NASA Technical Reports Server (NTRS)
Stobie, J.
1999-01-01
A new atmospheric objective analysis system designed for parallel computers will be described. The system can produce a global analysis (on a 1 X 1 lat-lon grid with 18 levels of heights and winds and 10 levels of moisture) using 120,000 observations in 17 minutes on 32 CPUs (SGI Origin 2000). No special parallel code is needed (e.g. MPI or multitasking) and the 32 CPUs do not have to be on the same platform. The system is totally portable and can run on several different architectures at once. In addition, the system can easily scale up to 100 or more CPUS. This will allow for much higher resolution and significant increases in input data. The system scales linearly as the number of observations and the number of grid points. The cost overhead in going from 1 to 32 CPUs is 18%. In addition, the analysis results are identical regardless of the number of processors used. This system has all the characteristics of optimal interpolation, combining detailed instrument and first guess error statistics to produce the best estimate of the atmospheric state. Static tests with a 2 X 2.5 resolution version of this system showed it's analysis increments are comparable to the latest NASA operational system including maintenance of mass-wind balance. Results from several months of cycling test in the Goddard EOS Data Assimilation System (GEOS DAS) show this new analysis retains the same level of agreement between the first guess and observations (O-F statistics) as the current operational system.
An Efficient Objective Analysis System for Parallel Computers
NASA Technical Reports Server (NTRS)
Stobie, James G.
1999-01-01
A new objective analysis system designed for parallel computers will be described. The system can produce a global analysis (on a 2 x 2.5 lat-lon grid with 20 levels of heights and winds and 10 levels of moisture) using 120,000 observations in less than 3 minutes on 32 CPUs (SGI Origin 2000). No special parallel code is needed (e.g. MPI or multitasking) and the 32 CPUs do not have to be on the same platform. The system Ls totally portable and can run on -several different architectures at once. In addition, the system can easily scale up to 100 or more CPUS. This will allow for much higher resolution and significant increases in input data. The system scales linearly as the number of observations and the number of grid points. The cost overhead in going from I to 32 CPus is 18%. in addition, the analysis results are identical regardless of the number of processors used. T'his system has all the characteristics of optimal interpolation, combining detailed instrument and first guess error statistics to produce the best estimate of the atmospheric state. It also includes a new quality control (buddy check) system. Static tests with the system showed it's analysis increments are comparable to the latest NASA operational system including maintenance of mass-wind balance. Results from a 2-month cycling test in the Goddard EOS Data Assimilation System (GEOS DAS) show this new analysis retains the same level of agreement between the first guess and observations (0-F statistics) throughout the entire two months.
Mathematical model partitioning and packing for parallel computer calculation
NASA Technical Reports Server (NTRS)
Arpasi, Dale J.; Milner, Edward J.
1986-01-01
This paper deals with the development of multiprocessor simulations from a serial set of ordinary differential equations describing a physical system. The identification of computational parallelism within the model equations is discussed. A technique is presented for identifying this parallelism and for partitioning the equations for parallel solution on a multiprocessor. Next, an algorithm which packs the equations into a minimum number of processors is described. The results of applying the packing algorithm to a turboshaft engine model are presented.
Implementation and analysis of a Navier-Stokes algorithm on parallel computers
NASA Technical Reports Server (NTRS)
Fatoohi, Raad A.; Grosch, Chester E.
1988-01-01
The results of the implementation of a Navier-Stokes algorithm on three parallel/vector computers are presented. The object of this research is to determine how well, or poorly, a single numerical algorithm would map onto three different architectures. The algorithm is a compact difference scheme for the solution of the incompressible, two-dimensional, time-dependent Navier-Stokes equations. The computers were chosen so as to encompass a variety of architectures. They are the following: the MPP, an SIMD machine with 16K bit serial processors; Flex/32, an MIMD machine with 20 processors; and Cray/2. The implementation of the algorithm is discussed in relation to these architectures and measures of the performance on each machine are given. The basic comparison is among SIMD instruction parallelism on the MPP, MIMD process parallelism on the Flex/32, and vectorization of a serial code on the Cray/2. Simple performance models are used to describe the performance. These models highlight the bottlenecks and limiting factors for this algorithm on these architectures. Finally, conclusions are presented.
Nguyen, Tuan-Anh; Nakib, Amir; Nguyen, Huy-Nam
2016-06-01
The Non-local means denoising filter has been established as gold standard for image denoising problem in general and particularly in medical imaging due to its efficiency. However, its computation time limited its applications in real world application, especially in medical imaging. In this paper, a distributed version on parallel hybrid architecture is proposed to solve the computation time problem and a new method to compute the filters' coefficients is also proposed, where we focused on the implementation and the enhancement of filters' parameters via taking the neighborhood of the current voxel more accurately into account. In terms of implementation, our key contribution consists in reducing the number of shared memory accesses. The different tests of the proposed method were performed on the brain-web database for different levels of noise. Performances and the sensitivity were quantified in terms of speedup, peak signal to noise ratio, execution time, the number of floating point operations. The obtained results demonstrate the efficiency of the proposed method. Moreover, the implementation is compared to that of other techniques, recently published in the literature.
NASA Astrophysics Data System (ADS)
Fazanaro, Filipe I.; Soriano, Diogo C.; Suyama, Ricardo; Madrid, Marconi K.; Oliveira, José Raimundo de; Muñoz, Ignacio Bravo; Attux, Romis
2016-08-01
The characterization of nonlinear dynamical systems and their attractors in terms of invariant measures, basins of attractions and the structure of their vector fields usually outlines a task strongly related to the underlying computational cost. In this work, the practical aspects related to the use of parallel computing - specially the use of Graphics Processing Units (GPUS) and of the Compute Unified Device Architecture (CUDA) - are reviewed and discussed in the context of nonlinear dynamical systems characterization. In this work such characterization is performed by obtaining both local and global Lyapunov exponents for the classical forced Duffing oscillator. The local divergence measure was employed by the computation of the Lagrangian Coherent Structures (LCSS), revealing the general organization of the flow according to the obtained separatrices, while the global Lyapunov exponents were used to characterize the attractors obtained under one or more bifurcation parameters. These simulation sets also illustrate the required computation time and speedup gains provided by different parallel computing strategies, justifying the employment and the relevance of GPUS and CUDA in such extensive numerical approach. Finally, more than simply providing an overview supported by a representative set of simulations, this work also aims to be a unified introduction to the use of the mentioned parallel computing tools in the context of nonlinear dynamical systems, providing codes and examples to be executed in MATLAB and using the CUDA environment, something that is usually fragmented in different scientific communities and restricted to specialists on parallel computing strategies.
NASA Technical Reports Server (NTRS)
Choudhary, Alok N.; Patel, Janak H.; Ahuja, Narendra
1989-01-01
In part 1 architecture of NETRA is presented. A performance evaluation of NETRA using several common vision algorithms is also presented. Performance of algorithms when they are mapped on one cluster is described. It is shown that SIMD, MIMD, and systolic algorithms can be easily mapped onto processor clusters, and almost linear speedups are possible. For some algorithms, analytical performance results are compared with implementation performance results. It is observed that the analysis is very accurate. Performance analysis of parallel algorithms when mapped across clusters is presented. Mappings across clusters illustrate the importance and use of shared as well as distributed memory in achieving high performance. The parameters for evaluation are derived from the characteristics of the parallel algorithms, and these parameters are used to evaluate the alternative communication strategies in NETRA. Furthermore, the effect of communication interference from other processors in the system on the execution of an algorithm is studied. Using the analysis, performance of many algorithms with different characteristics is presented. It is observed that if communication speeds are matched with the computation speeds, good speedups are possible when algorithms are mapped across clusters.
NASA Astrophysics Data System (ADS)
Arrasmith, William W.; Sullivan, Sean F.
2008-04-01
Phase diversity imaging methods work well in removing atmospheric turbulence and some system effects from predominantly near-field imaging systems. However, phase diversity approaches can be computationally intensive and slow. We present a recently adapted, high-speed phase diversity method using a conventional, software-based neural network paradigm. This phase-diversity method has the advantage of eliminating many time consuming, computationally heavy calculations and directly estimates the optical transfer function from the entrance pupil phases or phase differences. Additionally, this method is more accurate than conventional Zernike-based, phase diversity approaches and lends itself to implementation on parallel software or hardware architectures. We use computer simulation to demonstrate how this high-speed, phase diverse imaging method can be implemented on a parallel, highspeed, neural network-based architecture-specifically the Cellular Neural Network (CNN). The CNN architecture was chosen as a representative, neural network-based processing environment because 1) the CNN can be implemented in 2-D or 3-D processing schemes, 2) it can be implemented in hardware or software, 3) recent 2-D implementations of CNN technology have shown a 3 orders of magnitude superiority in speed, area, or power over equivalent digital representations, and 4) a complete development environment exists. We also provide a short discussion on processing speed.
Automatically Parallelizing Legacy Binary Code for Multicore Architectures
2009-08-01
had a lasting impact on the respective works of each researcher. 1 1 Executive Summary The industrial adoption of multicore computing has...The rise of commodity multicore computing has forced many organizations to re-evaluate current programming paradigms and software execution models...advantage of the power provided by now- commodity multicore hardware --- a power for which the extensive legacy computing base seems ill-matched, since
A portable implementation of ARPACK for distributed memory parallel architectures
Maschhoff, K.J.; Sorensen, D.C.
1996-12-31
ARPACK is a package of Fortran 77 subroutines which implement the Implicitly Restarted Arnoldi Method used for solving large sparse eigenvalue problems. A parallel implementation of ARPACK is presented which is portable across a wide range of distributed memory platforms and requires minimal changes to the serial code. The communication layers used for message passing are the Basic Linear Algebra Communication Subprograms (BLACS) developed for the ScaLAPACK project and Message Passing Interface(MPI).
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.
Locating and computing in parallel all the simple roots of special functions using PVM
NASA Astrophysics Data System (ADS)
Plagianakos, V. P.; Nousis, N. K.; Vrahatis, M. N.
2001-08-01
An algorithm is proposed for locating and computing in parallel and with certainty all the simple roots of any twice continuously differentiable function in any specific interval. To compute with certainty all the roots, the proposed method is heavily based on the knowledge of the total number of roots within the given interval. To obtain this information we use results from topological degree theory and, in particular, the Kronecker-Picard approach. This theory gives a formula for the computation of the total number of roots of a system of equations within a given region, which can be computed in parallel. With this tool in hand, we construct a parallel procedure for the localization and isolation of all the roots by dividing the given region successively and applying the above formula to these subregions until the final domains contain at the most one root. The subregions with no roots are discarded, while for the rest a modification of the well-known bisection method is employed for the computation of the contained root. The new aspect of the present contribution is that the computation of the total number of zeros using the Kronecker-Picard integral as well as the localization and computation of all the roots is performed in parallel using the parallel virtual machine (PVM). PVM is an integrated set of software tools and libraries that emulates a general-purpose, flexible, heterogeneous concurrent computing framework on interconnected computers of varied architectures. The proposed algorithm has large granularity and low synchronization, and is robust. It has been implemented and tested and our experience is that it can massively compute with certainty all the roots in a certain interval. Performance information from massive computations related to a recently proposed conjecture due to Elbert (this issue, J. Comput. Appl. Math. 133 (2001) 65-83) is reported.
Large-scale data-flow computer for parallel signal processing
Wong, F.S.; Ito, M.R.
1982-01-01
The authors describe a proposed data-driven, parallel computing machine for signal processing applications in which program codes are often executed repeatedly. This dataflow computer (DFC) consists of a large number of processing modules (PM) operating asynchronously; multiple concurrent activations of a single procedure could be supported by each PM without replication of codes. The architectural design emphasizes simplicity of system operations, modularity, speed and feasibility with current technology. Performance studies are carried out via software simulations. Results show some insights to the basic organization and the various modes of computation, the speed-ups and robustness of the design are also tested with the variations of several system parameters. 4 references.
Serial multiplier arrays for parallel computation
NASA Technical Reports Server (NTRS)
Winters, Kel
1990-01-01
Arrays of systolic serial-parallel multiplier elements are proposed as an alternative to conventional SIMD mesh serial adder arrays for applications that are multiplication intensive and require few stored operands. The design and operation of a number of multiplier and array configurations featuring locality of connection, modularity, and regularity of structure are discussed. A design methodology combining top-down and bottom-up techniques is described to facilitate development of custom high-performance CMOS multiplier element arrays as well as rapid synthesis of simulation models and semicustom prototype CMOS components. Finally, a differential version of NORA dynamic circuits requiring a single-phase uncomplemented clock signal introduced for this application.
NASA Astrophysics Data System (ADS)
Shi, X.
2015-12-01
As NSF indicated - "Theory and experimentation have for centuries been regarded as two fundamental pillars of science. It is now widely recognized that computational and data-enabled science forms a critical third pillar." Geocomputation is the third pillar of GIScience and geosciences. With the exponential growth of geodata, the challenge of scalable and high performance computing for big data analytics become urgent because many research activities are constrained by the inability of software or tool that even could not complete the computation process. Heterogeneous geodata integration and analytics obviously magnify the complexity and operational time frame. Many large-scale geospatial problems may be not processable at all if the computer system does not have sufficient memory or computational power. Emerging computer architectures, such as Intel's Many Integrated Core (MIC) Architecture and Graphics Processing Unit (GPU), and advanced computing technologies provide promising solutions to employ massive parallelism and hardware resources to achieve scalability and high performance for data intensive computing over large spatiotemporal and social media data. Exploring novel algorithms and deploying the solutions in massively parallel computing environment to achieve the capability for scalable data processing and analytics over large-scale, complex, and heterogeneous geodata with consistent quality and high-performance has been the central theme of our research team in the Department of Geosciences at the University of Arkansas (UARK). New multi-core architectures combined with application accelerators hold the promise to achieve scalability and high performance by exploiting task and data levels of parallelism that are not supported by the conventional computing systems. Such a parallel or distributed computing environment is particularly suitable for large-scale geocomputation over big data as proved by our prior works, while the potential of such advanced
Use of parallel computing in mass processing of laser data
NASA Astrophysics Data System (ADS)
Będkowski, J.; Bratuś, R.; Prochaska, M.; Rzonca, A.
2015-12-01
The first part of the paper includes a description of the rules used to generate the algorithm needed for the purpose of parallel computing and also discusses the origins of the idea of research on the use of graphics processors in large scale processing of laser scanning data. The next part of the paper includes the results of an efficiency assessment performed for an array of different processing options, all of which were substantially accelerated with parallel computing. The processing options were divided into the generation of orthophotos using point clouds, coloring of point clouds, transformations, and the generation of a regular grid, as well as advanced processes such as the detection of planes and edges, point cloud classification, and the analysis of data for the purpose of quality control. Most algorithms had to be formulated from scratch in the context of the requirements of parallel computing. A few of the algorithms were based on existing technology developed by the Dephos Software Company and then adapted to parallel computing in the course of this research study. Processing time was determined for each process employed for a typical quantity of data processed, which helped confirm the high efficiency of the solutions proposed and the applicability of parallel computing to the processing of laser scanning data. The high efficiency of parallel computing yields new opportunities in the creation and organization of processing methods for laser scanning data.
Parallel Computing for Probabilistic Response Analysis of High Temperature Composites
NASA Technical Reports Server (NTRS)
Sues, R. H.; Lua, Y. J.; Smith, M. D.
1994-01-01
The objective of this Phase I research was to establish the required software and hardware strategies to achieve large scale parallelism in solving PCM problems. To meet this objective, several investigations were conducted. First, we identified the multiple levels of parallelism in PCM and the computational strategies to exploit these parallelisms. Next, several software and hardware efficiency investigations were conducted. These involved the use of three different parallel programming paradigms and solution of two example problems on both a shared-memory multiprocessor and a distributed-memory network of workstations.
NASA Technical Reports Server (NTRS)
Smith, Garrett; Philips, Alan
2003-01-01
Three dominant Two Stage To Orbit (TSTO) class architectures were studied: Series Burn (SB), Parallel Bum with crossfeed (PBw/cf), and Parallel Burn, no-crossfeed (PBncf). The study goal was to determine what factors uniquely affect PBncf architectures, how each of these factors interact, and to determine from a performance perspective whether a PBncf vehicle could be competitive with a PBw/cf or a SB vehicle using equivalent technology and assumptions. In all cases, performance was evaluated on a relative basis for a fixed payload and mission by comparing gross and dry vehicle masses of a closed vehicle. Propellant combinations studied were LOX: LH2 propelled booster and orbiter (HH) and LOX: Kerosene booster with LOX: LH2 orbiter (KH). The study observations were: 1) A PBncf orbiter should be throttled as deeply as possible after launch until the staging point. 2) A PBncf TSTO architecture is feasible for systems that stage at mach 7. 2a) HH architectures can achieve a mass growth relative to PBw/cf of <20%. 2b) KH architectures can achieve a mass growth relative to Series Burn of <20%. 3) Center of gravity (CG) control will be a major issue for a PBncf vehicle, due to the low orbiter specific thrust to weight ratio and to the position of the orbiter required to align the nozzle heights at liftoff. 4) Thrust to weight ratios of 1.3 at liftoff and between 1.0 and 0.9 when staging at mach 7 appear to be close to ideal for PBncf vehicles. 5) Performance for HH vehicles was better when staged at mach 7 instead of mach 5. The study suggests possible methods to maximize performance of PBncf vehicle architectures in order to meet mission design requirements.
