Efficient multitasking: parallel versus serial processing of multiple tasks
Fischer, Rico; Plessow, Franziska
2015-01-01
In the context of performance optimizations in multitasking, a central debate has unfolded in multitasking research around whether cognitive processes related to different tasks proceed only sequentially (one at a time), or can operate in parallel (simultaneously). This review features a discussion of theoretical considerations and empirical evidence regarding parallel versus serial task processing in multitasking. In addition, we highlight how methodological differences and theoretical conceptions determine the extent to which parallel processing in multitasking can be detected, to guide their employment in future research. Parallel and serial processing of multiple tasks are not mutually exclusive. Therefore, questions focusing exclusively on either task-processing mode are too simplified. We review empirical evidence and demonstrate that shifting between more parallel and more serial task processing critically depends on the conditions under which multiple tasks are performed. We conclude that efficient multitasking is reflected by the ability of individuals to adjust multitasking performance to environmental demands by flexibly shifting between different processing strategies of multiple task-component scheduling. PMID:26441742
Efficient biased random bit generation for parallel processing
Slone, D.M.
1994-09-28
A lattice gas automaton was implemented on a massively parallel machine (the BBN TC2000) and a vector supercomputer (the CRAY C90). The automaton models Burgers equation {rho}t + {rho}{rho}{sub x} = {nu}{rho}{sub xx} in 1 dimension. The lattice gas evolves by advecting and colliding pseudo-particles on a 1-dimensional, periodic grid. The specific rules for colliding particles are stochastic in nature and require the generation of many billions of random numbers to create the random bits necessary for the lattice gas. The goal of the thesis was to speed up the process of generating the random bits and thereby lessen the computational bottleneck of the automaton.
The power and efficiency of advanced software and parallel processing
NASA Technical Reports Server (NTRS)
Singh, Ramen P.; Taylor, Lawrence W., Jr.
1989-01-01
Real-time simulation of flexible and articulating systems is difficult because of the computational burden of the time varying calculations. The mobile servicing system of the NASA Space Station Freedom will handle heavy payloads by local arm manipulations and by translating along the spline of the Station, it is crucial to have real-time simulation available. To enable such a simulation to be of high fidelity and to be able to be hosted on a modest computer, special care must be made in formulating the structural dynamics. Frontal solution algorithms save considerable time in performing these calculations. In addition, it is necessary to take advantage of parallel processing be compatible to take full advantage of both. An approach is offered which will result in high fidelity, real-time simulation for flexible, articulating systems such as the space Station remote servicing system.
Parallel processing for efficient 3D slope stability modelling
NASA Astrophysics Data System (ADS)
Marchesini, Ivan; Mergili, Martin; Alvioli, Massimiliano; Metz, Markus; Schneider-Muntau, Barbara; Rossi, Mauro; Guzzetti, Fausto
2014-05-01
We test the performance of the GIS-based, three-dimensional slope stability model r.slope.stability. The model was developed as a C- and python-based raster module of the GRASS GIS software. It considers the three-dimensional geometry of the sliding surface, adopting a modification of the model proposed by Hovland (1977), and revised and extended by Xie and co-workers (2006). Given a terrain elevation map and a set of relevant thematic layers, the model evaluates the stability of slopes for a large number of randomly selected potential slip surfaces, ellipsoidal or truncated in shape. Any single raster cell may be intersected by multiple sliding surfaces, each associated with a value of the factor of safety, FS. For each pixel, the minimum value of FS and the depth of the associated slip surface are stored. This information is used to obtain a spatial overview of the potentially unstable slopes in the study area. We test the model in the Collazzone area, Umbria, central Italy, an area known to be susceptible to landslides of different type and size. Availability of a comprehensive and detailed landslide inventory map allowed for a critical evaluation of the model results. The r.slope.stability code automatically splits the study area into a defined number of tiles, with proper overlap in order to provide the same statistical significance for the entire study area. The tiles are then processed in parallel by a given number of processors, exploiting a multi-purpose computing environment at CNR IRPI, Perugia. The map of the FS is obtained collecting the individual results, taking the minimum values on the overlapping cells. This procedure significantly reduces the processing time. We show how the gain in terms of processing time depends on the tile dimensions and on the number of cores.
Kothe, D.B.; Turner, J.A.; Mosso, S.J.; Ferrell, R.C.
1997-03-01
We discuss selected aspects of a new parallel three-dimensional (3-D) computational tool for the unstructured mesh simulation of Los Alamos National Laboratory (LANL) casting processes. This tool, known as {bold Telluride}, draws upon on robust, high resolution finite volume solutions of metal alloy mass, momentum, and enthalpy conservation equations to model the filling, cooling, and solidification of LANL castings. We briefly describe the current {bold Telluride} physical models and solution methods, then detail our parallelization strategy as implemented with Fortran 90 (F90). This strategy has yielded straightforward and efficient parallelization on distributed and shared memory architectures, aided in large part by new parallel libraries {bold JTpack9O} for Krylov-subspace iterative solution methods and {bold PGSLib} for efficient gather/scatter operations. We illustrate our methodology and current capabilities with source code examples and parallel efficiency results for a LANL casting simulation.
NASA Technical Reports Server (NTRS)
Liu, Kuojuey Ray
1990-01-01
Least-squares (LS) estimations and spectral decomposition algorithms constitute the heart of modern signal processing and communication problems. Implementations of recursive LS and spectral decomposition algorithms onto parallel processing architectures such as systolic arrays with efficient fault-tolerant schemes are the major concerns of this dissertation. There are four major results in this dissertation. First, we propose the systolic block Householder transformation with application to the recursive least-squares minimization. It is successfully implemented on a systolic array with a two-level pipelined implementation at the vector level as well as at the word level. Second, a real-time algorithm-based concurrent error detection scheme based on the residual method is proposed for the QRD RLS systolic array. The fault diagnosis, order degraded reconfiguration, and performance analysis are also considered. Third, the dynamic range, stability, error detection capability under finite-precision implementation, order degraded performance, and residual estimation under faulty situations for the QRD RLS systolic array are studied in details. Finally, we propose the use of multi-phase systolic algorithms for spectral decomposition based on the QR algorithm. Two systolic architectures, one based on triangular array and another based on rectangular array, are presented for the multiphase operations with fault-tolerant considerations. Eigenvectors and singular vectors can be easily obtained by using the multi-pase operations. Performance issues are also considered.
Parallel Information Processing.
ERIC Educational Resources Information Center
Rasmussen, Edie M.
1992-01-01
Examines parallel computer architecture and the use of parallel processors for text. Topics discussed include parallel algorithms; performance evaluation; parallel information processing; parallel access methods for text; parallel and distributed information retrieval systems; parallel hardware for text; and network models for information…
Special parallel processing workshop
1994-12-01
This report contains viewgraphs from the Special Parallel Processing Workshop. These viewgraphs deal with topics such as parallel processing performance, message passing, queue structure, and other basic concept detailing with parallel processing.
A new strategy for efficient solar energy conversion: Parallel-processing with surface plasmons
NASA Technical Reports Server (NTRS)
Anderson, L. M.
1982-01-01
This paper introduces an advanced concept for direct conversion of sunlight to electricity, which aims at high efficiency by tailoring the conversion process to separate energy bands within the broad solar spectrum. The objective is to obtain a high level of spectrum-splitting without sequential losses or unique materials for each frequency band. In this concept, sunlight excites a spectrum of surface plasma waves which are processed in parallel on the same metal film. The surface plasmons transport energy to an array of metal-barrier-semiconductor diodes, where energy is extracted by inelastic tunneling. Diodes are tuned to different frequency bands by selecting the operating voltage and geometry, but all diodes share the same materials.
Cusack, Rhodri; Vicente-Grabovetsky, Alejandro; Mitchell, Daniel J; Wild, Conor J; Auer, Tibor; Linke, Annika C; Peelle, Jonathan E
2014-01-01
Recent years have seen neuroimaging data sets becoming richer, with larger cohorts of participants, a greater variety of acquisition techniques, and increasingly complex analyses. These advances have made data analysis pipelines complicated to set up and run (increasing the risk of human error) and time consuming to execute (restricting what analyses are attempted). Here we present an open-source framework, automatic analysis (aa), to address these concerns. Human efficiency is increased by making code modular and reusable, and managing its execution with a processing engine that tracks what has been completed and what needs to be (re)done. Analysis is accelerated by optional parallel processing of independent tasks on cluster or cloud computing resources. A pipeline comprises a series of modules that each perform a specific task. The processing engine keeps track of the data, calculating a map of upstream and downstream dependencies for each module. Existing modules are available for many analysis tasks, such as SPM-based fMRI preprocessing, individual and group level statistics, voxel-based morphometry, tractography, and multi-voxel pattern analyses (MVPA). However, aa also allows for full customization, and encourages efficient management of code: new modules may be written with only a small code overhead. aa has been used by more than 50 researchers in hundreds of neuroimaging studies comprising thousands of subjects. It has been found to be robust, fast, and efficient, for simple-single subject studies up to multimodal pipelines on hundreds of subjects. It is attractive to both novice and experienced users. aa can reduce the amount of time neuroimaging laboratories spend performing analyses and reduce errors, expanding the range of scientific questions it is practical to address. PMID:25642185
Cusack, Rhodri; Vicente-Grabovetsky, Alejandro; Mitchell, Daniel J.; Wild, Conor J.; Auer, Tibor; Linke, Annika C.; Peelle, Jonathan E.
2015-01-01
Recent years have seen neuroimaging data sets becoming richer, with larger cohorts of participants, a greater variety of acquisition techniques, and increasingly complex analyses. These advances have made data analysis pipelines complicated to set up and run (increasing the risk of human error) and time consuming to execute (restricting what analyses are attempted). Here we present an open-source framework, automatic analysis (aa), to address these concerns. Human efficiency is increased by making code modular and reusable, and managing its execution with a processing engine that tracks what has been completed and what needs to be (re)done. Analysis is accelerated by optional parallel processing of independent tasks on cluster or cloud computing resources. A pipeline comprises a series of modules that each perform a specific task. The processing engine keeps track of the data, calculating a map of upstream and downstream dependencies for each module. Existing modules are available for many analysis tasks, such as SPM-based fMRI preprocessing, individual and group level statistics, voxel-based morphometry, tractography, and multi-voxel pattern analyses (MVPA). However, aa also allows for full customization, and encourages efficient management of code: new modules may be written with only a small code overhead. aa has been used by more than 50 researchers in hundreds of neuroimaging studies comprising thousands of subjects. It has been found to be robust, fast, and efficient, for simple-single subject studies up to multimodal pipelines on hundreds of subjects. It is attractive to both novice and experienced users. aa can reduce the amount of time neuroimaging laboratories spend performing analyses and reduce errors, expanding the range of scientific questions it is practical to address. PMID:25642185
Efficient Parallel Video Processing Techniques on GPU: From Framework to Implementation
Su, Huayou; Wen, Mei; Wu, Nan; Ren, Ju; Zhang, Chunyuan
2014-01-01
Through reorganizing the execution order and optimizing the data structure, we proposed an efficient parallel framework for H.264/AVC encoder based on massively parallel architecture. We implemented the proposed framework by CUDA on NVIDIA's GPU. Not only the compute intensive components of the H.264 encoder are parallelized but also the control intensive components are realized effectively, such as CAVLC and deblocking filter. In addition, we proposed serial optimization methods, including the multiresolution multiwindow for motion estimation, multilevel parallel strategy to enhance the parallelism of intracoding as much as possible, component-based parallel CAVLC, and direction-priority deblocking filter. More than 96% of workload of H.264 encoder is offloaded to GPU. Experimental results show that the parallel implementation outperforms the serial program by 20 times of speedup ratio and satisfies the requirement of the real-time HD encoding of 30 fps. The loss of PSNR is from 0.14 dB to 0.77 dB, when keeping the same bitrate. Through the analysis to the kernels, we found that speedup ratios of the compute intensive algorithms are proportional with the computation power of the GPU. However, the performance of the control intensive parts (CAVLC) is much related to the memory bandwidth, which gives an insight for new architecture design. PMID:24757432
Efficient Process Migration for Parallel Processing on Non-Dedicated Networks of Workstations
NASA Technical Reports Server (NTRS)
Chanchio, Kasidit; Sun, Xian-He
1996-01-01
This paper presents the design and preliminary implementation of MpPVM, a software system that supports process migration for PVM application programs in a non-dedicated heterogeneous computing environment. New concepts of migration point as well as migration point analysis and necessary data analysis are introduced. In MpPVM, process migrations occur only at previously inserted migration points. Migration point analysis determines appropriate locations to insert migration points; whereas, necessary data analysis provides a minimum set of variables to be transferred at each migration pint. A new methodology to perform reliable point-to-point data communications in a migration environment is also discussed. Finally, a preliminary implementation of MpPVM and its experimental results are presented, showing the correctness and promising performance of our process migration mechanism in a scalable non-dedicated heterogeneous computing environment. While MpPVM is developed on top of PVM, the process migration methodology introduced in this study is general and can be applied to any distributed software environment.