An Efficient Cloud Computing-Based Architecture for Freight System Application in China Railway
NASA Astrophysics Data System (ADS)
Zhang, Baopeng; Zhang, Ning; Li, Honghui; Liu, Feng; Miao, Kai
Cloud computing is a new network computing paradigm of distributed application environment. It utilizes the computing resource and storage resource to dynamically provide on-demand service for users. The distribution and parallel characters of cloud computing can leverage the railway freight system. We implement a cloud computing-based architecture for freight system application, which explores the Tashi and Hadoop for virtual resource management and MapReduce-based search technology. We propose the semantic model and setup configuration parameter by experiment, and develop the prototype system for freight search and tracking.
Implementation of linear-scaling plane wave density functional theory on parallel computers
NASA Astrophysics Data System (ADS)
Skylaris, Chris-Kriton; Haynes, Peter D.; Mostofi, Arash A.; Payne, Mike C.
We describe the algorithms we have developed for linear-scaling plane wave density functional calculations on parallel computers as implemented in the onetep program. We outline how onetep achieves plane wave accuracy with a computational cost which increases only linearly with the number of atoms by optimising directly the single-particle density matrix expressed in a psinc basis set. We describe in detail the novel algorithms we have developed for computing with the psinc basis set the quantities needed in the evaluation and optimisation of the total energy within our approach. For our parallel computations we use the general Message Passing Interface (MPI) library of subroutines to exchange data between processors. Accordingly, we have developed efficient schemes for distributing data and computational load to processors in a balanced manner. We describe these schemes in detail and in relation to our algorithms for computations with a psinc basis. Results of tests on different materials show that onetep is an efficient parallel code that should be able to take advantage of a wide range of parallel computer architectures.
History Matching in Parallel Computational Environments
Steven Bryant; Sanjay Srinivasan; Alvaro Barrera; Sharad Yadav
2004-08-31
In the probabilistic approach for history matching, the information from the dynamic data is merged with the prior geologic information in order to generate permeability models consistent with the observed dynamic data as well as the prior geology. The relationship between dynamic response data and reservoir attributes may vary in different regions of the reservoir due to spatial variations in reservoir attributes, fluid properties, well configuration, flow constrains on wells etc. This implies probabilistic approach should then update different regions of the reservoir in different ways. This necessitates delineation of multiple reservoir domains in order to increase the accuracy of the approach. The research focuses on a probabilistic approach to integrate dynamic data that ensures consistency between reservoir models developed from one stage to the next. The algorithm relies on efficient parameterization of the dynamic data integration problem and permits rapid assessment of the updated reservoir model at each stage. The report also outlines various domain decomposition schemes from the perspective of increasing the accuracy of probabilistic approach of history matching. Research progress in three important areas of the project are discussed: {lg_bullet}Validation and testing the probabilistic approach to incorporating production data in reservoir models. {lg_bullet}Development of a robust scheme for identifying reservoir regions that will result in a more robust parameterization of the history matching process. {lg_bullet}Testing commercial simulators for parallel capability and development of a parallel algorithm for history matching.
Performance Analysis of Multilevel Parallel Applications on Shared Memory Architectures
NASA Technical Reports Server (NTRS)
Jost, Gabriele; Jin, Haoqiang; Labarta, Jesus; Gimenez, Judit; Caubet, Jordi; Biegel, Bryan A. (Technical Monitor)
2002-01-01
In this paper we describe how to apply powerful performance analysis techniques to understand the behavior of multilevel parallel applications. We use the Paraver/OMPItrace performance analysis system for our study. This system consists of two major components: The OMPItrace dynamic instrumentation mechanism, which allows the tracing of processes and threads and the Paraver graphical user interface for inspection and analyses of the generated traces. We describe how to use the system to conduct a detailed comparative study of a benchmark code implemented in five different programming paradigms applicable for shared memory
Access and visualization using clusters and other parallel computers
NASA Technical Reports Server (NTRS)
Katz, Daniel S.; Bergou, Attila; Berriman, Bruce; Block, Gary; Collier, Jim; Curkendall, Dave; Good, John; Husman, Laura; Jacob, Joe; Laity, Anastasia; Li, Peggy; Miller, Craig; Plesea, Lucian; Prince, Tom; Siegel, Herb; Williams, Roy
2003-01-01
JPL's Parallel Applications Technologies Group has been exploring the issues of data access and visualization of very large data sets over the past 10 or so years. this work has used a number of types of parallel computers, and today includes the use of commodity clusters. This talk will highlight some of the applications and tools we have developed, including how they use parallel computing resources, and specifically how we are using modern clusters. Our applications focus on NASA's needs; thus our data sets are usually related to Earth and Space Science, including data delivered from instruments in space, and data produced by telescopes on the ground.
Performing a global barrier operation in a parallel computer
Archer, Charles J; Blocksome, Michael A; Ratterman, Joseph D; Smith, Brian E
2014-12-09
Executing computing tasks on a parallel computer that includes compute nodes coupled for data communications, where each compute node executes tasks, with one task on each compute node designated as a master task, including: for each task on each compute node until all master tasks have joined a global barrier: determining whether the task is a master task; if the task is not a master task, joining a single local barrier; if the task is a master task, joining the global barrier and the single local barrier only after all other tasks on the compute node have joined the single local barrier.
Parallel hardware architecture for JPEG-LS based on domain decomposition
NASA Astrophysics Data System (ADS)
Ahmed, S.; Wang, Z.; Klaiber, M.; Wahl, S.; Wroblewski, M.; Simon, S.
2012-10-01
JPEG-LS has a large number of different and independent context sets that provide the opportunity for par-allelism. As JPEG-LS, many of the lossless image compression standards have "adaptive" error modeling as the core part. This, however, leads to data dependency loops of the compression scheme such that a parallel compression of neighboring pixels is not possible. In this paper, a hardware architecture is proposed in order to achieve parallelism in the JPEG-LS compression. In the adaptive part of the algorithm, the context update and error modeling of a pixel belonging to a context number depends on the previous pixel having the same context number. On the other hand, the probability for two successive pixels to be in different contexts is only 17%. Thus storage is required for the intermediary pixels of the same context. In this architecture, a buffer mechanism is built to exploit the parallelism regardless of the adaptive characteristics. Despite the introduced architectural parallelism, the resulting JPEG-LS codec is fully compatible with the ISO/IEC 14495-1 JPEG-LS standard. A design for such a hardware system is provided here and simulated in FPGA which is also compared with a sequential pipelined architecture of JPEG-LS implemented in FPGA. The final design makes it possible to be applied with a streaming image sensor and does not require storing the entire image before compression. Thus it is capable of lossless compression of input images in real-time embedded systems.
Models and Measurements of Parallelism for a Distributed Computer System.
1982-01-01
that parallel execution of the processes comprising an application program will defray U the overhead costs of distributed computing . This...of Different Approaches to Distributed Computing ", Proceedings of the Ist International Conference on Distributed Comput er Systems, Huntsville, AL...Oct. 1-5, 1979), pp. 222-232. [20] Liskov, B., "Primitives for Distributed Computing ", Froceedings of the 7--th Symposium on Operating System
Swift : fast, reliable, loosely coupled parallel computation.
Zhao, Y.; Hategan, M.; Clifford, B.; Foster, I.; von Laszewski, G.; Nefedova, V.; Raicu, I.; Stef-Praun, T.; Wilde, M.; Mathematics and Computer Science; Univ. of Chicago
2007-01-01
A common pattern in scientific computing involves the execution of many tasks that are coupled only in the sense that the output of one may be passed as input to one or more others - for example, as a file, or via a Web Services invocation. While such 'loosely coupled' computations can involve large amounts of computation and communication, the concerns of the programmer tend to be different than in traditional high performance computing, being focused on management issues relating to the large numbers of datasets and tasks (and often, the complexities inherent in 'messy' data organizations) rather than the optimization of interprocessor communication. To address these concerns, we have developed Swift, a system that combines a novel scripting language called SwiftScript with a powerful runtime system based on CoG Karajan and Falkon to allow for the concise specification, and reliable and efficient execution, of large loosely coupled computations. Swift adopts and adapts ideas first explored in the GriPhyN virtual data system, improving on that system in many regards. We describe the SwiftScript language and its use of XDTM to describe the logical structure of complex file system structures. We also present the Swift system and its use of CoG Karajan, Falkon, and Globus services to dispatch and manage the execution of many tasks in different execution environments. We summarize application experiences and detail performance experiments that quantify the cost of Swift operations.
Parallel structures in human and computer memory
NASA Technical Reports Server (NTRS)
Kanerva, P.
1986-01-01
If one thinks of our experiences as being recorded continuously on film, then human memory can be compared to a film library that is indexed by the contents of the film strips stored in it. Moreover, approximate retrieval cues suffice to retrieve information stored in this library. One recognizes a familiar person in a fuzzy photograph or a familiar tune played on a strange instrument. A computer memory that would allow a computer to recognize patterns and to recall sequences the way humans do is constructed. Such a memory is remarkably similiar in structure to a conventional computer memory and also to the neural circuits in the cortex of the cerebellum of the human brain. It is concluded that the frame problem of artificial intelligence could be solved by the use of such a memory if one were able to encode information about the world properly.
Misleading Performance Claims in Parallel Computations
Bailey, David H.
2009-05-29
In a previous humorous note entitled 'Twelve Ways to Fool the Masses,' I outlined twelve common ways in which performance figures for technical computer systems can be distorted. In this paper and accompanying conference talk, I give a reprise of these twelve 'methods' and give some actual examples that have appeared in peer-reviewed literature in years past. I then propose guidelines for reporting performance, the adoption of which would raise the level of professionalism and reduce the level of confusion, not only in the world of device simulation but also in the larger arena of technical computing.
Performance Analysis of Cloud Computing Architectures Using Discrete Event Simulation
NASA Technical Reports Server (NTRS)
Stocker, John C.; Golomb, Andrew M.
2011-01-01
Cloud computing offers the economic benefit of on-demand resource allocation to meet changing enterprise computing needs. However, the flexibility of cloud computing is disadvantaged when compared to traditional hosting in providing predictable application and service performance. Cloud computing relies on resource scheduling in a virtualized network-centric server environment, which makes static performance analysis infeasible. We developed a discrete event simulation model to evaluate the overall effectiveness of organizations in executing their workflow in traditional and cloud computing architectures. The two part model framework characterizes both the demand using a probability distribution for each type of service request as well as enterprise computing resource constraints. Our simulations provide quantitative analysis to design and provision computing architectures that maximize overall mission effectiveness. We share our analysis of key resource constraints in cloud computing architectures and findings on the appropriateness of cloud computing in various applications.
Parallel processor-based raster graphics system architecture
Littlefield, Richard J.
1990-01-01
An apparatus for generating raster graphics images from the graphics command stream includes a plurality of graphics processors connected in parallel, each adapted to receive any part of the graphics command stream for processing the command stream part into pixel data. The apparatus also includes a frame buffer for mapping the pixel data to pixel locations and an interconnection network for interconnecting the graphics processors to the frame buffer. Through the interconnection network, each graphics processor may access any part of the frame buffer concurrently with another graphics processor accessing any other part of the frame buffer. The plurality of graphics processors can thereby transmit concurrently pixel data to pixel locations in the frame buffer.
Efficient Parallel Kernel Solvers for Computational Fluid Dynamics Applications
NASA Technical Reports Server (NTRS)
Sun, Xian-He
1997-01-01
Distributed-memory parallel computers dominate today's parallel computing arena. These machines, such as Intel Paragon, IBM SP2, and Cray Origin2OO, have successfully delivered high performance computing power for solving some of the so-called "grand-challenge" problems. Despite initial success, parallel machines have not been widely accepted in production engineering environments due to the complexity of parallel programming. On a parallel computing system, a task has to be partitioned and distributed appropriately among processors to reduce communication cost and to attain load balance. More importantly, even with careful partitioning and mapping, the performance of an algorithm may still be unsatisfactory, since conventional sequential algorithms may be serial in nature and may not be implemented efficiently on parallel machines. In many cases, new algorithms have to be introduced to increase parallel performance. In order to achieve optimal performance, in addition to partitioning and mapping, a careful performance study should be conducted for a given application to find a good algorithm-machine combination. This process, however, is usually painful and elusive. The goal of this project is to design and develop efficient parallel algorithms for highly accurate Computational Fluid Dynamics (CFD) simulations and other engineering applications. The work plan is 1) developing highly accurate parallel numerical algorithms, 2) conduct preliminary testing to verify the effectiveness and potential of these algorithms, 3) incorporate newly developed algorithms into actual simulation packages. The work plan has well achieved. Two highly accurate, efficient Poisson solvers have been developed and tested based on two different approaches: (1) Adopting a mathematical geometry which has a better capacity to describe the fluid, (2) Using compact scheme to gain high order accuracy in numerical discretization. The previously developed Parallel Diagonal Dominant (PDD) algorithm
Innovative architectures for dense multi-microprocessor computers
NASA Technical Reports Server (NTRS)
Donaldson, Thomas; Doty, Karl; Engle, Steven W.; Larson, Robert E.; O'Reilly, John G.
1988-01-01
The results of a Phase I Small Business Innovative Research (SBIR) project performed for the NASA Langley Computational Structural Mechanics Group are described. The project resulted in the identification of a family of chordal-ring interconnection architectures with excellent potential to serve as the basis for new multimicroprocessor (MMP) computers. The paper presents examples of how computational algorithms from structural mechanics can be efficiently implemented on the chordal-ring architecture.
Distributed Computing for Signal Processing: Modeling of Asynchronous Parallel Computation.
1986-03-01
P36-844. **VAX is a trademark of Digital Equipment Corporation . ..- ’. 100 *e .................................................... Paper 2L Parallel...ming, Computzng Surveyv, 9, March, pp. 29-59. U .nix is a trademark AI Bell Lajboratories. ... VAX is a trademark of Digital Equipment Corporation ...parallelism will not reduce the processor communicatio s response time. Thus, there are associated costs and limitations (•) Amount of memory
A Lanczos eigenvalue method on a parallel computer
NASA Technical Reports Server (NTRS)
Bostic, Susan W.; Fulton, Robert E.
1987-01-01
Eigenvalue analyses of complex structures is a computationally intensive task which can benefit significantly from new and impending parallel computers. This study reports on a parallel computer implementation of the Lanczos method for free vibration analysis. The approach used here subdivides the major Lanczos calculation tasks into subtasks and introduces parallelism down to the subtask levels such as matrix decomposition and forward/backward substitution. The method was implemented on a commercial parallel computer and results were obtained for a long flexible space structure. While parallel computing efficiency for the Lanczos method was good for a moderate number of processors for the test problem, the greatest reduction in time was realized for the decomposition of the stiffness matrix, a calculation which took 70 percent of the time in the sequential program and which took 25 percent of the time on eight processors. For a sample calculation of the twenty lowest frequencies of a 486 degree of freedom problem, the total sequential computing time was reduced by almost a factor of ten using 16 processors.
Identifying failure in a tree network of a parallel computer
Archer, Charles J.; Pinnow, Kurt W.; Wallenfelt, Brian P.
2010-08-24
Methods, parallel computers, and products are provided for identifying failure in a tree network of a parallel computer. The parallel computer includes one or more processing sets including an I/O node and a plurality of compute nodes. For each processing set embodiments include selecting a set of test compute nodes, the test compute nodes being a subset of the compute nodes of the processing set; measuring the performance of the I/O node of the processing set; measuring the performance of the selected set of test compute nodes; calculating a current test value in dependence upon the measured performance of the I/O node of the processing set, the measured performance of the set of test compute nodes, and a predetermined value for I/O node performance; and comparing the current test value with a predetermined tree performance threshold. If the current test value is below the predetermined tree performance threshold, embodiments include selecting another set of test compute nodes. If the current test value is not below the predetermined tree performance threshold, embodiments include selecting from the test compute nodes one or more potential problem nodes and testing individually potential problem nodes and links to potential problem nodes.
Parallel Computing by Xeroxing on Transparencies
NASA Astrophysics Data System (ADS)
Head, Tom
We illustrate a procedure for solving instances of the Boolean satisfiability (SAT) problem by xeroxing onto transparent plastic sheets. Suppose that m clauses are given in which n variables occur and that the longest clause contains k literals. The associated instance of the SAT problem can be solved by using a xerox machine to form only n+2k+m successive transparencies. The applicability of this linear time algorithm is limited, of course, by the increase in the information density on the transparencies when n is large. This same scheme of computation can be carried out by using photographic or other optical processes. This work has been developed as an alternate implementation of procedures previously developed in the context of aqueous (DNA) computing.
Applications of Parallel Computation in Micro-Mechanics and Finite Element Method
NASA Technical Reports Server (NTRS)
Tan, Hui-Qian
1996-01-01
This project discusses the application of parallel computations related with respect to material analyses. Briefly speaking, we analyze some kind of material by elements computations. We call an element a cell here. A cell is divided into a number of subelements called subcells and all subcells in a cell have the identical structure. The detailed structure will be given later in this paper. It is obvious that the problem is "well-structured". SIMD machine would be a better choice. In this paper we try to look into the potentials of SIMD machine in dealing with finite element computation by developing appropriate algorithms on MasPar, a SIMD parallel machine. In section 2, the architecture of MasPar will be discussed. A brief review of the parallel programming language MPL also is given in that section. In section 3, some general parallel algorithms which might be useful to the project will be proposed. And, combining with the algorithms, some features of MPL will be discussed in more detail. In section 4, the computational structure of cell/subcell model will be given. The idea of designing the parallel algorithm for the model will be demonstrated. Finally in section 5, a summary will be given.
A microeconomic scheduler for parallel computers
NASA Technical Reports Server (NTRS)
Stoica, Ion; Abdel-Wahab, Hussein; Pothen, Alex
1995-01-01
We describe a scheduler based on the microeconomic paradigm for scheduling on-line a set of parallel jobs in a multiprocessor system. In addition to the classical objectives of increasing the system throughput and reducing the response time, we consider fairness in allocating system resources among the users, and providing the user with control over the relative performances of his jobs. We associate with every user a savings account in which he receives money at a constant rate. When a user wants to run a job, he creates an expense account for that job to which he transfers money from his savings account. The job uses the funds in its expense account to obtain the system resources it needs for execution. The share of the system resources allocated to the user is directly related to the rate at which the user receives money; the rate at which the user transfers money into a job expense account controls the job's performance. We prove that starvation is not possible in our model. Simulation results show that our scheduler improves both system and user performances in comparison with two different variable partitioning policies. It is also shown to be effective in guaranteeing fairness and providing control over the performance of jobs.
Methods for operating parallel computing systems employing sequenced communications
Benner, R.E.; Gustafson, J.L.; Montry, G.R.
1999-08-10
A parallel computing system and method are disclosed having improved performance where a program is concurrently run on a plurality of nodes for reducing total processing time, each node having a processor, a memory, and a predetermined number of communication channels connected to the node and independently connected directly to other nodes. The present invention improves performance of the parallel computing system by providing a system which can provide efficient communication between the processors and between the system and input and output devices. A method is also disclosed which can locate defective nodes with the computing system. 15 figs.
Methods for operating parallel computing systems employing sequenced communications
Benner, Robert E.; Gustafson, John L.; Montry, Gary R.
1999-01-01
A parallel computing system and method having improved performance where a program is concurrently run on a plurality of nodes for reducing total processing time, each node having a processor, a memory, and a predetermined number of communication channels connected to the node and independently connected directly to other nodes. The present invention improves performance of performance of the parallel computing system by providing a system which can provide efficient communication between the processors and between the system and input and output devices. A method is also disclosed which can locate defective nodes with the computing system.
History Matching in Parallel Computational Environments
Steven Bryant; Sanjay Srinivasan; Alvaro Barrera; Yonghwee Kim; Sharad Yadav
2006-08-31
A novel methodology for delineating multiple reservoir domains for the purpose of history matching in a distributed computing environment has been proposed. A fully probabilistic approach to perturb permeability within the delineated zones is implemented. The combination of robust schemes for identifying reservoir zones and distributed computing significantly increase the accuracy and efficiency of the probabilistic approach. The information pertaining to the permeability variations in the reservoir that is contained in dynamic data is calibrated in terms of a deformation parameter rD. This information is merged with the prior geologic information in order to generate permeability models consistent with the observed dynamic data as well as the prior geology. The relationship between dynamic response data and reservoir attributes may vary in different regions of the reservoir due to spatial variations in reservoir attributes, well configuration, flow constrains etc. The probabilistic approach then has to account for multiple r{sub D} values in different regions of the reservoir. In order to delineate reservoir domains that can be characterized with different r{sub D} parameters, principal component analysis (PCA) of the Hessian matrix has been done. The Hessian matrix summarizes the sensitivity of the objective function at a given step of the history matching to model parameters. It also measures the interaction of the parameters in affecting the objective function. The basic premise of PC analysis is to isolate the most sensitive and least correlated regions. The eigenvectors obtained during the PCA are suitably scaled and appropriate grid block volume cut-offs are defined such that the resultant domains are neither too large (which increases interactions between domains) nor too small (implying ineffective history matching). The delineation of domains requires calculation of Hessian, which could be computationally costly and as well as restricts the current
History Matching in Parallel Computational Environments
Steven Bryant; Sanjay Srinivasan; Alvaro Barrera; Sharad Yadav
2005-10-01
A novel methodology for delineating multiple reservoir domains for the purpose of history matching in a distributed computing environment has been proposed. A fully probabilistic approach to perturb permeability within the delineated zones is implemented. The combination of robust schemes for identifying reservoir zones and distributed computing significantly increase the accuracy and efficiency of the probabilistic approach. The information pertaining to the permeability variations in the reservoir that is contained in dynamic data is calibrated in terms of a deformation parameter rD. This information is merged with the prior geologic information in order to generate permeability models consistent with the observed dynamic data as well as the prior geology. The relationship between dynamic response data and reservoir attributes may vary in different regions of the reservoir due to spatial variations in reservoir attributes, well configuration, flow constrains etc. The probabilistic approach then has to account for multiple r{sub D} values in different regions of the reservoir. In order to delineate reservoir domains that can be characterized with different rD parameters, principal component analysis (PCA) of the Hessian matrix has been done. The Hessian matrix summarizes the sensitivity of the objective function at a given step of the history matching to model parameters. It also measures the interaction of the parameters in affecting the objective function. The basic premise of PC analysis is to isolate the most sensitive and least correlated regions. The eigenvectors obtained during the PCA are suitably scaled and appropriate grid block volume cut-offs are defined such that the resultant domains are neither too large (which increases interactions between domains) nor too small (implying ineffective history matching). The delineation of domains requires calculation of Hessian, which could be computationally costly and as well as restricts the current approach to
Parallel Computational Fluid Dynamics: Current Status and Future Requirements
NASA Technical Reports Server (NTRS)
Simon, Horst D.; VanDalsem, William R.; Dagum, Leonardo; Kutler, Paul (Technical Monitor)
1994-01-01
One or the key objectives of the Applied Research Branch in the Numerical Aerodynamic Simulation (NAS) Systems Division at NASA Allies Research Center is the accelerated introduction of highly parallel machines into a full operational environment. In this report we discuss the performance results obtained from the implementation of some computational fluid dynamics (CFD) applications on the Connection Machine CM-2 and the Intel iPSC/860. We summarize some of the experiences made so far with the parallel testbed machines at the NAS Applied Research Branch. Then we discuss the long term computational requirements for accomplishing some of the grand challenge problems in computational aerosciences. We argue that only massively parallel machines will be able to meet these grand challenge requirements, and we outline the computer science and algorithm research challenges ahead.
Tutorial: Parallel Computing of Simulation Models for Risk Analysis.
Reilly, Allison C; Staid, Andrea; Gao, Michael; Guikema, Seth D
2016-10-01
Simulation models are widely used in risk analysis to study the effects of uncertainties on outcomes of interest in complex problems. Often, these models are computationally complex and time consuming to run. This latter point may be at odds with time-sensitive evaluations or may limit the number of parameters that are considered. In this article, we give an introductory tutorial focused on parallelizing simulation code to better leverage modern computing hardware, enabling risk analysts to better utilize simulation-based methods for quantifying uncertainty in practice. This article is aimed primarily at risk analysts who use simulation methods but do not yet utilize parallelization to decrease the computational burden of these models. The discussion is focused on conceptual aspects of embarrassingly parallel computer code and software considerations. Two complementary examples are shown using the languages MATLAB and R. A brief discussion of hardware considerations is located in the Appendix.
NASA Astrophysics Data System (ADS)
Mighell, Kenneth John
2011-11-01
The development of parallel-processing image-analysis codes is generally a challenging task that requires complicated choreography of interprocessor communications. If, however, the image-analysis algorithm is embarrassingly parallel, then the development of a parallel-processing implementation of that algorithm can be a much easier task to accomplish because, by definition, there is little need for communication between the compute processes. I describe the design, implementation, and performance of a parallel-processing image-analysis application, called CRBLASTER, which does cosmic-ray rejection of CCD (charge-coupled device) images using the embarrassingly-parallel L.A.COSMIC algorithm. CRBLASTER is written in C using the high-performance computing industry standard Message Passing Interface (MPI) library. The code has been designed to be used by research scientists who are familiar with C as a parallel-processing computational framework that enables the easy development of parallel-processing image-analysis programs based on embarrassingly-parallel algorithms. The CRBLASTER source code is freely available at the official application website at the National Optical Astronomy Observatory. Removing cosmic rays from a single 800x800 pixel Hubble Space Telescope WFPC2 image takes 44 seconds with the IRAF script lacos_im.cl running on a single core of an Apple Mac Pro computer with two 2.8-GHz quad-core Intel Xeon processors. CRBLASTER is 7.4 times faster processing the same image on a single core on the same machine. Processing the same image with CRBLASTER simultaneously on all 8 cores of the same machine takes 0.875 seconds -- which is a speedup factor of 50.3 times faster than the IRAF script. A detailed analysis is presented of the performance of CRBLASTER using between 1 and 57 processors on a low-power Tilera 700-MHz 64-core TILE64 processor.
Development of Parallel Architectures for Sensor Array Processing. Volume 1
1993-08-01
required for the DOA estimation [ 1-7]. The Multiple Signal Classification ( MUSIC ) [ 1] and the Estimation of Signal Parameters by Rotational...manifold and the estimated subspace. Although MUSIC is a high resolution algorithm, it has several drawbacks including the fact that complete knowledge of...thoroughly, MUSIC algorithm was selected to develop special purpose hardware for real time computation. Summary of the MUSIC algorithm is as follows
1997-03-01
to construct their computer codes (written largely in FORTRAN) to exploit this type of architecture. Towards the end of the 1980s, however, vector...for exploiting parallel architectures using both single and overset grids in conjunction with typical grid-based PDE solvers in general and FVTD...8217. Furthermore, it naturally exploits the means by which the electric and magnetic fields are related through the curl operators. Unfortunately, although stag
Parallel genetic architecture of parallel adaptive radiations in mimetic Heliconius butterflies.
Kronforst, Marcus R; Kapan, Durrell D; Gilbert, Lawrence E
2006-09-01
It is unknown whether homologous loci underlie the independent and parallel wing pattern radiations of Heliconius butterflies. By comparing the locations of color patterning genes on linkage maps we show that three loci that act similarly in the two radiations are in similar positions on homologous chromosomes.
Algorithmic support for commodity-based parallel computing systems.
Leung, Vitus Joseph; Bender, Michael A.; Bunde, David P.; Phillips, Cynthia Ann
2003-10-01
The Computational Plant or Cplant is a commodity-based distributed-memory supercomputer under development at Sandia National Laboratories. Distributed-memory supercomputers run many parallel programs simultaneously. Users submit their programs to a job queue. When a job is scheduled to run, it is assigned to a set of available processors. Job runtime depends not only on the number of processors but also on the particular set of processors assigned to it. Jobs should be allocated to localized clusters of processors to minimize communication costs and to avoid bandwidth contention caused by overlapping jobs. This report introduces new allocation strategies and performance metrics based on space-filling curves and one dimensional allocation strategies. These algorithms are general and simple. Preliminary simulations and Cplant experiments indicate that both space-filling curves and one-dimensional packing improve processor locality compared to the sorted free list strategy previously used on Cplant. These new allocation strategies are implemented in Release 2.0 of the Cplant System Software that was phased into the Cplant systems at Sandia by May 2002. Experimental results then demonstrated that the average number of communication hops between the processors allocated to a job strongly correlates with the job's completion time. This report also gives processor-allocation algorithms for minimizing the average number of communication hops between the assigned processors for grid architectures. The associated clustering problem is as follows: Given n points in {Re}d, find k points that minimize their average pairwise L{sub 1} distance. Exact and approximate algorithms are given for these optimization problems. One of these algorithms has been implemented on Cplant and will be included in Cplant System Software, Version 2.1, to be released. In more preliminary work, we suggest improvements to the scheduler separate from the allocator.
Evaluating parallel architectures for two real-time applications with 100 kHz repetition rate
Baldier, J.; Busson, Ph.; Charlot, C. ); Centro, S.; Pascoli, D ); Davis, E.E.; Ni, P. ); Denes, E.; Odor, G.; Vesztergombi ); Gheorghe, A.; Legrand, I. ); Klefenz, F.; Maenner, R.; Noffz, K.H.; Zoz, R. ); Lourens, W.; Taal, A. ); Malecki, P.; Sobala, A. ); Thielmann, A. ); Vermeulen, J. )
1993-02-01
In the context of Research and Development (R and D) activities for future hadron colliders, competitive implementations of real-time algorithms for feature extraction have been made on various forms of commercial pipelined and parallel architectures. The algorithms used for benchmarking serve for decision making and are of relative complexity; they are required to run with a repetition rate of 1,000 kHz in data sets of kilobyte size. Results are reported and discussed in detail. Among the commercially available architectures, pipelined image processing systems can compete with custom-designed architectures. General-purpose processors with systolic mesh connectivity can also be used. Massively parallel systems of the SIMD type (many processors executing the same program on different data) are less suitable in the presently marketed form.
Parallel Domain Decomposition Preconditioning for Computational Fluid Dynamics
NASA Technical Reports Server (NTRS)
Barth, Timothy J.; Chan, Tony F.; Tang, Wei-Pai; Kutler, Paul (Technical Monitor)
1998-01-01
This viewgraph presentation gives an overview of the parallel domain decomposition preconditioning for computational fluid dynamics. Details are given on some difficult fluid flow problems, stabilized spatial discretizations, and Newton's method for solving the discretized flow equations. Schur complement domain decomposition is described through basic formulation, simplifying strategies (including iterative subdomain and Schur complement solves, matrix element dropping, localized Schur complement computation, and supersparse computations), and performance evaluation.
Modeling groundwater flow on massively parallel computers
Ashby, S.F.; Falgout, R.D.; Fogwell, T.W.; Tompson, A.F.B.
1994-12-31
The authors will explore the numerical simulation of groundwater flow in three-dimensional heterogeneous porous media. An interdisciplinary team of mathematicians, computer scientists, hydrologists, and environmental engineers is developing a sophisticated simulation code for use on workstation clusters and MPPs. To date, they have concentrated on modeling flow in the saturated zone (single phase), which requires the solution of a large linear system. they will discuss their implementation of preconditioned conjugate gradient solvers. The preconditioners under consideration include simple diagonal scaling, s-step Jacobi, adaptive Chebyshev polynomial preconditioning, and multigrid. They will present some preliminary numerical results, including simulations of groundwater flow at the LLNL site. They also will demonstrate the code`s scalability.
Parallel and pipeline computation of fast unitary transforms
NASA Technical Reports Server (NTRS)
Fino, B. J.; Algazi, V. R.
1975-01-01
The letter discusses the parallel and pipeline organization of fast-unitary-transform algorithms such as the fast Fourier transform, and points out the efficiency of a combined parallel-pipeline processor of a transform such as the Haar transform, in which (2 to the n-th power) -1 hardware 'butterflies' generate a transform of order 2 to the n-th power every computation cycle.
DANTSYS/MPI: a system for 3-D deterministic transport on parallel architectures
Baker, R.S.; Alcouffe, R.E.
1996-12-31
Since 1994, we have been using a data parallel form of our deterministic transport code DANTSYS to perform time-independent fixed source and eigenvalue calculations on the CM-200`s at Los Alamos National Laboratory (LANL). Parallelization of the transport sweep is obtained by using a 2-D spatial decomposition which retains the ability to invert the source iteration equation in a single iteration (i.e., the diagonal plane sweep). We have now implemented a message passing version of DANTSYS, referred to as DANTSYS/MPI, on the Cray T3D installed at Los Alamos in 1995. By taking advantage of the SPMD (Single Program, Multiple Data) architecture of the Cray T3D, as well as its low latency communications network, we have managed to achieve grind times (time to solve a single cell in phase space) of less than 10 nanoseconds on the 512 PE (Processing Element) T3D, as opposed to typical grind times of 150-200 nanoseconds on a 2048 PE CM-200, or 300-400 nanoseconds on a single PE of a Cray Y-MP. In addition, we have also parallelized the Diffusion Synthetic Accelerator (DSA) equations which are used to accelerate the convergence of the transport equation. DANTSYS/MPI currently runs on traditional Cray PVP`s and the Cray T3D, and it`s computational kernel (Sweep3D) has been ported to and tested on an array of SGI SMP`s (Symmetric Memory Processors), a network of IBM 590 workstations, an IBM SP2, and the Intel TFLOPs machine at Sandia National Laboratory. This paper describes the implementation of DANTSYS/MPI on the Cray T3D, and presents a simple performance model which accurately predicts the grind time as a function of the number of PE`s and problem size, or scalability. This paper also describes the parallel implementation and performance of the elliptic solver used in DANTSYS/MPI for solving the synthetic acceleration equations.