Efficiency of parallel direct optimization
NASA Technical Reports Server (NTRS)
Janies, D. A.; Wheeler, W. C.
2001-01-01
Tremendous progress has been made at the level of sequential computation in phylogenetics. However, little attention has been paid to parallel computation. Parallel computing is particularly suited to phylogenetics because of the many ways large computational problems can be broken into parts that can be analyzed concurrently. In this paper, we investigate the scaling factors and efficiency of random addition and tree refinement strategies using the direct optimization software, POY, on a small (10 slave processors) and a large (256 slave processors) cluster of networked PCs running LINUX. These algorithms were tested on several data sets composed of DNA and morphology ranging from 40 to 500 taxa. Various algorithms in POY show fundamentally different properties within and between clusters. All algorithms are efficient on the small cluster for the 40-taxon data set. On the large cluster, multibuilding exhibits excellent parallel efficiency, whereas parallel building is inefficient. These results are independent of data set size. Branch swapping in parallel shows excellent speed-up for 16 slave processors on the large cluster. However, there is no appreciable speed-up for branch swapping with the further addition of slave processors (>16). This result is independent of data set size. Ratcheting in parallel is efficient with the addition of up to 32 processors in the large cluster. This result is independent of data set size. c2001 The Willi Hennig Society.
Efficiency of parallel direct optimization.
Janies, D A; Wheeler, W C
2001-03-01
Tremendous progress has been made at the level of sequential computation in phylogenetics. However, little attention has been paid to parallel computation. Parallel computing is particularly suited to phylogenetics because of the many ways large computational problems can be broken into parts that can be analyzed concurrently. In this paper, we investigate the scaling factors and efficiency of random addition and tree refinement strategies using the direct optimization software, POY, on a small (10 slave processors) and a large (256 slave processors) cluster of networked PCs running LINUX. These algorithms were tested on several data sets composed of DNA and morphology ranging from 40 to 500 taxa. Various algorithms in POY show fundamentally different properties within and between clusters. All algorithms are efficient on the small cluster for the 40-taxon data set. On the large cluster, multibuilding exhibits excellent parallel efficiency, whereas parallel building is inefficient. These results are independent of data set size. Branch swapping in parallel shows excellent speed-up for 16 slave processors on the large cluster. However, there is no appreciable speed-up for branch swapping with the further addition of slave processors (>16). This result is independent of data set size. Ratcheting in parallel is efficient with the addition of up to 32 processors in the large cluster. This result is independent of data set size. PMID:12240679
Coarrars for Parallel Processing
NASA Technical Reports Server (NTRS)
Snyder, W. Van
2011-01-01
The design of the Coarray feature of Fortran 2008 was guided by answering the question "What is the smallest change required to convert Fortran to a robust and efficient parallel language." Two fundamental issues that any parallel programming model must address are work distribution and data distribution. In order to coordinate work distribution and data distribution, methods for communication and synchronization must be provided. Although originally designed for Fortran, the Coarray paradigm has stimulated development in other languages. X10, Chapel, UPC, Titanium, and class libraries being developed for C++ have the same conceptual framework.
Speeding up parallel processing
NASA Technical Reports Server (NTRS)
Denning, Peter J.
1988-01-01
In 1967 Amdahl expressed doubts about the ultimate utility of multiprocessors. The formulation, now called Amdahl's law, became part of the computing folklore and has inspired much skepticism about the ability of the current generation of massively parallel processors to efficiently deliver all their computing power to programs. The widely publicized recent results of a group at Sandia National Laboratory, which showed speedup on a 1024 node hypercube of over 500 for three fixed size problems and over 1000 for three scalable problems, have convincingly challenged this bit of folklore and have given new impetus to parallel scientific computing.
Parallel processing and expert systems
NASA Technical Reports Server (NTRS)
Yan, Jerry C.; Lau, Sonie
1991-01-01
Whether it be monitoring the thermal subsystem of Space Station Freedom, or controlling the navigation of the autonomous rover on Mars, NASA missions in the 90's cannot enjoy an increased level of autonomy without the efficient use of expert systems. Merely increasing the computational speed of uniprocessors may not be able to guarantee that real time demands are met for large expert systems. Speed-up via parallel processing must be pursued alongside the optimization of sequential implementations. Prototypes of parallel expert systems have been built at universities and industrial labs in the U.S. and Japan. The state-of-the-art research in progress related to parallel execution of expert systems was surveyed. The survey is divided into three major sections: (1) multiprocessors for parallel expert systems; (2) parallel languages for symbolic computations; and (3) measurements of parallelism of expert system. Results to date indicate that the parallelism achieved for these systems is small. In order to obtain greater speed-ups, data parallelism and application parallelism must be exploited.
Parallel processing and expert systems
NASA Technical Reports Server (NTRS)
Lau, Sonie; Yan, Jerry C.
1991-01-01
Whether it be monitoring the thermal subsystem of Space Station Freedom, or controlling the navigation of the autonomous rover on Mars, NASA missions in the 1990s cannot enjoy an increased level of autonomy without the efficient implementation of expert systems. Merely increasing the computational speed of uniprocessors may not be able to guarantee that real-time demands are met for larger systems. Speedup via parallel processing must be pursued alongside the optimization of sequential implementations. Prototypes of parallel expert systems have been built at universities and industrial laboratories in the U.S. and Japan. The state-of-the-art research in progress related to parallel execution of expert systems is surveyed. The survey discusses multiprocessors for expert systems, parallel languages for symbolic computations, and mapping expert systems to multiprocessors. Results to date indicate that the parallelism achieved for these systems is small. The main reasons are (1) the body of knowledge applicable in any given situation and the amount of computation executed by each rule firing are small, (2) dividing the problem solving process into relatively independent partitions is difficult, and (3) implementation decisions that enable expert systems to be incrementally refined hamper compile-time optimization. In order to obtain greater speedups, data parallelism and application parallelism must be exploited.
An efficient parallel algorithm for mesh smoothing
Freitag, L.; Plassmann, P.; Jones, M.