Biomimetic design processes in architecture: morphogenetic and evolutionary computational design.
Menges, Achim
2012-03-01
Design computation has profound impact on architectural design methods. This paper explains how computational design enables the development of biomimetic design processes specific to architecture, and how they need to be significantly different from established biomimetic processes in engineering disciplines. The paper first explains the fundamental difference between computer-aided and computational design in architecture, as the understanding of this distinction is of critical importance for the research presented. Thereafter, the conceptual relation and possible transfer of principles from natural morphogenesis to design computation are introduced and the related developments of generative, feature-based, constraint-based, process-based and feedback-based computational design methods are presented. This morphogenetic design research is then related to exploratory evolutionary computation, followed by the presentation of two case studies focusing on the exemplary development of spatial envelope morphologies and urban block morphologies.
Toward an automated parallel computing environment for geosciences
NASA Astrophysics Data System (ADS)
Zhang, Huai; Liu, Mian; Shi, Yaolin; Yuen, David A.; Yan, Zhenzhen; Liang, Guoping
2007-08-01
Software for geodynamic modeling has not kept up with the fast growing computing hardware and network resources. In the past decade supercomputing power has become available to most researchers in the form of affordable Beowulf clusters and other parallel computer platforms. However, to take full advantage of such computing power requires developing parallel algorithms and associated software, a task that is often too daunting for geoscience modelers whose main expertise is in geosciences. We introduce here an automated parallel computing environment built on open-source algorithms and libraries. Users interact with this computing environment by specifying the partial differential equations, solvers, and model-specific properties using an English-like modeling language in the input files. The system then automatically generates the finite element codes that can be run on distributed or shared memory parallel machines. This system is dynamic and flexible, allowing users to address different problems in geosciences. It is capable of providing web-based services, enabling users to generate source codes online. This unique feature will facilitate high-performance computing to be integrated with distributed data grids in the emerging cyber-infrastructures for geosciences. In this paper we discuss the principles of this automated modeling environment and provide examples to demonstrate its versatility.
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.
CFD Analysis and Design Optimization Using Parallel Computers
NASA Technical Reports Server (NTRS)
Martinelli, Luigi; Alonso, Juan Jose; Jameson, Antony; Reuther, James
1997-01-01
A versatile and efficient multi-block method is presented for the simulation of both steady and unsteady flow, as well as aerodynamic design optimization of complete aircraft configurations. The compressible Euler and Reynolds Averaged Navier-Stokes (RANS) equations are discretized using a high resolution scheme on body-fitted structured meshes. An efficient multigrid implicit scheme is implemented for time-accurate flow calculations. Optimum aerodynamic shape design is achieved at very low cost using an adjoint formulation. The method is implemented on parallel computing systems using the MPI message passing interface standard to ensure portability. The results demonstrate that, by combining highly efficient algorithms with parallel computing, it is possible to perform detailed steady and unsteady analysis as well as automatic design for complex configurations using the present generation of parallel computers.
Multithreaded Model for Dynamic Load Balancing Parallel Adaptive PDE Computations
NASA Technical Reports Server (NTRS)
Chrisochoides, Nikos
1995-01-01
We present a multithreaded model for the dynamic load-balancing of numerical, adaptive computations required for the solution of Partial Differential Equations (PDE's) on multiprocessors. Multithreading is used as a means of exploring concurrency in the processor level in order to tolerate synchronization costs inherent to traditional (non-threaded) parallel adaptive PDE solvers. Our preliminary analysis for parallel, adaptive PDE solvers indicates that multithreading can be used an a mechanism to mask overheads required for the dynamic balancing of processor workloads with computations required for the actual numerical solution of the PDE's. Also, multithreading can simplify the implementation of dynamic load-balancing algorithms, a task that is very difficult for traditional data parallel adaptive PDE computations. Unfortunately, multithreading does not always simplify program complexity, often makes code re-usability not an easy task, and increases software complexity.
Parallel grid generation algorithm for distributed memory computers
NASA Technical Reports Server (NTRS)
Moitra, Stuti; Moitra, Anutosh
1994-01-01
A parallel grid-generation algorithm and its implementation on the Intel iPSC/860 computer are described. The grid-generation scheme is based on an algebraic formulation of homotopic relations. Methods for utilizing the inherent parallelism of the grid-generation scheme are described, and implementation of multiple levELs of parallelism on multiple instruction multiple data machines are indicated. The algorithm is capable of providing near orthogonality and spacing control at solid boundaries while requiring minimal interprocessor communications. Results obtained on the Intel hypercube for a blended wing-body configuration are used to demonstrate the effectiveness of the algorithm. Fortran implementations bAsed on the native programming model of the iPSC/860 computer and the Express system of software tools are reported. Computational gains in execution time speed-up ratios are given.
Single Circuit Parallel Computing with Phonons through Magneto-acoustics
NASA Astrophysics Data System (ADS)
Sklan, Sophia; Grossman, Jeffrey
2013-03-01
Phononic computing - the use of (typically thermal) vibrations for information processing - is a nascent technology; its capabilities are still being discovered. We analyze an alternative form of phononic computing inspired by optical, rather than electronic, computing. Using the acoustic Faraday effect, we design a phonon gyrator and thereby a means of performing computation through the manipulation of polarization in transverse phonon currents. Moreover, we establish that our gyrators act as generalized transistors and can construct digital logic gates. Exploiting the wave nature of phonons and the similarity of our logic gates, we demonstrate parallel computation within a single circuit, an effect presently unique to phonons. Finally, a generic method of designing these parallel circuits is introduced and used to analyze the feasibility of magneto-acoustic materials in realizing these circuits. This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No. 1122374.
A Highly Parallel Implementation of K-Means for Multithreaded Architecture
Mackey, Patrick S.; Feo, John T.; Wong, Pak C.; Chen, Yousu
2011-04-06
We present a parallel implementation of the popular k-means clustering algorithm for massively multithreaded computer systems, as well as a parallelized version of the KKZ seed selection algorithm. We demonstrate that as system size increases, sequential seed selection can become a bottleneck. We also present an early attempt at parallelizing k-means that highlights critical performance issues when programming massively multithreaded systems. For our case studies, we used data collected from electric power simulations and run on the Cray XMT.
Scalability of preconditioners as a strategy for parallel computation of compressible fluid flow
Hansen, G.A.
1996-05-01
Parallel implementations of a Newton-Krylov-Schwarz algorithm are used to solve a model problem representing low Mach number compressible fluid flow over a backward-facing step. The Mach number is specifically selected to result in a numerically {open_quote}stiff{close_quotes} matrix problem, based on an implicit finite volume discretization of the compressible 2D Navier-Stokes/energy equations using primitive variables. Newton`s method is used to linearize the discrete system, and a preconditioned Krylov projection technique is used to solve the resulting linear system. Domain decomposition enables the development of a global preconditioner via the parallel construction of contributions derived from subdomains. Formation of the global preconditioner is based upon additive and multiplicative Schwarz algorithms, with and without subdomain overlap. The degree of parallelism of this technique is further enhanced with the use of a matrix-free approximation for the Jacobian used in the Krylov technique (in this case, GMRES(k)). Of paramount interest to this study is the implementation and optimization of these techniques on parallel shared-memory hardware, namely the Cray C90 and SGI Challenge architectures. These architectures were chosen as representative and commonly available to researchers interested in the solution of problems of this type. The Newton-Krylov-Schwarz solution technique is increasingly being investigated for computational fluid dynamics (CFD) applications due to the advantages of full coupling of all variables and equations, rapid non-linear convergence, and moderate memory requirements. A parallel version of this method that scales effectively on the above architectures would be extremely attractive to practitioners, resulting in efficient, cost-effective, parallel solutions exhibiting the benefits of the solution technique.
A heterogeneous hierarchical architecture for real-time computing
Skroch, D.A.; Fornaro, R.J.
1988-12-01
The need for high-speed data acquisition and control algorithms has prompted continued research in the area of multiprocessor systems and related programming techniques. The result presented here is a unique hardware and software architecture for high-speed real-time computer systems. The implementation of a prototype of this architecture has required the integration of architecture, operating systems and programming languages into a cohesive unit. This report describes a Heterogeneous Hierarchial Architecture for Real-Time (H{sup 2} ART) and system software for program loading and interprocessor communication.
Efficient Helicopter Aerodynamic and Aeroacoustic Predictions on Parallel Computers
NASA Technical Reports Server (NTRS)
Wissink, Andrew M.; Lyrintzis, Anastasios S.; Strawn, Roger C.; Oliker, Leonid; Biswas, Rupak
1996-01-01
This paper presents parallel implementations of two codes used in a combined CFD/Kirchhoff methodology to predict the aerodynamics and aeroacoustics properties of helicopters. The rotorcraft Navier-Stokes code, TURNS, computes the aerodynamic flowfield near the helicopter blades and the Kirchhoff acoustics code computes the noise in the far field, using the TURNS solution as input. The overall parallel strategy adds MPI message passing calls to the existing serial codes to allow for communication between processors. As a result, the total code modifications required for parallel execution are relatively small. The biggest bottleneck in running the TURNS code in parallel comes from the LU-SGS algorithm that solves the implicit system of equations. We use a new hybrid domain decomposition implementation of LU-SGS to obtain good parallel performance on the SP-2. TURNS demonstrates excellent parallel speedups for quasi-steady and unsteady three-dimensional calculations of a helicopter blade in forward flight. The execution rate attained by the code on 114 processors is six times faster than the same cases run on one processor of the Cray C-90. The parallel Kirchhoff code also shows excellent parallel speedups and fast execution rates. As a performance demonstration, unsteady acoustic pressures are computed at 1886 far-field observer locations for a sample acoustics problem. The calculation requires over two hundred hours of CPU time on one C-90 processor but takes only a few hours on 80 processors of the SP2. The resultant far-field acoustic field is analyzed with state of-the-art audio and video rendering of the propagating acoustic signals.
Small file aggregation in a parallel computing system
Faibish, Sorin; Bent, John M.; Tzelnic, Percy; Grider, Gary; Zhang, Jingwang
2014-09-02
Techniques are provided for small file aggregation in a parallel computing system. An exemplary method for storing a plurality of files generated by a plurality of processes in a parallel computing system comprises aggregating the plurality of files into a single aggregated file; and generating metadata for the single aggregated file. The metadata comprises an offset and a length of each of the plurality of files in the single aggregated file. The metadata can be used to unpack one or more of the files from the single aggregated file.
Method for implementation of recursive hierarchical segmentation on parallel computers
NASA Technical Reports Server (NTRS)
Tilton, James C. (Inventor)
2005-01-01
A method, computer readable storage, and apparatus for implementing a recursive hierarchical segmentation algorithm on a parallel computing platform. The method includes setting a bottom level of recursion that defines where a recursive division of an image into sections stops dividing, and setting an intermediate level of recursion where the recursive division changes from a parallel implementation into a serial implementation. The segmentation algorithm is implemented according to the set levels. The method can also include setting a convergence check level of recursion with which the first level of recursion communicates with when performing a convergence check.
Parallel and Distributed Computational Fluid Dynamics: Experimental Results and Challenges
NASA Technical Reports Server (NTRS)
Djomehri, Mohammad Jahed; Biswas, R.; VanderWijngaart, R.; Yarrow, M.
2000-01-01
This paper describes several results of parallel and distributed computing using a large scale production flow solver program. A coarse grained parallelization based on clustering of discretization grids combined with partitioning of large grids for load balancing is presented. An assessment is given of its performance on distributed and distributed-shared memory platforms using large scale scientific problems. An experiment with this solver, adapted to a Wide Area Network execution environment is presented. We also give a comparative performance assessment of computation and communication times on both the tightly and loosely-coupled machines.
Implicit schemes and parallel computing in unstructured grid CFD
NASA Technical Reports Server (NTRS)
Venkatakrishnam, V.
1995-01-01
The development of implicit schemes for obtaining steady state solutions to the Euler and Navier-Stokes equations on unstructured grids is outlined. Applications are presented that compare the convergence characteristics of various implicit methods. Next, the development of explicit and implicit schemes to compute unsteady flows on unstructured grids is discussed. Next, the issues involved in parallelizing finite volume schemes on unstructured meshes in an MIMD (multiple instruction/multiple data stream) fashion are outlined. Techniques for partitioning unstructured grids among processors and for extracting parallelism in explicit and implicit solvers are discussed. Finally, some dynamic load balancing ideas, which are useful in adaptive transient computations, are presented.
High Performance Input/Output for Parallel Computer Systems
NASA Technical Reports Server (NTRS)
Ligon, W. B.
1996-01-01
The goal of our project is to study the I/O characteristics of parallel applications used in Earth Science data processing systems such as Regional Data Centers (RDCs) or EOSDIS. Our approach is to study the runtime behavior of typical programs and the effect of key parameters of the I/O subsystem both under simulation and with direct experimentation on parallel systems. Our three year activity has focused on two items: developing a test bed that facilitates experimentation with parallel I/O, and studying representative programs from the Earth science data processing application domain. The Parallel Virtual File System (PVFS) has been developed for use on a number of platforms including the Tiger Parallel Architecture Workbench (TPAW) simulator, The Intel Paragon, a cluster of DEC Alpha workstations, and the Beowulf system (at CESDIS). PVFS provides considerable flexibility in configuring I/O in a UNIX- like environment. Access to key performance parameters facilitates experimentation. We have studied several key applications fiom levels 1,2 and 3 of the typical RDC processing scenario including instrument calibration and navigation, image classification, and numerical modeling codes. We have also considered large-scale scientific database codes used to organize image data.
Real-Time Cognitive Computing Architecture for Data Fusion in a Dynamic Environment
NASA Technical Reports Server (NTRS)
Duong, Tuan A.; Duong, Vu A.
2012-01-01
A novel cognitive computing architecture is conceptualized for processing multiple channels of multi-modal sensory data streams simultaneously, and fusing the information in real time to generate intelligent reaction sequences. This unique architecture is capable of assimilating parallel data streams that could be analog, digital, synchronous/asynchronous, and could be programmed to act as a knowledge synthesizer and/or an "intelligent perception" processor. In this architecture, the bio-inspired models of visual pathway and olfactory receptor processing are combined as processing components, to achieve the composite function of "searching for a source of food while avoiding the predator." The architecture is particularly suited for scene analysis from visual data and odorant.
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.
Archer, Charles J.; Blocksome, Michael A.; Ratterman, Joseph D.; Smith, Brian E.
2016-03-15
Processing data communications events in a parallel active messaging interface (`PAMI`) of a parallel computer that includes compute nodes that execute a parallel application, with the PAMI including data communications endpoints, and the endpoints are coupled for data communications through the PAMI and through other data communications resources, including determining by an advance function that there are no actionable data communications events pending for its context, placing by the advance function its thread of execution into a wait state, waiting for a subsequent data communications event for the context; responsive to occurrence of a subsequent data communications event for the context, awakening by the thread from the wait state; and processing by the advance function the subsequent data communications event now pending for the context.
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.
A design methodology for portable software on parallel computers
NASA Technical Reports Server (NTRS)
Nicol, David M.; Miller, Keith W.; Chrisman, Dan A.
1993-01-01
This final report for research that was supported by grant number NAG-1-995 documents our progress in addressing two difficulties in parallel programming. The first difficulty is developing software that will execute quickly on a parallel computer. The second difficulty is transporting software between dissimilar parallel computers. In general, we expect that more hardware-specific information will be included in software designs for parallel computers than in designs for sequential computers. This inclusion is an instance of portability being sacrificed for high performance. New parallel computers are being introduced frequently. Trying to keep one's software on the current high performance hardware, a software developer almost continually faces yet another expensive software transportation. The problem of the proposed research is to create a design methodology that helps designers to more precisely control both portability and hardware-specific programming details. The proposed research emphasizes programming for scientific applications. We completed our study of the parallelizability of a subsystem of the NASA Earth Radiation Budget Experiment (ERBE) data processing system. This work is summarized in section two. A more detailed description is provided in Appendix A ('Programming Practices to Support Eventual Parallelism'). Mr. Chrisman, a graduate student, wrote and successfully defended a Ph.D. dissertation proposal which describes our research associated with the issues of software portability and high performance. The list of research tasks are specified in the proposal. The proposal 'A Design Methodology for Portable Software on Parallel Computers' is summarized in section three and is provided in its entirety in Appendix B. We are currently studying a proposed subsystem of the NASA Clouds and the Earth's Radiant Energy System (CERES) data processing system. This software is the proof-of-concept for the Ph.D. dissertation. We have implemented and measured
Dynamic Load-Balancing for Distributed Heterogeneous Computing of Parallel CFD Problems
NASA Technical Reports Server (NTRS)
Ecer, A.; Chien, Y. P.; Boenisch, T.; Akay, H. U.
2000-01-01
The developed methodology is aimed at improving the efficiency of executing block-structured algorithms on parallel, distributed, heterogeneous computers. The basic approach of these algorithms is to divide the flow domain into many sub- domains called blocks, and solve the governing equations over these blocks. Dynamic load balancing problem is defined as the efficient distribution of the blocks among the available processors over a period of several hours of computations. In environments with computers of different architecture, operating systems, CPU speed, memory size, load, and network speed, balancing the loads and managing the communication between processors becomes crucial. Load balancing software tools for mutually dependent parallel processes have been created to efficiently utilize an advanced computation environment and algorithms. These tools are dynamic in nature because of the chances in the computer environment during execution time. More recently, these tools were extended to a second operating system: NT. In this paper, the problems associated with this application will be discussed. Also, the developed algorithms were combined with the load sharing capability of LSF to efficiently utilize workstation clusters for parallel computing. Finally, results will be presented on running a NASA based code ADPAC to demonstrate the developed tools for dynamic load balancing.
Parallel-vector computation for CSI-design code
NASA Technical Reports Server (NTRS)
Nguyen, Duc T.
1990-01-01
Computational aspects of Control-Structure Interaction (CSI) DESIGN code is reviewed. Numerical intensive computation portions of CSI-DESIGN code were identified. Improvements in computational speed for the CSI-DESIGN code can be achieved by exploiting parallel and vector capabilities offered by modern computers, such as the Alliant, Convex, Cray-2, and Cray-YMP. Four options to generate the coefficient stiffness matrix and to solve the system of linear, simultaneous equations are currently available in the CSI-DESIGN code. A preprocessor to use RCM (Reverse Cuthill-Mackee) algorithm for bandwidth minimization was also developed for the CSI-DESIGN code. Preliminary results obtained by solving a small-scale, 97 node CSI finite element model (for eigensolution) have indicated that this new CSI-DESIGN code is 5 to 6 times faster (using 1 Alliant processor) than the old version of CSI-DESIGN code. This speed-up was achieved due to the RCM algorithm and the use of a new skyline solver. Efforts are underway to further improve the vector speed for CSI-DESIGN code, to evaluate its performance on a larger scale CSI model (such as phase zero CSI model) to make the code run efficiently on multiprocessor, parallel computer environment, and to make the code portable among different parallel computers available at NASA LaRC, such as Alliant, Convex, and Cray computers.
Lattice gauge theory on the Intel parallel scientific computer
NASA Astrophysics Data System (ADS)
Gottlieb, Steven
1990-08-01
Intel Scientific Computers (ISC) has just started producing its third general of parallel computer, the iPSC/860. Based on the i860 chip that has a peak performance of 80 Mflops and with a current maximum of 128 nodes, this computer should achieve speeds in excess of those obtainable on conventional vector supercomputers. The hardware, software and computing techniques appropriate for lattice gauge theory calculations are described. The differences between a staggered fermion conjugate gradient program written under CANOPY and for the iPSC are detailed.
Integrated computer control system architectural overview
Van Arsdall, P.
1997-06-18
This overview introduces the NIF Integrated Control System (ICCS) architecture. The design is abstract to allow the construction of many similar applications from a common framework. This summary lays the essential foundation for understanding the model-based engineering approach used to execute the design.
Solving tridiagonal linear systems on the Butterfly parallel computer
Kumar, S.P.
1989-01-01
A parallel block partitioning method to solve a tri-diagonal system of linear equations is adapted to the BBN Butterfly multiprocessor. A performance analysis of the programming experiments on the 32-node Butterfly is presented. An upper bound on the number of processors to achieve the best performance with this method is derived. The computational results verify the theoretical speedup and efficiency results of the parallel algorithm over its serial counterpart. Also included is a study comparing performance runs of the same code on the Butterfly processor with a hardware floating point unit and on one with a software floating point facility. The total parallel time of the given code is considerably reduced by making use of the hardware floating point facility whereas the speedup and efficiency of the parallel program considerably improve on the system with software floating point capability. The achieved results are shown to be within 82% to 90% of the predicted performance.
The science of computing - The evolution of parallel processing
NASA Technical Reports Server (NTRS)
Denning, P. J.
1985-01-01
The present paper is concerned with the approaches to be employed to overcome the set of limitations in software technology which impedes currently an effective use of parallel hardware technology. The process required to solve the arising problems is found to involve four different stages. At the present time, Stage One is nearly finished, while Stage Two is under way. Tentative explorations are beginning on Stage Three, and Stage Four is more distant. In Stage One, parallelism is introduced into the hardware of a single computer, which consists of one or more processors, a main storage system, a secondary storage system, and various peripheral devices. In Stage Two, parallel execution of cooperating programs on different machines becomes explicit, while in Stage Three, new languages will make parallelism implicit. In Stage Four, there will be very high level user interfaces capable of interacting with scientists at the same level of abstraction as scientists do with each other.
A Low-Cost, Portable, Parallel Computing Cluster
NASA Astrophysics Data System (ADS)
Bullock, Daniel; Poppeliers, Christian; Allen, Charles
2006-10-01
Research in modern physical sciences has placed an increasing demand on computers for complex algorithms that push the limits of consumer personal computers. Parallel supercomputers are often required for large-scale algorithms, however the cost of these systems can be prohibitive. The purpose of this project is to construct a low-cost, portable, parallel computer system as an alternative to large-scale supercomputers, using Commercial Off The Shelf (COTS) components. These components can be networked together to allow processors to communicate with one another for faster computations. The overall design of this system is based on the development of ``Little Fe'' at Contra Costa College in San Pablo, California. Revisions to this design include improved design components, smaller physical size, easier transportation, less wiring, and a single AC power supply.
Parallel algorithms for computation of the manipulator inertia matrix
NASA Technical Reports Server (NTRS)
Amin-Javaheri, Masoud; Orin, David E.
1989-01-01
The development of an O(log2N) parallel algorithm for the manipulator inertia matrix is presented. It is based on the most efficient serial algorithm which uses the composite rigid body method. Recursive doubling is used to reformulate the linear recurrence equations which are required to compute the diagonal elements of the matrix. It results in O(log2N) levels of computation. Computation of the off-diagonal elements involves N linear recurrences of varying-size and a new method, which avoids redundant computation of position and orientation transforms for the manipulator, is developed. The O(log2N) algorithm is presented in both equation and graphic forms which clearly show the parallelism inherent in the algorithm.
Parallelization of Finite Element Analysis Codes Using Heterogeneous Distributed Computing
NASA Technical Reports Server (NTRS)
Ozguner, Fusun
1996-01-01
Performance gains in computer design are quickly consumed as users seek to analyze larger problems to a higher degree of accuracy. Innovative computational methods, such as parallel and distributed computing, seek to multiply the power of existing hardware technology to satisfy the computational demands of large applications. In the early stages of this project, experiments were performed using two large, coarse-grained applications, CSTEM and METCAN. These applications were parallelized on an Intel iPSC/860 hypercube. It was found that the overall speedup was very low, due to large, inherently sequential code segments present in the applications. The overall execution time T(sub par), of the application is dependent on these sequential segments. If these segments make up a significant fraction of the overall code, the application will have a poor speedup measure.
NASA Astrophysics Data System (ADS)
Mighell, Kenneth John
2010-10-01
The development of parallel-processing image-analysis codes is generally a challenging task that requires complicated choreography of interprocessor communications. If, however, the image-analysis algorithm is embarrassingly parallel, then the development of a parallel-processing implementation of that algorithm can be a much easier task to accomplish because, by definition, there is little need for communication between the compute processes. I describe the design, implementation, and performance of a parallel-processing image-analysis application, called crblaster, which does cosmic-ray rejection of CCD images using the embarrassingly parallel l.a.cosmic algorithm. crblaster is written in C using the high-performance computing industry standard Message Passing Interface (MPI) library. crblaster uses a two-dimensional image partitioning algorithm that partitions an input image into N rectangular subimages of nearly equal area; the subimages include sufficient additional pixels along common image partition edges such that the need for communication between computer processes is eliminated. The code has been designed to be used by research scientists who are familiar with C as a parallel-processing computational framework that enables the easy development of parallel-processing image-analysis programs based on embarrassingly parallel algorithms. The crblaster source code is freely available at the official application Web site at the National Optical Astronomy Observatory. Removing cosmic rays from a single 800 × 800 pixel Hubble Space Telescope WFPC2 image takes 44 s with the IRAF script lacos_im.cl running on a single core of an Apple Mac Pro computer with two 2.8 GHz quad-core Intel Xeon processors. crblaster is 7.4 times faster when processing the same image on a single core on the same machine. Processing the same image with crblaster simultaneously on all eight cores of the same machine takes 0.875 s—which is a speedup factor of 50.3 times faster than the
Variable-Complexity Multidisciplinary Optimization on Parallel Computers
NASA Technical Reports Server (NTRS)
Grossman, Bernard; Mason, William H.; Watson, Layne T.; Haftka, Raphael T.
1998-01-01
This report covers work conducted under grant NAG1-1562 for the NASA High Performance Computing and Communications Program (HPCCP) from December 7, 1993, to December 31, 1997. The objective of the research was to develop new multidisciplinary design optimization (MDO) techniques which exploit parallel computing to reduce the computational burden of aircraft MDO. The design of the High-Speed Civil Transport (HSCT) air-craft was selected as a test case to demonstrate the utility of our MDO methods. The three major tasks of this research grant included: development of parallel multipoint approximation methods for the aerodynamic design of the HSCT, use of parallel multipoint approximation methods for structural optimization of the HSCT, mathematical and algorithmic development including support in the integration of parallel computation for items (1) and (2). These tasks have been accomplished with the development of a response surface methodology that incorporates multi-fidelity models. For the aerodynamic design we were able to optimize with up to 20 design variables using hundreds of expensive Euler analyses together with thousands of inexpensive linear theory simulations. We have thereby demonstrated the application of CFD to a large aerodynamic design problem. For the predicting structural weight we were able to combine hundreds of structural optimizations of refined finite element models with thousands of optimizations based on coarse models. Computations have been carried out on the Intel Paragon with up to 128 nodes. The parallel computation allowed us to perform combined aerodynamic-structural optimization using state of the art models of a complex aircraft configurations.
Hybrid VLSI/QCA Architecture for Computing FFTs
NASA Technical Reports Server (NTRS)
Fijany, Amir; Toomarian, Nikzad; Modarres, Katayoon; Spotnitz, Matthew
2003-01-01
A data-processor architecture that would incorporate elements of both conventional very-large-scale integrated (VLSI) circuitry and quantum-dot cellular automata (QCA) has been proposed to enable the highly parallel and systolic computation of fast Fourier transforms (FFTs). The proposed circuit would complement the QCA-based circuits described in several prior NASA Tech Briefs articles, namely Implementing Permutation Matrices by Use of Quantum Dots (NPO-20801), Vol. 25, No. 10 (October 2001), page 42; Compact Interconnection Networks Based on Quantum Dots (NPO-20855) Vol. 27, No. 1 (January 2003), page 32; and Bit-Serial Adder Based on Quantum Dots (NPO-20869), Vol. 27, No. 1 (January 2003), page 35. The cited prior articles described the limitations of very-large-scale integrated (VLSI) circuitry and the major potential advantage afforded by QCA. To recapitulate: In a VLSI circuit, signal paths that are required not to interact with each other must not cross in the same plane. In contrast, for reasons too complex to describe in the limited space available for this article, suitably designed and operated QCAbased signal paths that are required not to interact with each other can nevertheless be allowed to cross each other in the same plane without adverse effect. In principle, this characteristic could be exploited to design compact, coplanar, simple (relative to VLSI) QCA-based networks to implement complex, advanced interconnection schemes.
Parallelization of implicit finite difference schemes in computational fluid dynamics
NASA Technical Reports Server (NTRS)
Decker, Naomi H.; Naik, Vijay K.; Nicoules, Michel
1990-01-01
Implicit finite difference schemes are often the preferred numerical schemes in computational fluid dynamics, requiring less stringent stability bounds than the explicit schemes. Each iteration in an implicit scheme involves global data dependencies in the form of second and higher order recurrences. Efficient parallel implementations of such iterative methods are considerably more difficult and non-intuitive. The parallelization of the implicit schemes that are used for solving the Euler and the thin layer Navier-Stokes equations and that require inversions of large linear systems in the form of block tri-diagonal and/or block penta-diagonal matrices is discussed. Three-dimensional cases are emphasized and schemes that minimize the total execution time are presented. Partitioning and scheduling schemes for alleviating the effects of the global data dependencies are described. An analysis of the communication and the computation aspects of these methods is presented. The effect of the boundary conditions on the parallel schemes is also discussed.
Measuring performance of parallel computers. Progress report, 1989
Sullivan, F.
1994-07-01
Performance Measurement - the authors have developed a taxonomy of parallel algorithms based on data motion and example applications have been coded for each class of the taxonomy. Computational benchmark kernels have been extracted for several applications, and detailed measurements have been performed. Algorithms for Massively Parallel SIMD machines - measurement results and computational experiences indicate that top performance will be achieved by `iteration` type algorithms running on massively parallel SIMD machines. Reformulation as iteration may entail unorthodox approaches based on probabilistic methods. The authors have developed such methods for some applications. Here they discuss their approach to performance measurement, describe the taxonomy and measurements which have been made, and report on some general conclusions which can be drawn from the results of the measurements.
Element-topology-independent preconditioners for parallel finite element computations
NASA Technical Reports Server (NTRS)
Park, K. C.; Alexander, Scott
1992-01-01
A family of preconditioners for the solution of finite element equations are presented, which are element-topology independent and thus can be applicable to element order-free parallel computations. A key feature of the present preconditioners is the repeated use of element connectivity matrices and their left and right inverses. The properties and performance of the present preconditioners are demonstrated via beam and two-dimensional finite element matrices for implicit time integration computations.
Smart Memory Systems: Polymorphous Computing Architectures
2007-11-02
optimal parallel regions. Our hardware support is described in a paper presented at CGO titled "TEST: A Tracer for Extracting Speculative Threads". To...Speedups of 3 to 4 are seen on floating-point, 2 to 3 on multimedia and 1.5 to 2.5 on integer benchmarks. This work 7 was reported in an ISCA paper ...titled “The Jrpm System for Dynamically Parallelizing Java Programs.” This paper was selected by IEEE Micro Magazine as a “Top Pick of 2003” which
A Parallel Computational Fluid Dynamics Unstructured Grid Generator
1993-12-01
Vol 11. 953-961. Philadelphia: SIAM, 1993. Holey, J. Andrew and Oscar H. Ibarra . "Triangulation, Veronoi Diagram, and Convex Hull in k-Space on Mesh...rIdhner, Rainald, Jose Camberos, and Marshall Merriam. "Parallel Unstructured Grid Generation," in Unstructured Scientific Computation on Scalable
Hardware packet pacing using a DMA in a parallel computer
Chen, Dong; Heidelberger, Phillip; Vranas, Pavlos
2013-08-13
Method and system for hardware packet pacing using a direct memory access controller in a parallel computer which, in one aspect, keeps track of a total number of bytes put on the network as a result of a remote get operation, using a hardware token counter.
Streamline Integration Using MPI-Hybrid Parallelism on a Large Multicore Architecture
Garth, Christoph
2011-01-01
Streamline computation in a very large vector field data set represents a significant challenge due to the nonlocal and data-dependent nature of streamline integration. In this paper, we conduct a study of the performance characteristics of hybrid parallel programming and execution as applied to streamline integration on a large, multicore platform. With multicore processors now prevalent in clusters and supercomputers, there is a need to understand the impact of these hybrid systems in order to make the best implementation choice. We use two MPI-based distribution approaches based on established parallelization paradigms, parallelize over seeds and parallelize over blocks, and present a novel MPI-hybrid algorithm for each approach to compute streamlines. Our findings indicate that the work sharing between cores in the proposed MPI-hybrid parallel implementation results in much improved performance and consumes less communication and I/O bandwidth than a traditional, nonhybrid distributed implementation.
Streamline Integration using MPI-Hybrid Parallelism on a Large Multi-Core Architecture
Camp, David; Garth, Christoph; Childs, Hank; Pugmire, Dave; Joy, Kenneth I.
2010-11-01
Streamline computation in a very large vector field data set represents a significant challenge due to the non-local and datadependentnature of streamline integration. In this paper, we conduct a study of the performance characteristics of hybrid parallel programmingand execution as applied to streamline integration on a large, multicore platform. With multi-core processors now prevalent in clustersand supercomputers, there is a need to understand the impact of these hybrid systems in order to make the best implementation choice.We use two MPI-based distribution approaches based on established parallelization paradigms, parallelize-over-seeds and parallelize-overblocks,and present a novel MPI-hybrid algorithm for each approach to compute streamlines. Our findings indicate that the work sharing betweencores in the proposed MPI-hybrid parallel implementation results in much improved performance and consumes less communication andI/O bandwidth than a traditional, non-hybrid distributed implementation.
Fencing data transfers in a parallel active messaging interface of a parallel computer
Blocksome, Michael A.; Mamidala, Amith R.