1995-12-31
Automatic mesh generation and adaptive refinement methods have proven to be very successful tools for the efficient solution of complex finite element applications. A problem with these methods is that they can produce poorly shaped elements; such elements are undesirable because they introduce numerical difficulties in the solution process. However, the shape of the elements can be improved through the determination of new geometric locations for mesh vertices by using a mesh smoothing algorithm. In this paper the authors present a new parallel algorithm for mesh smoothing that has a fast parallel runtime both in theory and in practice. The authors present an efficient implementation of the algorithm that uses non-smooth optimization techniques to find the new location of each vertex. Finally, they present experimental results obtained on the IBM SP system demonstrating the efficiency of this approach.
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.
EFFICIENT SCHEDULING OF PARALLEL JOBS ON MASSIVELY PARALLEL SYSTEMS
F. PETRINI; W. FENG
1999-09-01
We present buffered coscheduling, a new methodology to multitask parallel jobs in a message-passing environment and to develop parallel programs that can pave the way to the efficient implementation of a distributed operating system. Buffered coscheduling is based on three innovative techniques: communication buffering, strobing, and non-blocking communication. By leveraging these techniques, we can perform effective optimizations based on the global status of the parallel machine rather than on the limited knowledge available locally to each processor. The advantages of buffered coscheduling include higher resource utilization, reduced communication overhead, efficient implementation of low-control strategies and fault-tolerant protocols, accurate performance modeling, and a simplified yet still expressive parallel programming model. Preliminary experimental results show that buffered coscheduling is very effective in increasing the overall performance in the presence of load imbalance and communication-intensive workloads.
Efficient, massively parallel eigenvalue computation
NASA Technical Reports Server (NTRS)
Huo, Yan; Schreiber, Robert
1993-01-01
In numerical simulations of disordered electronic systems, one of the most common approaches is to diagonalize random Hamiltonian matrices and to study the eigenvalues and eigenfunctions of a single electron in the presence of a random potential. An effort to implement a matrix diagonalization routine for real symmetric dense matrices on massively parallel SIMD computers, the Maspar MP-1 and MP-2 systems, is described. Results of numerical tests and timings are also presented.
Knowledge representation into Ada parallel processing
NASA Technical Reports Server (NTRS)
Masotto, Tom; Babikyan, Carol; Harper, Richard
1990-01-01
The Knowledge Representation into Ada Parallel Processing project is a joint NASA and Air Force funded project to demonstrate the execution of intelligent systems in Ada on the Charles Stark Draper Laboratory fault-tolerant parallel processor (FTPP). Two applications were demonstrated - a portion of the adaptive tactical navigator and a real time controller. Both systems are implemented as Activation Framework Objects on the Activation Framework intelligent scheduling mechanism developed by Worcester Polytechnic Institute. The implementations, results of performance analyses showing speedup due to parallelism and initial efficiency improvements are detailed and further areas for performance improvements are suggested.
Parallel processing spacecraft communication system
NASA Technical Reports Server (NTRS)
Bolotin, Gary S. (Inventor); Donaldson, James A. (Inventor); Luong, Huy H. (Inventor); Wood, Steven H. (Inventor)
1998-01-01
An uplink controlling assembly speeds data processing using a special parallel codeblock technique. A correct start sequence initiates processing of a frame. Two possible start sequences can be used; and the one which is used determines whether data polarity is inverted or non-inverted. Processing continues until uncorrectable errors are found. The frame ends by intentionally sending a block with an uncorrectable error. Each of the codeblocks in the frame has a channel ID. Each channel ID can be separately processed in parallel. This obviates the problem of waiting for error correction processing. If that channel number is zero, however, it indicates that the frame of data represents a critical command only. That data is handled in a special way, independent of the software. Otherwise, the processed data further handled using special double buffering techniques to avoid problems from overrun. When overrun does occur, the system takes action to lose only the oldest data.
Efficient communication in massively parallel computers
Cypher, R.E.
1989-01-01
A fundamental operation in parallel computation is sorting. Sorting is important not only because it is required by many algorithms, but also because it can be used to implement irregular, pointer-based communication. The author studies two algorithms for sorting in massively parallel computers. First, he examines Shellsort. Shellsort is a sorting algorithm that is based on a sequence of parameters called increments. Shellsort can be used to create a parallel sorting device known as a sorting network. Researchers have suggested that if the correct increment sequence is used, an optimal size sorting network can be obtained. All published increment sequences have been monotonically decreasing. He shows that no monotonically decreasing increment sequence will yield an optimal size sorting network. Second, he presents a sorting algorithm called Cubesort. Cubesort is the fastest known sorting algorithm for a variety of parallel computers aver a wide range of parameters. He also presents a paradigm for developing parallel algorithms that have efficient communication. The paradigm, called the data reduction paradigm, consists of using a divide-and-conquer strategy. Both the division and combination phases of the divide-and-conquer algorithm may require irregular, pointer-based communication between processors. However, the problem is divided so as to limit the amount of data that must be communicated. As a result the communication can be performed efficiently. He presents data reduction algorithms for the image component labeling problem, the closest pair problem and four versions of the parallel prefix problem.
Massively parallel femtosecond laser processing.
Hasegawa, Satoshi; Ito, Haruyasu; Toyoda, Haruyoshi; Hayasaki, Yoshio
2016-08-01
Massively parallel femtosecond laser processing with more than 1000 beams was demonstrated. Parallel beams were generated by a computer-generated hologram (CGH) displayed on a spatial light modulator (SLM). The key to this technique is to optimize the CGH in the laser processing system using a scheme called in-system optimization. It was analytically demonstrated that the number of beams is determined by the horizontal number of pixels in the SLM N_{SLM} that is imaged at the pupil plane of an objective lens and a distance parameter p_{d} obtained by dividing the distance between adjacent beams by the diffraction-limited beam diameter. A performance limitation of parallel laser processing in our system was estimated at N_{SLM} of 250 and p_{d} of 7.0. Based on these parameters, the maximum number of beams in a hexagonal close-packed structure was calculated to be 1189 by using an analytical equation. PMID:27505815
Efficient parallel global garbage collection on massively parallel computers
Kamada, Tomio; Matsuoka, Satoshi; Yonezawa, Akinori
1994-12-31
On distributed-memory high-performance MPPs where processors are interconnected by an asynchronous network, efficient Garbage Collection (GC) becomes difficult due to inter-node references and references within pending, unprocessed messages. The parallel global GC algorithm (1) takes advantage of reference locality, (2) efficiently traverses references over nodes, (3) admits minimum pause time of ongoing computations, and (4) has been shown to scale up to 1024 node MPPs. The algorithm employs a global weight counting scheme to substantially reduce message traffic. The two methods for confirming the arrival of pending messages are used: one counts numbers of messages and the other uses network `bulldozing.` Performance evaluation in actual implementations on a multicomputer with 32-1024 nodes, Fujitsu AP1000, reveals various favorable properties of the algorithm.