2015-06-09
Fencing data transfers in a parallel active messaging interface (`PAMI`) of a parallel computer, the PAMI including data communications endpoints, each endpoint including a specification of data communications parameters for a thread of execution on a compute node, including specifications of a client, a context, and a task; the compute nodes coupled for data communications through the PAMI and through data communications resources including at least one segment of shared random access memory; including initiating execution through the PAMI of an ordered sequence of active SEND instructions for SEND data transfers between two endpoints, effecting deterministic SEND data transfers through a segment of shared memory; and executing through the PAMI, with no FENCE accounting for SEND data transfers, an active FENCE instruction, the FENCE instruction completing execution only after completion of all SEND instructions initiated prior to execution of the FENCE instruction for SEND data transfers between the two endpoints.
Fencing data transfers in a parallel active messaging interface of a parallel computer
Blocksome, Michael A.; Mamidala, Amith R.
2015-06-02
Fencing data transfers in a parallel active messaging interface (`PAMI`) of a parallel computer, the PAMI including data communications endpoints, each endpoint including a specification of data communications parameters for a thread of execution on a compute node, including specifications of a client, a context, and a task; the compute nodes coupled for data communications through the PAMI and through data communications resources including at least one segment of shared random access memory; including initiating execution through the PAMI of an ordered sequence of active SEND instructions for SEND data transfers between two endpoints, effecting deterministic SEND data transfers through a segment of shared memory; and executing through the PAMI, with no FENCE accounting for SEND data transfers, an active FENCE instruction, the FENCE instruction completing execution only after completion of all SEND instructions initiated prior to execution of the FENCE instruction for SEND data transfers between the two endpoints.
Fencing data transfers in a parallel active messaging interface of a parallel computer
Blocksome, Michael A.; Mamidala, Amith R.
2015-06-30
Fencing data transfers in a parallel active messaging interface (`PAMI`) of a parallel computer, the PAMI including data communications endpoints, each endpoint comprising a specification of data communications parameters for a thread of execution on a compute node, including specifications of a client, a context, and a task, the compute nodes coupled for data communications through the PAMI and through data communications resources including a deterministic data communications network, including initiating execution through the PAMI of an ordered sequence of active SEND instructions for SEND data transfers between two endpoints, effecting deterministic SEND data transfers; and executing through the PAMI, with no FENCE accounting for SEND data transfers, an active FENCE instruction, the FENCE instruction completing execution only after completion of all SEND instructions initiated prior to execution of the FENCE instruction for SEND data transfers between the two endpoints.
Fencing data transfers in a parallel active messaging interface of a parallel computer
Blocksome, Michael A.; Mamidala, Amith R.
2015-08-11
Fencing data transfers in a parallel active messaging interface (`PAMI`) of a parallel computer, the PAMI including data communications endpoints, each endpoint comprising a specification of data communications parameters for a thread of execution on a compute node, including specifications of a client, a context, and a task, the compute nodes coupled for data communications through the PAMI and through data communications resources including a deterministic data communications network, including initiating execution through the PAMI of an ordered sequence of active SEND instructions for SEND data transfers between two endpoints, effecting deterministic SEND data transfers; and executing through the PAMI, with no FENCE accounting for SEND data transfers, an active FENCE instruction, the FENCE instruction completing execution only after completion of all SEND instructions initiated prior to execution of the FENCE instruction for SEND data transfers between the two endpoints.
Computationally efficient implementation of combustion chemistry in parallel PDF calculations
Lu Liuyan Lantz, Steven R.; Ren Zhuyin; Pope, Stephen B.
2009-08-20
In parallel calculations of combustion processes with realistic chemistry, the serial in situ adaptive tabulation (ISAT) algorithm [S.B. Pope, Computationally efficient implementation of combustion chemistry using in situ adaptive tabulation, Combustion Theory and Modelling, 1 (1997) 41-63; L. Lu, S.B. Pope, An improved algorithm for in situ adaptive tabulation, Journal of Computational Physics 228 (2009) 361-386] substantially speeds up the chemistry calculations on each processor. To improve the parallel efficiency of large ensembles of such calculations in parallel computations, in this work, the ISAT algorithm is extended to the multi-processor environment, with the aim of minimizing the wall clock time required for the whole ensemble. Parallel ISAT strategies are developed by combining the existing serial ISAT algorithm with different distribution strategies, namely purely local processing (PLP), uniformly random distribution (URAN), and preferential distribution (PREF). The distribution strategies enable the queued load redistribution of chemistry calculations among processors using message passing. They are implemented in the software x2f{sub m}pi, which is a Fortran 95 library for facilitating many parallel evaluations of a general vector function. The relative performance of the parallel ISAT strategies is investigated in different computational regimes via the PDF calculations of multiple partially stirred reactors burning methane/air mixtures. The results show that the performance of ISAT with a fixed distribution strategy strongly depends on certain computational regimes, based on how much memory is available and how much overlap exists between tabulated information on different processors. No one fixed strategy consistently achieves good performance in all the regimes. Therefore, an adaptive distribution strategy, which blends PLP, URAN and PREF, is devised and implemented. It yields consistently good performance in all regimes. In the adaptive
Computationally efficient implementation of combustion chemistry in parallel PDF calculations
NASA Astrophysics Data System (ADS)
Lu, Liuyan; Lantz, Steven R.; Ren, Zhuyin; Pope, Stephen B.
2009-08-01
In parallel calculations of combustion processes with realistic chemistry, the serial in situ adaptive tabulation (ISAT) algorithm [S.B. Pope, Computationally efficient implementation of combustion chemistry using in situ adaptive tabulation, Combustion Theory and Modelling, 1 (1997) 41-63; L. Lu, S.B. Pope, An improved algorithm for in situ adaptive tabulation, Journal of Computational Physics 228 (2009) 361-386] substantially speeds up the chemistry calculations on each processor. To improve the parallel efficiency of large ensembles of such calculations in parallel computations, in this work, the ISAT algorithm is extended to the multi-processor environment, with the aim of minimizing the wall clock time required for the whole ensemble. Parallel ISAT strategies are developed by combining the existing serial ISAT algorithm with different distribution strategies, namely purely local processing (PLP), uniformly random distribution (URAN), and preferential distribution (PREF). The distribution strategies enable the queued load redistribution of chemistry calculations among processors using message passing. They are implemented in the software x2f_mpi, which is a Fortran 95 library for facilitating many parallel evaluations of a general vector function. The relative performance of the parallel ISAT strategies is investigated in different computational regimes via the PDF calculations of multiple partially stirred reactors burning methane/air mixtures. The results show that the performance of ISAT with a fixed distribution strategy strongly depends on certain computational regimes, based on how much memory is available and how much overlap exists between tabulated information on different processors. No one fixed strategy consistently achieves good performance in all the regimes. Therefore, an adaptive distribution strategy, which blends PLP, URAN and PREF, is devised and implemented. It yields consistently good performance in all regimes. In the adaptive parallel
Aggregating job exit statuses of a plurality of compute nodes executing a parallel application
Aho, Michael E.; Attinella, John E.; Gooding, Thomas M.; Mundy, Michael B.
2015-07-21
Aggregating job exit statuses of a plurality of compute nodes executing a parallel application, including: identifying a subset of compute nodes in the parallel computer to execute the parallel application; selecting one compute node in the subset of compute nodes in the parallel computer as a job leader compute node; initiating execution of the parallel application on the subset of compute nodes; receiving an exit status from each compute node in the subset of compute nodes, where the exit status for each compute node includes information describing execution of some portion of the parallel application by the compute node; aggregating each exit status from each compute node in the subset of compute nodes; and sending an aggregated exit status for the subset of compute nodes in the parallel computer.
On the impact of approximate computation in an analog DeSTIN architecture.
Young, Steven; Lu, Junjie; Holleman, Jeremy; Arel, Itamar
2014-05-01
Deep machine learning (DML) holds the potential to revolutionize machine learning by automating rich feature extraction, which has become the primary bottleneck of human engineering in pattern recognition systems. However, the heavy computational burden renders DML systems implemented on conventional digital processors impractical for large-scale problems. The highly parallel computations required to implement large-scale deep learning systems are well suited to custom hardware. Analog computation has demonstrated power efficiency advantages of multiple orders of magnitude relative to digital systems while performing nonideal computations. In this paper, we investigate typical error sources introduced by analog computational elements and their impact on system-level performance in DeSTIN--a compositional deep learning architecture. These inaccuracies are evaluated on a pattern classification benchmark, clearly demonstrating the robustness of the underlying algorithm to the errors introduced by analog computational elements. A clear understanding of the impacts of nonideal computations is necessary to fully exploit the efficiency of analog circuits.
Superfast robust digital image correlation analysis with parallel computing
NASA Astrophysics Data System (ADS)
Pan, Bing; Tian, Long
2015-03-01
Existing digital image correlation (DIC) using the robust reliability-guided displacement tracking (RGDT) strategy for full-field displacement measurement is a path-dependent process that can only be executed sequentially. This path-dependent tracking strategy not only limits the potential of DIC for further improvement of its computational efficiency but also wastes the parallel computing power of modern computers with multicore processors. To maintain the robustness of the existing RGDT strategy and to overcome its deficiency, an improved RGDT strategy using a two-section tracking scheme is proposed. In the improved RGDT strategy, the calculated points with correlation coefficients higher than a preset threshold are all taken as reliably computed points and given the same priority to extend the correlation analysis to their neighbors. Thus, DIC calculation is first executed in parallel at multiple points by separate independent threads. Then for the few calculated points with correlation coefficients smaller than the threshold, DIC analysis using existing RGDT strategy is adopted. Benefiting from the improved RGDT strategy and the multithread computing, superfast DIC analysis can be accomplished without sacrificing its robustness and accuracy. Experimental results show that the presented parallel DIC method performed on a common eight-core laptop can achieve about a 7 times speedup.
Boundary element analysis on vector and parallel computers
NASA Technical Reports Server (NTRS)
Kane, J. H.
1994-01-01
Boundary element analysis (BEA) can be characterized as a numerical technique that generally shifts the computational burden in the analysis toward numerical integration and the solution of nonsymmetric and either dense or blocked sparse systems of algebraic equations. Researchers have explored the concept that the fundamental characteristics of BEA can be exploited to generate effective implementations on vector and parallel computers. In this paper, the results of some of these investigations are discussed. The performance of overall algorithms for BEA on vector supercomputers, massively data parallel single instruction multiple data (SIMD), and relatively fine grained distributed memory multiple instruction multiple data (MIMD) computer systems is described. Some general trends and conclusions are discussed, along with indications of future developments that may prove fruitful in this regard.
Computer Architecture. (Latest Citations from the Aerospace Database)
NASA Technical Reports Server (NTRS)
1996-01-01
The bibliography contains citations concerning research and development in the field of computer architecture. Design of computer systems, microcomputer components, and digital networks are among the topics discussed. Multimicroprocessor system performance, software development, and aerospace avionics applications are also included. (Contains 50-250 citations and includes a subject term index and title list.)
The Contribution of Visualization to Learning Computer Architecture
ERIC Educational Resources Information Center
Yehezkel, Cecile; Ben-Ari, Mordechai; Dreyfus, Tommy
2007-01-01
This paper describes a visualization environment and associated learning activities designed to improve learning of computer architecture. The environment, EasyCPU, displays a model of the components of a computer and the dynamic processes involved in program execution. We present the results of a research program that analysed the contribution of…
Distributed Computing Environment: An Architecture For Supporting Change?
1995-11-01
Distributed Computing Environment (DCE) has been in development for about five years but has only been widely used in the last two years. It consists...these services form an architecture for distributed computing that enables users to carry out the new, cheaper operations they require with the
Parallel distance matrix computation for Matlab data mining
NASA Astrophysics Data System (ADS)
Skurowski, Przemysław; Staniszewski, Michał
2016-06-01
The paper presents utility functions for computing of a distance matrix, which plays a crucial role in data mining. The goal in the design was to enable operating on relatively large datasets by overcoming basic shortcoming - computing time - with an interface easy to use. The presented solution is a set of functions, which were created with emphasis on practical applicability in real life. The proposed solution is presented along the theoretical background for the performance scaling. Furthermore, different approaches of the parallel computing are analyzed, including shared memory, which is uncommon in Matlab environment.
Parallelism in computational chemistry: Applications in quantum and statistical mechanics
NASA Astrophysics Data System (ADS)
Clementi, E.; Corongiu, G.; Detrich, J. H.; Kahnmohammadbaigi, H.; Chin, S.; Domingo, L.; Laaksonen, A.; Nguyen, N. L.
1985-08-01
Often very fundamental biochemical and biophysical problems defy simulations because of limitation in today's computers. We present and discuss a distributed system composed of two IBM-4341 and one IBM-4381, as front-end processors, and ten FPS-164 attached array processors. This parallel system-called LCAP-has presently a peak performance of about 120 MFlops; extensions to higher performance are discussed. Presently, the system applications use a modified version of VM/SP as the operating system: description of the modifications is given. Three applications programs have migrated from sequential to parallel; a molecular quantum mechanical, a Metropolis-Monte Carlo and a Molecular Dynamics program. Descriptions of the parallel codes are briefly outlined. As examples and tests of these applications we report on a study for proton tunneling in DNA base-pairs, very relevant to spontaneous mutations in genetics. As a second example, we present a Monte Carlo study of liquid water at room temperature where not only two- and three-body interactions are considered but-for the first time-also four-body interactions are included. Finally we briefly summarize a molecular dynamics study where two- and three-body interactions have been considered. These examples, and very positive performance comparison with today's supercomputers allow us to conclude that parallel computers and programming of the type we have considered, represent a pragmatic answer to many computer intensive problems.
Parallel computing in genomic research: advances and applications
Ocaña, Kary; de Oliveira, Daniel
2015-01-01
Today’s genomic experiments have to process the so-called “biological big data” that is now reaching the size of Terabytes and Petabytes. To process this huge amount of data, scientists may require weeks or months if they use their own workstations. Parallelism techniques and high-performance computing (HPC) environments can be applied for reducing the total processing time and to ease the management, treatment, and analyses of this data. However, running bioinformatics experiments in HPC environments such as clouds, grids, clusters, and graphics processing unit requires the expertise from scientists to integrate computational, biological, and mathematical techniques and technologies. Several solutions have already been proposed to allow scientists for processing their genomic experiments using HPC capabilities and parallelism techniques. This article brings a systematic review of literature that surveys the most recently published research involving genomics and parallel computing. Our objective is to gather the main characteristics, benefits, and challenges that can be considered by scientists when running their genomic experiments to benefit from parallelism techniques and HPC capabilities. PMID:26604801
New Parallel computing framework for radiation transport codes
Kostin, M.A.; Mokhov, N.V.; Niita, K.; /JAERI, Tokai
2010-09-01
A new parallel computing framework has been developed to use with general-purpose radiation transport codes. The framework was implemented as a C++ module that uses MPI for message passing. The module is significantly independent of radiation transport codes it can be used with, and is connected to the codes by means of a number of interface functions. The framework was integrated with the MARS15 code, and an effort is under way to deploy it in PHITS. Besides the parallel computing functionality, the framework offers a checkpoint facility that allows restarting calculations with a saved checkpoint file. The checkpoint facility can be used in single process calculations as well as in the parallel regime. Several checkpoint files can be merged into one thus combining results of several calculations. The framework also corrects some of the known problems with the scheduling and load balancing found in the original implementations of the parallel computing functionality in MARS15 and PHITS. The framework can be used efficiently on homogeneous systems and networks of workstations, where the interference from the other users is possible.
Parallel computing in genomic research: advances and applications.
Ocaña, Kary; de Oliveira, Daniel
2015-01-01
Today's genomic experiments have to process the so-called "biological big data" that is now reaching the size of Terabytes and Petabytes. To process this huge amount of data, scientists may require weeks or months if they use their own workstations. Parallelism techniques and high-performance computing (HPC) environments can be applied for reducing the total processing time and to ease the management, treatment, and analyses of this data. However, running bioinformatics experiments in HPC environments such as clouds, grids, clusters, and graphics processing unit requires the expertise from scientists to integrate computational, biological, and mathematical techniques and technologies. Several solutions have already been proposed to allow scientists for processing their genomic experiments using HPC capabilities and parallelism techniques. This article brings a systematic review of literature that surveys the most recently published research involving genomics and parallel computing. Our objective is to gather the main characteristics, benefits, and challenges that can be considered by scientists when running their genomic experiments to benefit from parallelism techniques and HPC capabilities.
JPRS Report. Science & Technology, Japan: Computer Architecture
2007-11-02
No 3, 1987, pp 650-651. [HIBI86] Information provided by Y. Hibino of NTT. [KNUT73] D.E. Knuth , "The Art of Computer Programming," Vol 3: Sorting... computation model, and have been engaged in the experimental generation of a neural network description language, a compiler and simulators and in...functions by simulation. For the simulations, we used simulators implemented by software on conventional types of computers (LISP machine, VAX
Experiences with the Lanczos method on a parallel computer
NASA Technical Reports Server (NTRS)
Bostic, Susan W.; Fulton, Robert E.
1987-01-01
A parallel computer implementation of the Lanczos method for the free-vibration analysis of structures is considered, and results for two example problems show substantial time-reduction over the sequential solutions. The major Lanczos calculation tasks are subdivided into subtasks, and parallelism is introduced at the subtask level. A speedup of 7.8 on eight processors was obtained for the decomposition step of the problem involving a 60-m three-longeron space mast, and a speedup of 14.6 on 16 processors was obtained for the decomposition step of the problem involving a blade-stiffened graphite-epoxy panel.
A language comparison for scientific computing on MIMD architectures
NASA Technical Reports Server (NTRS)
Jones, Mark T.; Patrick, Merrell L.; Voigt, Robert G.
1989-01-01
Choleski's method for solving banded symmetric, positive definite systems is implemented on a multiprocessor computer using three FORTRAN based parallel programming languages, the Force, PISCES and Concurrent FORTRAN. The capabilities of the language for expressing parallelism and their user friendliness are discussed, including readability of the code, debugging assistance offered, and expressiveness of the languages. The performance of the different implementations is compared. It is argued that PISCES, using the Force for medium-grained parallelism, is the appropriate choice for programming Choleski's method on the multiprocessor computer, Flex/32.
Fault tolerant hypercube computer system architecture
NASA Technical Reports Server (NTRS)
Madan, Herb S. (Inventor); Chow, Edward (Inventor)
1989-01-01
A fault-tolerant multiprocessor computer system of the hypercube type comprising a hierarchy of computers of like kind which can be functionally substituted for one another as necessary is disclosed. Communication between the working nodes is via one communications network while communications between the working nodes and watch dog nodes and load balancing nodes higher in the structure is via another communications network separate from the first. A typical branch of the hierarchy reporting to a master node or host computer comprises, a plurality of first computing nodes; a first network of message conducting paths for interconnecting the first computing nodes as a hypercube. The first network provides a path for message transfer between the first computing nodes; a first watch dog node; and a second network of message connecting paths for connecting the first computing nodes to the first watch dog node independent from the first network, the second network provides an independent path for test message and reconfiguration affecting transfers between the first computing nodes and the first switch watch dog node. There is additionally, a plurality of second computing nodes; a third network of message conducting paths for interconnecting the second computing nodes as a hypercube. The third network provides a path for message transfer between the second computing nodes; a fourth network of message conducting paths for connecting the second computing nodes to the first watch dog node independent from the third network. The fourth network provides an independent path for test message and reconfiguration affecting transfers between the second computing nodes and the first watch dog node; and a first multiplexer disposed between the first watch dog node and the second and fourth networks for allowing the first watch dog node to selectively communicate with individual ones of the computing nodes through the second and fourth networks; as well as, a second watch dog node
Architecture independent environment for developing engineering software on MIMD computers
NASA Technical Reports Server (NTRS)
Valimohamed, Karim A.; Lopez, L. A.
1990-01-01
Engineers are constantly faced with solving problems of increasing complexity and detail. Multiple Instruction stream Multiple Data stream (MIMD) computers have been developed to overcome the performance limitations of serial computers. The hardware architectures of MIMD computers vary considerably and are much more sophisticated than serial computers. Developing large scale software for a variety of MIMD computers is difficult and expensive. There is a need to provide tools that facilitate programming these machines. First, the issues that must be considered to develop those tools are examined. The two main areas of concern were architecture independence and data management. Architecture independent software facilitates software portability and improves the longevity and utility of the software product. It provides some form of insurance for the investment of time and effort that goes into developing the software. The management of data is a crucial aspect of solving large engineering problems. It must be considered in light of the new hardware organizations that are available. Second, the functional design and implementation of a software environment that facilitates developing architecture independent software for large engineering applications are described. The topics of discussion include: a description of the model that supports the development of architecture independent software; identifying and exploiting concurrency within the application program; data coherence; engineering data base and memory management.
Highly-Parallel, Highly-Compact Computing Structures Implemented in Nanotechnology
NASA Technical Reports Server (NTRS)
Crawley, D. G.; Duff, M. J. B.; Fountain, T. J.; Moffat, C. D.; Tomlinson, C. D.
1995-01-01
In this paper, we describe work in which we are evaluating how the evolving properties of nano-electronic devices could best be utilized in highly parallel computing structures. Because of their combination of high performance, low power, and extreme compactness, such structures would have obvious applications in spaceborne environments, both for general mission control and for on-board data analysis. However, the anticipated properties of nano-devices mean that the optimum architecture for such systems is by no means certain. Candidates include single instruction multiple datastream (SIMD) arrays, neural networks, and multiple instruction multiple datastream (MIMD) assemblies.
Parallel algorithm for computation of second-order sequential best rotations
NASA Astrophysics Data System (ADS)
Redif, Soydan; Kasap, Server
2013-12-01
Algorithms for computing an approximate polynomial matrix eigenvalue decomposition of para-Hermitian systems have emerged as a powerful, generic signal processing tool. A technique that has shown much success in this regard is the sequential best rotation (SBR2) algorithm. Proposed is a scheme for parallelising SBR2 with a view to exploiting the modern architectural features and inherent parallelism of field-programmable gate array (FPGA) technology. Experiments show that the proposed scheme can achieve low execution times while requiring minimal FPGA resources.
Heavy Lift Vehicle (HLV) Avionics Flight Computing Architecture Study
NASA Technical Reports Server (NTRS)
Hodson, Robert F.; Chen, Yuan; Morgan, Dwayne R.; Butler, A. Marc; Sdhuh, Joseph M.; Petelle, Jennifer K.; Gwaltney, David A.; Coe, Lisa D.; Koelbl, Terry G.; Nguyen, Hai D.
2011-01-01
A NASA multi-Center study team was assembled from LaRC, MSFC, KSC, JSC and WFF to examine potential flight computing architectures for a Heavy Lift Vehicle (HLV) to better understand avionics drivers. The study examined Design Reference Missions (DRMs) and vehicle requirements that could impact the vehicles avionics. The study considered multiple self-checking and voting architectural variants and examined reliability, fault-tolerance, mass, power, and redundancy management impacts. Furthermore, a goal of the study was to develop the skills and tools needed to rapidly assess additional architectures should requirements or assumptions change.
Data communications in a parallel active messaging interface of a parallel computer
Archer, Charles J; Blocksome, Michael A; Ratterman, Joseph D; Smith, Brian E
2015-02-03
Data communications in a parallel active messaging interface (`PAMI`) of a parallel computer, the PAMI composed of data communications endpoints, each endpoint including a specification of data communications parameters for a thread of execution on a compute node, including specifications of a client, a context, and a task, endpoints coupled for data communications through the PAMI and through data communications resources, including receiving in an origin endpoint of the PAMI a SEND instruction, the SEND instruction specifying a transmission of transfer data from the origin endpoint to a first target endpoint; transmitting from the origin endpoint to the first target endpoint a Request-To-Send (`RTS`) message advising the first target endpoint of the location and size of the transfer data; assigning by the first target endpoint to each of a plurality of target endpoints separate portions of the transfer data; and receiving by the plurality of target endpoints the transfer data.
Data communications in a parallel active messaging interface of a parallel computer
Archer, Charles J; Blocksome, Michael A; Ratterman, Joseph D; Smith, Brian E
2014-11-18
Data communications in a parallel active messaging interface (`PAMI`) of a parallel computer, the PAMI composed of data communications endpoints, each endpoint including a specification of data communications parameters for a thread of execution on a compute node, including specifications of a client, a context, and a task, endpoints coupled for data communications through the PAMI and through data communications resources, including receiving in an origin endpoint of the PAMI a SEND instruction, the SEND instruction specifying a transmission of transfer data from the origin endpoint to a first target endpoint; transmitting from the origin endpoint to the first target endpoint a Request-To-Send (`RTS`) message advising the first target endpoint of the location and size of the transfer data; assigning by the first target endpoint to each of a plurality of target endpoints separate portions of the transfer data; and receiving by the plurality of target endpoints the transfer data.
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.
Distributed parallel computing in stochastic modeling of groundwater systems.
Dong, Yanhui; Li, Guomin; Xu, Haizhen
2013-03-01
Stochastic modeling is a rapidly evolving, popular approach to the study of the uncertainty and heterogeneity of groundwater systems. However, the use of Monte Carlo-type simulations to solve practical groundwater problems often encounters computational bottlenecks that hinder the acquisition of meaningful results. To improve the computational efficiency, a system that combines stochastic model generation with MODFLOW-related programs and distributed parallel processing is investigated. The distributed computing framework, called the Java Parallel Processing Framework, is integrated into the system to allow the batch processing of stochastic models in distributed and parallel systems. As an example, the system is applied to the stochastic delineation of well capture zones in the Pinggu Basin in Beijing. Through the use of 50 processing threads on a cluster with 10 multicore nodes, the execution times of 500 realizations are reduced to 3% compared with those of a serial execution. Through this application, the system demonstrates its potential in solving difficult computational problems in practical stochastic modeling.
Implementation of ADI: Schemes on MIMD parallel computers
NASA Technical Reports Server (NTRS)
Vanderwijngaart, Rob F.
1993-01-01
In order to simulate the effects of the impingement of hot exhaust jets of High Performance Aircraft on landing surfaces a multi-disciplinary computation coupling flow dynamics to heat conduction in the runway needs to be carried out. Such simulations, which are essentially unsteady, require very large computational power in order to be completed within a reasonable time frame of the order of an hour. Such power can be furnished by the latest generation of massively parallel computers. These remove the bottleneck of ever more congested data paths to one or a few highly specialized central processing units (CPU's) by having many off-the-shelf CPU's work independently on their own data, and exchange information only when needed. During the past year the first phase of this project was completed, in which the optimal strategy for mapping an ADI-algorithm for the three dimensional unsteady heat equation to a MIMD parallel computer was identified. This was done by implementing and comparing three different domain decomposition techniques that define the tasks for the CPU's in the parallel machine. These implementations were done for a Cartesian grid and Dirichlet boundary conditions. The most promising technique was then used to implement the heat equation solver on a general curvilinear grid with a suite of nontrivial boundary conditions. Finally, this technique was also used to implement the Scalar Penta-diagonal (SP) benchmark, which was taken from the NAS Parallel Benchmarks report. All implementations were done in the programming language C on the Intel iPSC/860 computer.
Parallel calculations on shared memory, NUMA-based computers using MATLAB
NASA Astrophysics Data System (ADS)
Krotkiewski, Marcin; Dabrowski, Marcin
2014-05-01
Achieving satisfactory computational performance in numerical simulations on modern computer architectures can be a complex task. Multi-core design makes it necessary to parallelize the code. Efficient parallelization on NUMA (Non-Uniform Memory Access) shared memory architectures necessitates explicit placement of the data in the memory close to the CPU that uses it. In addition, using more than 8 CPUs (~100 cores) requires a cluster solution of interconnected nodes, which involves (expensive) communication between the processors. It takes significant effort to overcome these challenges even when programming in low-level languages, which give the programmer full control over data placement and work distribution. Instead, many modelers use high-level tools such as MATLAB, which severely limit the optimization/tuning options available. Nonetheless, the advantage of programming simplicity and a large available code base can tip the scale in favor of MATLAB. We investigate whether MATLAB can be used for efficient, parallel computations on modern shared memory architectures. A common approach to performance optimization of MATLAB programs is to identify a bottleneck and migrate the corresponding code block to a MEX file implemented in, e.g. C. Instead, we aim at achieving a scalable parallel performance of MATLABs core functionality. Some of the MATLABs internal functions (e.g., bsxfun, sort, BLAS3, operations on vectors) are multi-threaded. Achieving high parallel efficiency of those may potentially improve the performance of significant portion of MATLABs code base. Since we do not have MATLABs source code, our performance tuning relies on the tools provided by the operating system alone. Most importantly, we use custom memory allocation routines, thread to CPU binding, and memory page migration. The performance tests are carried out on multi-socket shared memory systems (2- and 4-way Intel-based computers), as well as a Distributed Shared Memory machine with 96 CPU
Karasick, Michael S.; Strip, David R.
1996-01-01
A parallel computing system is described that comprises a plurality of uniquely labeled, parallel processors, each processor capable of modelling a three-dimensional object that includes a plurality of vertices, faces and edges. The system comprises a front-end processor for issuing a modelling command to the parallel processors, relating to a three-dimensional object. Each parallel processor, in response to the command and through the use of its own unique label, creates a directed-edge (d-edge) data structure that uniquely relates an edge of the three-dimensional object to one face of the object. Each d-edge data structure at least includes vertex descriptions of the edge and a description of the one face. As a result, each processor, in response to the modelling command, operates upon a small component of the model and generates results, in parallel with all other processors, without the need for processor-to-processor intercommunication.
Karasick, M.S.; Strip, D.R.
1996-01-30
A parallel computing system is described that comprises a plurality of uniquely labeled, parallel processors, each processor capable of modeling a three-dimensional object that includes a plurality of vertices, faces and edges. The system comprises a front-end processor for issuing a modeling command to the parallel processors, relating to a three-dimensional object. Each parallel processor, in response to the command and through the use of its own unique label, creates a directed-edge (d-edge) data structure that uniquely relates an edge of the three-dimensional object to one face of the object. Each d-edge data structure at least includes vertex descriptions of the edge and a description of the one face. As a result, each processor, in response to the modeling command, operates upon a small component of the model and generates results, in parallel with all other processors, without the need for processor-to-processor intercommunication. 8 figs.
Executing a gather operation on a parallel computer
Archer, Charles J [Rochester, MN; Ratterman, Joseph D [Rochester, MN
2012-03-20
Methods, apparatus, and computer program products are disclosed for executing a gather operation on a parallel computer according to embodiments of the present invention. Embodiments include configuring, by the logical root, a result buffer or the logical root, the result buffer having positions, each position corresponding to a ranked node in the operational group and for storing contribution data gathered from that ranked node. Embodiments also include repeatedly for each position in the result buffer: determining, by each compute node of an operational group, whether the current position in the result buffer corresponds with the rank of the compute node, if the current position in the result buffer corresponds with the rank of the compute node, contributing, by that compute node, the compute node's contribution data, if the current position in the result buffer does not correspond with the rank of the compute node, contributing, by that compute node, a value of zero for the contribution data, and storing, by the logical root in the current position in the result buffer, results of a bitwise OR operation of all the contribution data by all compute nodes of the operational group for the current position, the results received through the global combining network.
NASA Technical Reports Server (NTRS)
Fouts, Douglas J.; Butner, Steven E.
1991-01-01
The design of the processing element of GASP, a GaAs supercomputer with a 500-MHz instruction issue rate and 1-GHz subsystem clocks, is presented. The novel, functionally modular, block data flow architecture of GASP is described. The architecture and design of a GASP processing element is then presented. The processing element (PE) is implemented in a hybrid semiconductor module with 152 custom GaAs ICs of eight different types. The effects of the implementation technology on both the system-level architecture and the PE design are discussed. SPICE simulations indicate that parts of the PE are capable of being clocked at 1 GHz, while the rest of the PE uses a 500-MHz clock. The architecture utilizes data flow techniques at a program block level, which allows efficient execution of parallel programs while maintaining reasonably good performance on sequential programs. A simulation study of the architecture indicates that an instruction execution rate of over 30,000 MIPS can be attained with 65 PEs.
A Parallel Computational Model for Multichannel Phase Unwrapping Problem
NASA Astrophysics Data System (ADS)
Imperatore, Pasquale; Pepe, Antonio; Lanari, Riccardo
2015-05-01
In this paper, a parallel model for the solution of the computationally intensive multichannel phase unwrapping (MCh-PhU) problem is proposed. Firstly, the Extended Minimum Cost Flow (EMCF) algorithm for solving MCh-PhU problem is revised within the rigorous mathematical framework of the discrete calculus ; thus permitting to capture its topological structure in terms of meaningful discrete differential operators. Secondly, emphasis is placed on those methodological and practical aspects, which lead to a parallel reformulation of the EMCF algorithm. Thus, a novel dual-level parallel computational model, in which the parallelism is hierarchically implemented at two different (i.e., process and thread) levels, is presented. The validity of our approach has been demonstrated through a series of experiments that have revealed a significant speedup. Therefore, the attained high-performance prototype is suitable for the solution of large-scale phase unwrapping problems in reasonable time frames, with a significant impact on the systematic exploitation of the existing, and rapidly growing, large archives of SAR data.
Parallel-Computing Architecture for JWST Wavefront-Sensing Algorithms
2011-09-01
Hubble Space Telescope and will be NASA’s premier observatory of the next decade. Image-based wavefront sensing (phase retrieval) is the primary...INTRODUCTION The James Webb Space Telescope (JWST) is the next-generation successor to the Hubble Space Telescope . It is a large, space -based infrared...ABSTRACT The James Webb Space Telescope (JWST) is the successor to the Hubble Space Telescope and will be NASA?s premier
Final Report: Center for Programming Models for Scalable Parallel Computing
Mellor-Crummey, John
2011-09-13
As part of the Center for Programming Models for Scalable Parallel Computing, Rice University collaborated with project partners in the design, development and deployment of language, compiler, and runtime support for parallel programming models to support application development for the “leadership-class” computer systems at DOE national laboratories. Work over the course of this project has focused on the design, implementation, and evaluation of a second-generation version of Coarray Fortran. Research and development efforts of the project have focused on the CAF 2.0 language, compiler, runtime system, and supporting infrastructure. This has involved working with the teams that provide infrastructure for CAF that we rely on, implementing new language and runtime features, producing an open source compiler that enabled us to evaluate our ideas, and evaluating our design and implementation through the use of benchmarks. The report details the research, development, findings, and conclusions from this work.