Cluster-based parallel image processing toolkit
NASA Astrophysics Data System (ADS)
Squyres, Jeffery M.; Lumsdaine, Andrew; Stevenson, Robert L.
1995-03-01
Many image processing tasks exhibit a high degree of data locality and parallelism and map quite readily to specialized massively parallel computing hardware. However, as network technologies continue to mature, workstation clusters are becoming a viable and economical parallel computing resource, so it is important to understand how to use these environments for parallel image processing as well. In this paper we discuss our implementation of parallel image processing software library (the Parallel Image Processing Toolkit). The Toolkit uses a message- passing model of parallelism designed around the Message Passing Interface (MPI) standard. Experimental results are presented to demonstrate the parallel speedup obtained with the Parallel Image Processing Toolkit in a typical workstation cluster over a wide variety of image processing tasks. We also discuss load balancing and the potential for parallelizing portions of image processing tasks that seem to be inherently sequential, such as visualization and data I/O.
On the design, analysis, and implementation of efficient parallel algorithms
Sohn, S.M.
1989-01-01
There is considerable interest in developing algorithms for a variety of parallel computer architectures. This is not a trivial problem, although for certain models great progress has been made. Recently, general-purpose parallel machines have become available commercially. These machines possess widely varying interconnection topologies and data/instruction access schemes. It is important, therefore, to develop methodologies and design paradigms for not only synthesizing parallel algorithms from initial problem specifications, but also for mapping algorithms between different architectures. This work has considered both of these problems. A systolic array consists of a large collection of simple processors that are interconnected in a uniform pattern. The author has studied in detain the problem of mapping systolic algorithms onto more general-purpose parallel architectures such as the hypercube. The hypercube architecture is notable due to its symmetry and high connectivity, characteristics which are conducive to the efficient embedding of parallel algorithms. Although the parallel-to-parallel mapping techniques have yielded efficient target algorithms, it is not surprising that an algorithm designed directly for a particular parallel model would achieve superior performance. In this context, the author has developed hypercube algorithms for some important problems in speech and signal processing, text processing, language processing and artificial intelligence. These algorithms were implemented on a 64-node NCUBE/7 hypercube machine in order to evaluate their performance.
Multi-petascale highly efficient parallel supercomputer
Asaad, Sameh; Bellofatto, Ralph E.; Blocksome, Michael A.; Blumrich, Matthias A.; Boyle, Peter; Brunheroto, Jose R.; Chen, Dong; Cher, Chen -Yong; Chiu, George L.; Christ, Norman; Coteus, Paul W.; Davis, Kristan D.; Dozsa, Gabor J.; Eichenberger, Alexandre E.; Eisley, Noel A.; Ellavsky, Matthew R.; Evans, Kahn C.; Fleischer, Bruce M.; Fox, Thomas W.; Gara, Alan; Giampapa, Mark E.; Gooding, Thomas M.; Gschwind, Michael K.; Gunnels, John A.; Hall, Shawn A.; Haring, Rudolf A.; Heidelberger, Philip; Inglett, Todd A.; Knudson, Brant L.; Kopcsay, Gerard V.; Kumar, Sameer; Mamidala, Amith R.; Marcella, James A.; Megerian, Mark G.; Miller, Douglas R.; Miller, Samuel J.; Muff, Adam J.; Mundy, Michael B.; O'Brien, John K.; O'Brien, Kathryn M.; Ohmacht, Martin; Parker, Jeffrey J.; Poole, Ruth J.; Ratterman, Joseph D.; Salapura, Valentina; Satterfield, David L.; Senger, Robert M.; Smith, Brian; Steinmacher-Burow, Burkhard; Stockdell, William M.; Stunkel, Craig B.; Sugavanam, Krishnan; Sugawara, Yutaka; Takken, Todd E.; Trager, Barry M.; Van Oosten, James L.; Wait, Charles D.; Walkup, Robert E.; Watson, Alfred T.; Wisniewski, Robert W.; Wu, Peng
2015-07-14
A Multi-Petascale Highly Efficient Parallel Supercomputer of 100 petaOPS-scale computing, at decreased cost, power and footprint, and that allows for a maximum packaging density of processing nodes from an interconnect point of view. The Supercomputer exploits technological advances in VLSI that enables a computing model where many processors can be integrated into a single Application Specific Integrated Circuit (ASIC). Each ASIC computing node comprises a system-on-chip ASIC utilizing four or more processors integrated into one die, with each having full access to all system resources and enabling adaptive partitioning of the processors to functions such as compute or messaging I/O on an application by application basis, and preferably, enable adaptive partitioning of functions in accordance with various algorithmic phases within an application, or if I/O or other processors are underutilized, then can participate in computation or communication nodes are interconnected by a five dimensional torus network with DMA that optimally maximize the throughput of packet communications between nodes and minimize latency.
Parallel Processing at the High School Level.
ERIC Educational Resources Information Center
Sheary, Kathryn Anne
This study investigated the ability of high school students to cognitively understand and implement parallel processing. Data indicates that most parallel processing is being taught at the university level. Instructional modules on C, Linux, and the parallel processing language, P4, were designed to show that high school students are highly…
Hydrologic Terrain Processing Using Parallel Computing
NASA Astrophysics Data System (ADS)
Tarboton, D. G.; Watson, D. W.; Wallace, R. M.; Schreuders, K.; Tesfa, T. K.
2009-12-01
Topography in the form of Digital Elevation Models (DEMs), is widely used to derive information for the modeling of hydrologic processes. Hydrologic terrain analysis augments the information content of digital elevation data by removing spurious pits, deriving a structured flow field, and calculating surfaces of hydrologic information derived from the flow field. The increasing availability of high-resolution terrain datasets for large areas poses a challenge for existing algorithms that process terrain data to extract this hydrologic information. This paper will describe parallel algorithms that have been developed to enhance hydrologic terrain pre-processing so that larger datasets can be more efficiently computed. Message Passing Interface (MPI) parallel implementations have been developed for pit removal, flow direction, and generalized flow accumulation methods within the Terrain Analysis Using Digital Elevation Models (TauDEM) package. The parallel algorithm works by decomposing the domain into striped or tiled data partitions where each tile is processed by a separate processor. This method also reduces the memory requirements of each processor so that larger size grids can be processed. The parallel pit removal algorithm is adapted from the method of Planchon and Darboux that starts from a high elevation then progressively scans the grid, lowering each grid cell to the maximum of the original elevation or the lowest neighbor. The MPI implementation reconciles elevations along process domain edges after each scan. Generalized flow accumulation extends flow accumulation approaches commonly available in GIS through the integration of multiple inputs and a broad class of algebraic rules into the calculation of flow related quantities. It is based on establishing a flow field through DEM grid cells, that is then used to evaluate any mathematical function that incorporates dependence on values of the quantity being evaluated at upslope (or downslope) grid cells
Parallel processing and medium-scale multiprocessors
Wouk, A.