Performing a local reduction operation on a parallel computer
Blocksome, Michael A.; Faraj, Daniel A.
2012-12-11
A parallel computer including compute nodes, each including two reduction processing cores, a network write processing core, and a network read processing core, each processing core assigned an input buffer. Copying, in interleaved chunks by the reduction processing cores, contents of the reduction processing cores' input buffers to an interleaved buffer in shared memory; copying, by one of the reduction processing cores, contents of the network write processing core's input buffer to shared memory; copying, by another of the reduction processing cores, contents of the network read processing core's input buffer to shared memory; and locally reducing in parallel by the reduction processing cores: the contents of the reduction processing core's input buffer; every other interleaved chunk of the interleaved buffer; the copied contents of the network write processing core's input buffer; and the copied contents of the network read processing core's input buffer.
Performing a local reduction operation on a parallel computer
Blocksome, Michael A; Faraj, Daniel A
2013-06-04
A parallel computer including compute nodes, each including two reduction processing cores, a network write processing core, and a network read processing core, each processing core assigned an input buffer. Copying, in interleaved chunks by the reduction processing cores, contents of the reduction processing cores' input buffers to an interleaved buffer in shared memory; copying, by one of the reduction processing cores, contents of the network write processing core's input buffer to shared memory; copying, by another of the reduction processing cores, contents of the network read processing core's input buffer to shared memory; and locally reducing in parallel by the reduction processing cores: the contents of the reduction processing core's input buffer; every other interleaved chunk of the interleaved buffer; the copied contents of the network write processing core's input buffer; and the copied contents of the network read processing core's input buffer.
Establishing a group of endpoints in a parallel computer
Archer, Charles J.; Blocksome, Michael A.; Ratterman, Joseph D.; Smith, Brian E.; Xue, Hanhong
2016-02-02
A parallel computer executes a number of tasks, each task includes a number of endpoints and the endpoints are configured to support collective operations. In such a parallel computer, establishing a group of endpoints receiving a user specification of a set of endpoints included in a global collection of endpoints, where the user specification defines the set in accordance with a predefined virtual representation of the endpoints, the predefined virtual representation is a data structure setting forth an organization of tasks and endpoints included in the global collection of endpoints and the user specification defines the set of endpoints without a user specification of a particular endpoint; and defining a group of endpoints in dependence upon the predefined virtual representation of the endpoints and the user specification.
Modeling of supersonic combustor flows using parallel computing
NASA Technical Reports Server (NTRS)
Riggins, D.; Underwood, M.; Mcmillin, B.; Reeves, L.; Lu, E. J.-L.
1992-01-01
While current 3D CFD codes and modeling techniques have been shown capable of furnishing engineering data for complex scramjet flowfields, the usefulness of such efforts is primarily limited by solutions' CPU time requirements, and secondarily by memory requirements. Attention is presently given to the use of parallel computing capabilities for engineering CFD tools for the analysis of supersonic reacting flows, and to an illustrative incompressible CFD problem using up to 16 iPSC/2 processors with single-domain decomposition.
LINCS: Livermore's network architecture. [Octopus computing network
Fletcher, J.G.
1982-01-01
Octopus, a local computing network that has been evolving at the Lawrence Livermore National Laboratory for over fifteen years, is currently undergoing a major revision. The primary purpose of the revision is to consolidate and redefine the variety of conventions and formats, which have grown up over the years, into a single standard family of protocols, the Livermore Interactive Network Communication Standard (LINCS). This standard treats the entire network as a single distributed operating system such that access to a computing resource is obtained in a single way, whether that resource is local (on the same computer as the accessing process) or remote (on another computer). LINCS encompasses not only communication but also such issues as the relationship of customer to server processes and the structure, naming, and protection of resources. The discussion includes: an overview of the Livermore user community and computing hardware, the functions and structure of each of the seven layers of LINCS protocol, the reasons why we have designed our own protocols and why we are dissatisfied by the directions that current protocol standards are taking.
Performing an allreduce operation on a plurality of compute nodes of a parallel computer
Faraj, Ahmad [Rochester, MN
2012-04-17
Methods, apparatus, and products are disclosed for performing an allreduce operation on a plurality of compute nodes of a parallel computer. Each compute node includes at least two processing cores. Each processing core has contribution data for the allreduce operation. Performing an allreduce operation on a plurality of compute nodes of a parallel computer includes: establishing one or more logical rings among the compute nodes, each logical ring including at least one processing core from each compute node; performing, for each logical ring, a global allreduce operation using the contribution data for the processing cores included in that logical ring, yielding a global allreduce result for each processing core included in that logical ring; and performing, for each compute node, a local allreduce operation using the global allreduce results for each processing core on that compute node.
Domain decomposition methods for the parallel computation of reacting flows
NASA Technical Reports Server (NTRS)
Keyes, David E.
1988-01-01
Domain decomposition is a natural route to parallel computing for partial differential equation solvers. Subdomains of which the original domain of definition is comprised are assigned to independent processors at the price of periodic coordination between processors to compute global parameters and maintain the requisite degree of continuity of the solution at the subdomain interfaces. In the domain-decomposed solution of steady multidimensional systems of PDEs by finite difference methods using a pseudo-transient version of Newton iteration, the only portion of the computation which generally stands in the way of efficient parallelization is the solution of the large, sparse linear systems arising at each Newton step. For some Jacobian matrices drawn from an actual two-dimensional reacting flow problem, comparisons are made between relaxation-based linear solvers and also preconditioned iterative methods of Conjugate Gradient and Chebyshev type, focusing attention on both iteration count and global inner product count. The generalized minimum residual method with block-ILU preconditioning is judged the best serial method among those considered, and parallel numerical experiments on the Encore Multimax demonstrate for it approximately 10-fold speedup on 16 processors.
Parallel Computation of the Regional Ocean Modeling System (ROMS)
Wang, P; Song, Y T; Chao, Y; Zhang, H
2005-04-05
The Regional Ocean Modeling System (ROMS) is a regional ocean general circulation modeling system solving the free surface, hydrostatic, primitive equations over varying topography. It is free software distributed world-wide for studying both complex coastal ocean problems and the basin-to-global scale ocean circulation. The original ROMS code could only be run on shared-memory systems. With the increasing need to simulate larger model domains with finer resolutions and on a variety of computer platforms, there is a need in the ocean-modeling community to have a ROMS code that can be run on any parallel computer ranging from 10 to hundreds of processors. Recently, we have explored parallelization for ROMS using the MPI programming model. In this paper, an efficient parallelization strategy for such a large-scale scientific software package, based on an existing shared-memory computing model, is presented. In addition, scientific applications and data-performance issues on a couple of SGI systems, including Columbia, the world's third-fastest supercomputer, are discussed.
NASA Technical Reports Server (NTRS)
Reuther, James; Alonso, Juan Jose; Rimlinger, Mark J.; Jameson, Antony
1996-01-01
This work describes the application of a control theory-based aerodynamic shape optimization method to the problem of supersonic aircraft design. The design process is greatly accelerated through the use of both control theory and a parallel implementation on distributed memory computers. Control theory is employed to derive the adjoint differential equations whose solution allows for the evaluation of design gradient information at a fraction of the computational cost required by previous design methods. The resulting problem is then implemented on parallel distributed memory architectures using a domain decomposition approach, an optimized communication schedule, and the MPI (Message Passing Interface) Standard for portability and efficiency. The final result achieves very rapid aerodynamic design based on higher order computational fluid dynamics methods (CFD). In our earlier studies, the serial implementation of this design method was shown to be effective for the optimization of airfoils, wings, wing-bodies, and complex aircraft configurations using both the potential equation and the Euler equations. In our most recent paper, the Euler method was extended to treat complete aircraft configurations via a new multiblock implementation. Furthermore, during the same conference, we also presented preliminary results demonstrating that this basic methodology could be ported to distributed memory parallel computing architectures. In this paper, our concern will be to demonstrate that the combined power of these new technologies can be used routinely in an industrial design environment by applying it to the case study of the design of typical supersonic transport configurations. A particular difficulty of this test case is posed by the propulsion/airframe integration.
NASA Technical Reports Server (NTRS)
Reuther, James; Alonso, Juan Jose; Rimlinger, Mark J.; Jameson, Antony
1996-01-01
This work describes the application of a control theory-based aerodynamic shape optimization method to the problem of supersonic aircraft design. The design process is greatly accelerated through the use of both control theory and a parallel implementation on distributed memory computers. Control theory is employed to derive the adjoint differential equations whose solution allows for the evaluation of design gradient information at a fraction of the computational cost required by previous design methods (13, 12, 44, 38). The resulting problem is then implemented on parallel distributed memory architectures using a domain decomposition approach, an optimized communication schedule, and the MPI (Message Passing Interface) Standard for portability and efficiency. The final result achieves very rapid aerodynamic design based on higher order computational fluid dynamics methods (CFD). In our earlier studies, the serial implementation of this design method (19, 20, 21, 23, 39, 25, 40, 41, 42, 43, 9) was shown to be effective for the optimization of airfoils, wings, wing-bodies, and complex aircraft configurations using both the potential equation and the Euler equations (39, 25). In our most recent paper, the Euler method was extended to treat complete aircraft configurations via a new multiblock implementation. Furthermore, during the same conference, we also presented preliminary results demonstrating that the basic methodology could be ported to distributed memory parallel computing architectures [241. In this paper, our concem will be to demonstrate that the combined power of these new technologies can be used routinely in an industrial design environment by applying it to the case study of the design of typical supersonic transport configurations. A particular difficulty of this test case is posed by the propulsion/airframe integration.
Parallel and vector computation for stochastic optimal control applications
NASA Technical Reports Server (NTRS)
Hanson, F. B.
1989-01-01
A general method for parallel and vector numerical solutions of stochastic dynamic programming problems is described for optimal control of general nonlinear, continuous time, multibody dynamical systems, perturbed by Poisson as well as Gaussian random white noise. Possible applications include lumped flight dynamics models for uncertain environments, such as large scale and background random atmospheric fluctuations. The numerical formulation is highly suitable for a vector multiprocessor or vectorizing supercomputer, and results exhibit high processor efficiency and numerical stability. Advanced computing techniques, data structures, and hardware help alleviate Bellman's curse of dimensionality in dynamic programming computations.
Local rollback for fault-tolerance in parallel computing systems
Blumrich, Matthias A [Yorktown Heights, NY; Chen, Dong [Yorktown Heights, NY; Gara, Alan [Yorktown Heights, NY; Giampapa, Mark E [Yorktown Heights, NY; Heidelberger, Philip [Yorktown Heights, NY; Ohmacht, Martin [Yorktown Heights, NY; Steinmacher-Burow, Burkhard [Boeblingen, DE; Sugavanam, Krishnan [Yorktown Heights, NY
2012-01-24
A control logic device performs a local rollback in a parallel super computing system. The super computing system includes at least one cache memory device. The control logic device determines a local rollback interval. The control logic device runs at least one instruction in the local rollback interval. The control logic device evaluates whether an unrecoverable condition occurs while running the at least one instruction during the local rollback interval. The control logic device checks whether an error occurs during the local rollback. The control logic device restarts the local rollback interval if the error occurs and the unrecoverable condition does not occur during the local rollback interval.
Algorithms and software for solving finite element equations on serial and parallel architectures
NASA Technical Reports Server (NTRS)
George, Alan
1989-01-01
Over the past 15 years numerous new techniques have been developed for solving systems of equations and eigenvalue problems arising in finite element computations. A package called SPARSPAK has been developed by the author and his co-workers which exploits these new methods. The broad objective of this research project is to incorporate some of this software in the Computational Structural Mechanics (CSM) testbed, and to extend the techniques for use on multiprocessor architectures.
Neuromorphic Computing – From Materials Research to Systems Architecture Roundtable
Schuller, Ivan K.; Stevens, Rick; Pino, Robinson; Pechan, Michael
2015-10-29
Computation in its many forms is the engine that fuels our modern civilization. Modern computation—based on the von Neumann architecture—has allowed, until now, the development of continuous improvements, as predicted by Moore’s law. However, computation using current architectures and materials will inevitably—within the next 10 years—reach a limit because of fundamental scientific reasons. DOE convened a roundtable of experts in neuromorphic computing systems, materials science, and computer science in Washington on October 29-30, 2015 to address the following basic questions: Can brain-like (“neuromorphic”) computing devices based on new material concepts and systems be developed to dramatically outperform conventional CMOS based technology? If so, what are the basic research challenges for materials sicence and computing? The overarching answer that emerged was: The development of novel functional materials and devices incorporated into unique architectures will allow a revolutionary technological leap toward the implementation of a fully “neuromorphic” computer. To address this challenge, the following issues were considered: The main differences between neuromorphic and conventional computing as related to: signaling models, timing/clock, non-volatile memory, architecture, fault tolerance, integrated memory and compute, noise tolerance, analog vs. digital, and in situ learning New neuromorphic architectures needed to: produce lower energy consumption, potential novel nanostructured materials, and enhanced computation Device and materials properties needed to implement functions such as: hysteresis, stability, and fault tolerance Comparisons of different implementations: spin torque, memristors, resistive switching, phase change, and optical schemes for enhanced breakthroughs in performance, cost, fault tolerance, and/or manufacturability.
NASA Technical Reports Server (NTRS)
Crockett, Thomas W.
1995-01-01
This article provides a broad introduction to the subject of parallel rendering, encompassing both hardware and software systems. The focus is on the underlying concepts and the issues which arise in the design of parallel rendering algorithms and systems. We examine the different types of parallelism and how they can be applied in rendering applications. Concepts from parallel computing, such as data decomposition, task granularity, scalability, and load balancing, are considered in relation to the rendering problem. We also explore concepts from computer graphics, such as coherence and projection, which have a significant impact on the structure of parallel rendering algorithms. Our survey covers a number of practical considerations as well, including the choice of architectural platform, communication and memory requirements, and the problem of image assembly and display. We illustrate the discussion with numerous examples from the parallel rendering literature, representing most of the principal rendering methods currently used in computer graphics.
Runtime optimization of an application executing on a parallel computer
Faraj, Daniel A; Smith, Brian E
2014-11-18
Identifying a collective operation within an application executing on a parallel computer; identifying a call site of the collective operation; determining whether the collective operation is root-based; if the collective operation is not root-based: establishing a tuning session and executing the collective operation in the tuning session; if the collective operation is root-based, determining whether all compute nodes executing the application identified the collective operation at the same call site; if all compute nodes identified the collective operation at the same call site, establishing a tuning session and executing the collective operation in the tuning session; and if all compute nodes executing the application did not identify the collective operation at the same call site, executing the collective operation without establishing a tuning session.
Runtime optimization of an application executing on a parallel computer
Faraj, Daniel A.; Smith, Brian E.
2013-01-29
Identifying a collective operation within an application executing on a parallel computer; identifying a call site of the collective operation; determining whether the collective operation is root-based; if the collective operation is not root-based: establishing a tuning session and executing the collective operation in the tuning session; if the collective operation is root-based, determining whether all compute nodes executing the application identified the collective operation at the same call site; if all compute nodes identified the collective operation at the same call site, establishing a tuning session and executing the collective operation in the tuning session; and if all compute nodes executing the application did not identify the collective operation at the same call site, executing the collective operation without establishing a tuning session.
Runtime optimization of an application executing on a parallel computer
Faraj, Daniel A; Smith, Brian E
2014-11-25
Identifying a collective operation within an application executing on a parallel computer; identifying a call site of the collective operation; determining whether the collective operation is root-based; if the collective operation is not root-based: establishing a tuning session and executing the collective operation in the tuning session; if the collective operation is root-based, determining whether all compute nodes executing the application identified the collective operation at the same call site; if all compute nodes identified the collective operation at the same call site, establishing a tuning session and executing the collective operation in the tuning session; and if all compute nodes executing the application did not identify the collective operation at the same call site, executing the collective operation without establishing a tuning session.
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.
Advanced Computing Architectures for Cognitive Processing
2009-07-01
AND IS APPROVED FOR PUBLICATION IN ACCORDANCE WITH ASSIGNED DISTRIBUTION STATEMENT. FOR THE DIRECTOR: / s ... s / LOK YAN EDWARD J. JONES, Deputy Chief Work Unit Manager Advanced Computing Division...ELEMENT NUMBER 62702F 6. AUTHOR( S ) Gregory D. Peterson 5d. PROJECT NUMBER 459T 5e. TASK NUMBER AC 5f. WORK UNIT NUMBER CP 7. PERFORMING