1989-01-01
For some time, the community interested in large-scale scientific computing has been attempting to come to terms with parallel computation using a number of processors sufficient to make their concurrent utilization interesting, challenging, and, in the long run, beneficial. Unexpected consequences of parallelization have been discovered. It is possible to obtain reduced performance, both relative and absolute, from an increased number of processors, as a result of inappropriate use of resources in a multiprocessor environment. This exemplifies one of the paradoxes which result from our cultural bias towards sequential thought processes. As a consequence there is a bias for sequential styles of program development in a multiprocessor environment. The authors have learned that the problem of automatic optimization in compilation of parallel programs is computationally hard. Early hopes that automatic, optimal parallelization of sequentially conceived programs would be as achievable as earlier automatic vectorization had been, have been dashed. The authors lack the insights and folklore which are needed to develop useful methodologies and heuristics in the area of parallel computation. The authors are embarked on a voyage of exploration of this new territory, and the work described in this volume can provide helpful guidance. The authors have to explore fully the differences between distributed memory systems, shared memory systems, and combinations, as well as the relative applicability of SIMD and MIMD architectures. Based on the information obtained in such exploration, useful steps towards efficient utilization of many processors should become possible. This paper covers several areas: systems programming, parallel/language/programming systems, and applications programming.
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
Efficient parallel CFD-DEM simulations using OpenMP
NASA Astrophysics Data System (ADS)
Amritkar, Amit; Deb, Surya; Tafti, Danesh
2014-01-01
The paper describes parallelization strategies for the Discrete Element Method (DEM) used for simulating dense particulate systems coupled to Computational Fluid Dynamics (CFD). While the field equations of CFD are best parallelized by spatial domain decomposition techniques, the N-body particulate phase is best parallelized over the number of particles. When the two are coupled together, both modes are needed for efficient parallelization. It is shown that under these requirements, OpenMP thread based parallelization has advantages over MPI processes. Two representative examples, fairly typical of dense fluid-particulate systems are investigated, including the validation of the DEM-CFD and thermal-DEM implementation with experiments. Fluidized bed calculations are performed on beds with uniform particle loading, parallelized with MPI and OpenMP. It is shown that as the number of processing cores and the number of particles increase, the communication overhead of building ghost particle lists at processor boundaries dominates time to solution, and OpenMP which does not require this step is about twice as fast as MPI. In rotary kiln heat transfer calculations, which are characterized by spatially non-uniform particle distributions, the low overhead of switching the parallelization mode in OpenMP eliminates the load imbalances, but introduces increased overheads in fetching non-local data. In spite of this, it is shown that OpenMP is between 50-90% faster than MPI.
Parallel processing in immune networks
NASA Astrophysics Data System (ADS)
Agliari, Elena; Barra, Adriano; Bartolucci, Silvia; Galluzzi, Andrea; Guerra, Francesco; Moauro, Francesco
2013-04-01
In this work, we adopt a statistical-mechanics approach to investigate basic, systemic features exhibited by adaptive immune systems. The lymphocyte network made by B cells and T cells is modeled by a bipartite spin glass, where, following biological prescriptions, links connecting B cells and T cells are sparse. Interestingly, the dilution performed on links is shown to make the system able to orchestrate parallel strategies to fight several pathogens at the same time; this multitasking capability constitutes a remarkable, key property of immune systems as multiple antigens are always present within the host. We also define the stochastic process ruling the temporal evolution of lymphocyte activity and show its relaxation toward an equilibrium measure allowing statistical-mechanics investigations. Analytical results are compared with Monte Carlo simulations and signal-to-noise outcomes showing overall excellent agreement. Finally, within our model, a rationale for the experimentally well-evidenced correlation between lymphocytosis and autoimmunity is achieved; this sheds further light on the systemic features exhibited by immune networks.
Bitplane Image Coding With Parallel Coefficient Processing.
Auli-Llinas, Francesc; Enfedaque, Pablo; Moure, Juan C; Sanchez, Victor
2016-01-01
Image coding systems have been traditionally tailored for multiple instruction, multiple data (MIMD) computing. In general, they partition the (transformed) image in codeblocks that can be coded in the cores of MIMD-based processors. Each core executes a sequential flow of instructions to process the coefficients in the codeblock, independently and asynchronously from the others cores. Bitplane coding is a common strategy to code such data. Most of its mechanisms require sequential processing of the coefficients. The last years have seen the upraising of processing accelerators with enhanced computational performance and power efficiency whose architecture is mainly based on the single instruction, multiple data (SIMD) principle. SIMD computing refers to the execution of the same instruction to multiple data in a lockstep synchronous way. Unfortunately, current bitplane coding strategies cannot fully profit from such processors due to inherently sequential coding task. This paper presents bitplane image coding with parallel coefficient (BPC-PaCo) processing, a coding method that can process many coefficients within a codeblock in parallel and synchronously. To this end, the scanning order, the context formation, the probability model, and the arithmetic coder of the coding engine have been re-formulated. The experimental results suggest that the penalization in coding performance of BPC-PaCo with respect to the traditional strategies is almost negligible. PMID:26441420
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).
Applications of Parallel Processing to Astrodynamics
NASA Astrophysics Data System (ADS)
Coffey, S.; Healy, L.; Neal, H.
1996-03-01
Parallel processing is being used to improve the catalog of earth orbiting satellites and for problems associated with the catalog. Initial efforts centered around using SIMD parallel processors to perform debris conjunction analysis and satellite dynamics studies. More recently, the availability of cheap supercomputing processors and parallel processing software such as PVM have enabled the reutilization of existing astrodynamics software in distributed parallel processing environments, Computations once taking many days with traditional mainframes are now being performed in only a few hours. Efforts underway for the US Naval Space Command include conjunction prediction, uncorrelated target processing and a new space object catalog based on orbit determination and prediction with special perturbations methods.
Instruction-level parallel processing.
Fisher, J A; Rau, R
1991-09-13
The performance of microprocessors has increased steadily over the past 20 years at a rate of about 50% per year. This is the cumulative result of architectural improvements as well as increases in circuit speed. Moreover, this improvement has been obtained in a transparent fashion, that is, without requiring programmers to rethink their algorithms and programs, thereby enabling the tremendous proliferation of computers that we see today. To continue this performance growth, microprocessor designers have incorporated instruction-level parallelism (ILP) into new designs. ILP utilizes the parallel execution ofthe lowest level computer operations-adds, multiplies, loads, and so on-to increase performance transparently. The use of ILP promises to make possible, within the next few years, microprocessors whose performance is many times that of a CRAY-IS. This article provides an overview of ILP, with an emphasis on ILP architectures-superscalar, VLIW, and dataflow processors-and the compiler techniques necessary to make ILP work well. PMID:17831442
Multi-prediction particle filter for efficient parallelized implementation
NASA Astrophysics Data System (ADS)
Chu, Chun-Yuan; Chao, Chih-Hao; Chao, Min-An; Wu, An-Yeu Andy
2011-12-01
Particle filter (PF) is an emerging signal processing methodology, which can effectively deal with nonlinear and non-Gaussian signals by a sample-based approximation of the state probability density function. The particle generation of the PF is a data-independent procedure and can be implemented in parallel. However, the resampling procedure in the PF is a sequential task in natural and difficult to be parallelized. Based on the Amdahl's law, the sequential portion of a task limits the maximum speed-up of the parallelized implementation. Moreover, large particle number is usually required to obtain an accurate estimation, and the complexity of the resampling procedure is highly related to the number of particles. In this article, we propose a multi-prediction (MP) framework with two selection approaches. The proposed MP framework can reduce the required particle number for target estimation accuracy, and the sequential operation of the resampling can be reduced. Besides, the overhead of the MP framework can be easily compensated by parallel implementation. The proposed MP-PF alleviates the global sequential operation by increasing the local parallel computation. In addition, the MP-PF is very suitable for multi-core graphics processing unit (GPU) platform, which is a popular parallel processing architecture. We give prototypical implementations of the MP-PFs on multi-core GPU platform. For the classic bearing-only tracking experiments, the proposed MP-PF can be 25.1 and 15.3 times faster than the sequential importance resampling-PF with 10,000 and 20,000 particles, respectively. Hence, the proposed MP-PF can enhance the efficiency of the parallelization.
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.
An efficient parallel termination detection algorithm
Baker, A. H.; Crivelli, S.; Jessup, E. R.
2004-05-27
Information local to any one processor is insufficient to monitor the overall progress of most distributed computations. Typically, a second distributed computation for detecting termination of the main computation is necessary. In order to be a useful computational tool, the termination detection routine must operate concurrently with the main computation, adding minimal overhead, and it must promptly and correctly detect termination when it occurs. In this paper, we present a new algorithm for detecting the termination of a parallel computation on distributed-memory MIMD computers that satisfies all of those criteria. A variety of termination detection algorithms have been devised. Of these, the algorithm presented by Sinha, Kale, and Ramkumar (henceforth, the SKR algorithm) is unique in its ability to adapt to the load conditions of the system on which it runs, thereby minimizing the impact of termination detection on performance. Because their algorithm also detects termination quickly, we consider it to be the most efficient practical algorithm presently available. The termination detection algorithm presented here was developed for use in the PMESC programming library for distributed-memory MIMD computers. Like the SKR algorithm, our algorithm adapts to system loads and imposes little overhead. Also like the SKR algorithm, ours is tree-based, and it does not depend on any assumptions about the physical interconnection topology of the processors or the specifics of the distributed computation. In addition, our algorithm is easier to implement and requires only half as many tree traverses as does the SKR algorithm. This paper is organized as follows. In section 2, we define our computational model. In section 3, we review the SKR algorithm. We introduce our new algorithm in section 4, and prove its correctness in section 5. We discuss its efficiency and present experimental results in section 6.
Communication-efficient parallel architectures and algorithms for image computations
Alnuweiri, H.M.
1989-01-01
The main purpose of this dissertation is the design of efficient parallel techniques for image computations which require global operations on image pixels, as well as the development of parallel architectures with special communication features which can support global data movement efficiently. The class of image problems considered in this dissertation involves global operations on image pixels, and irregular (data-dependent) data movement operations. Such problems include histogramming, component labeling, proximity computations, computing the Hough Transform, computing convexity of regions and related properties such as computing the diameter and a smallest area enclosing rectangle for each region. Images with multiple figures and multiple labeled-sets of pixels are also considered. Efficient solutions to such problems involve integer sorting, graph theoretic techniques, and techniques from computational geometry. Although such solutions are not computationally intensive (they all require O(n{sup 2}) operations to be performed on an n {times} n image), they require global communications. The emphasis here is on developing parallel techniques for data movement, reduction, and distribution, which lead to processor-time optimal solutions for such problems on the proposed organizations. The proposed parallel architectures are based on a memory array which can be viewed as an arrangement of memory modules in a k-dimensional space such that the modules are connected to buses placed parallel to the orthogonal axes of the space, and each bus is connected to one processor or a group of processors. It will be shown that such organizations are communication-efficient and are thus highly suited to the image problems considered here, and also to several other classes of problems. The proposed organizations have p processors and O(n{sup 2}) words of memory to process n {times} n images.
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.
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
Parallel processing of a rotating shaft simulation
NASA Technical Reports Server (NTRS)
Arpasi, Dale J.
1989-01-01
A FORTRAN program describing the vibration modes of a rotor-bearing system is analyzed for parellelism in this simulation using a Pascal-like structured language. Potential vector operations are also identified. A critical path through the simulation is identified and used in conjunction with somewhat fictitious processor characteristics to determine the time to calculate the problem on a parallel processing system having those characteristics. A parallel processing overhead time is included as a parameter for proper evaluation of the gain over serial calculation. The serial calculation time is determined for the same fictitious system. An improvement of up to 640 percent is possible depending on the value of the overhead time. Based on the analysis, certain conclusions are drawn pertaining to the development needs of parallel processing technology, and to the specification of parallel processing systems to meet computational needs.
Efficient parallel simulation of CO2 geologic sequestration insaline aquifers
Zhang, Keni; Doughty, Christine; Wu, Yu-Shu; Pruess, Karsten
2007-01-01
An efficient parallel simulator for large-scale, long-termCO2 geologic sequestration in saline aquifers has been developed. Theparallel simulator is a three-dimensional, fully implicit model thatsolves large, sparse linear systems arising from discretization of thepartial differential equations for mass and energy balance in porous andfractured media. The simulator is based on the ECO2N module of the TOUGH2code and inherits all the process capabilities of the single-CPU TOUGH2code, including a comprehensive description of the thermodynamics andthermophysical properties of H2O-NaCl- CO2 mixtures, modeling singleand/or two-phase isothermal or non-isothermal flow processes, two-phasemixtures, fluid phases appearing or disappearing, as well as saltprecipitation or dissolution. The new parallel simulator uses MPI forparallel implementation, the METIS software package for simulation domainpartitioning, and the iterative parallel linear solver package Aztec forsolving linear equations by multiple processors. In addition, theparallel simulator has been implemented with an efficient communicationscheme. Test examples show that a linear or super-linear speedup can beobtained on Linux clusters as well as on supercomputers. Because of thesignificant improvement in both simulation time and memory requirement,the new simulator provides a powerful tool for tackling larger scale andmore complex problems than can be solved by single-CPU codes. Ahigh-resolution simulation example is presented that models buoyantconvection, induced by a small increase in brine density caused bydissolution of CO2.
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.
FORTRAN Extensions for Modular Parallel Processing
Energy Science and Technology Software Center (ESTSC)
1996-01-12
FORTRAN M is a small set of extensions to FORTRAN that supports a modular approach to the construction of sequential and parallel programs. FORTRAN M programs use channels to plug together processes which may be written in FORTRAN M or FORTRAN 77. Processes communicate by sending and receiving messages on channels. Channels and processes can be created dynamically, but programs remain deterministic unless specialized nondeterministic constructs are used.
Associative massively parallel processor for video processing
NASA Astrophysics Data System (ADS)
Krikelis, Argy; Tawiah, T.
1996-03-01
Massively parallel processing architectures have matured primarily through image processing and computer vision application. The similarity of processing requirements between these areas and video processing suggest that they should be very appropriate for video processing applications. This research describes the use of an associative massively parallel processing based system for video compression which includes architectural and system description, discussion of the implementation of compression tasks such as DCT/IDCT, Motion Estimation and Quantization and system evaluation. The core of the processing system is the ASP (Associative String Processor) architecture a modular massively parallel, programmable and inherently fault-tolerant fine-grain SIMD processing architecture incorporating a string of identical APEs (Associative Processing Elements), a reconfigurable inter-processor communication network and a Vector Data Buffer for fully-overlapped data input-output. For video compression applications a prototype system is developed, which is using ASP modules to implement the required compression tasks. This scheme leads to a linear speed up of the computation by simply adding more APEs to the modules.
Photon detection with parallel asynchronous processing
NASA Technical Reports Server (NTRS)
Coon, D. D.; Perera, A. G. U.
1990-01-01
An approach to photon detection with a parallel asynchronous signal processor is described. The visible or IR photon-detection capability of the silicon p(+)-n-n(+) detectors and the parallel asynchronous processing are addressed separately. This approach would permit an independent analog processing channel to be dedicated to every pixel. A laminar architecture consisting of a stack of planar arrays of the devices would form a 2D array processor with a 2D array of inputs located directly behind a focal-plane detector array. A 2D image data stream would propagate in neuronlike asynchronous pulse-coded form through the laminar processor. Such systems can integrate image acquisition and image processing. Acquisition and processing would be performed concurrently as in natural vision systems. The possibility of multispectral image processing is addressed.
NASA Astrophysics Data System (ADS)
Fainberg, J.; Schaefer, W.
2015-06-01
A new algorithm for heat exchange between thermally coupled diffusely radiating interfaces is presented, which can be applied for closed and half open transparent radiating cavities. Interfaces between opaque and transparent materials are automatically detected and subdivided into elementary radiation surfaces named tiles. Contrary to the classical view factor method, the fixed unit sphere area subdivision oriented along the normal tile direction is projected onto the surrounding radiation mesh and not vice versa. Then, the total incident radiating flux of the receiver is approximated as a direct sum of radiation intensities of representative “senders” with the same weight factor. A hierarchical scheme for the space angle subdivision is selected in order to minimize the total memory and the computational demands during thermal calculations. Direct visibility is tested by means of a voxel-based ray tracing method accelerated by means of the anisotropic Chebyshev distance method, which reuses the computational grid as a Chebyshev one. The ray tracing algorithm is fully parallelized using MPI and takes advantage of the balanced distribution of all available tiles among all CPU's. This approach allows tracing of each particular ray without any communication. The algorithm has been implemented in a commercial casting process simulation software. The accuracy and computational performance of the new radiation model for heat treatment, investment and ingot casting applications is illustrated using industrial examples.
Casting pearls ballistically: Efficient massively parallel simulation of particle deposition
Lubachevsky, B.D.; Privman, V.; Roy, S.C.
1996-06-01
We simulate ballistic particle deposition wherein a large number of spherical particles are {open_quotes}cast{close_quotes} vertically over a planar horizontal surface. Upon first contact (with the surface or with a previously deposited particle) each particle stops. This model helps material scientists to study the adsorption and sediment formation. The model is sequential, with particles deposited one by one. We have found an equivalent formulation using a continuous time random process and we simulate the latter in parallel using a method similar to the one previously employed for simulating Ising spins. We augment the parallel algorithm for simulating Ising spins with several techniques aimed at the increase of efficiency of producing the particle configuration and statistics collection. Some of these techniques are similar to earlier ones. We implement the resulting algorithm on a 16K PE MasPar MP-1 and a 4K PE MasPar MP-2. The parallel code runs on MasPar computers nearly two orders of magnitude faster than an optimized sequential code runs on a fast workstation. 17 refs., 9 figs.
Casting Pearls Ballistically: Efficient Massively Parallel Simulation of Particle Deposition
NASA Astrophysics Data System (ADS)
Lubachevsky, Boris D.; Privman, Vladimir; Roy, Subhas C.
1996-06-01
We simulate ballistic particle deposition wherein a large number of spherical particles are "cast" vertically over a planar horizontal surface. Upon first contact (with the surface or with a previously deposited particle) each particle stops. This model helps material scientists to study the adsorption and sediment formation. The model is sequential, with particles deposited one by one. We have found an equivalent formulation using a continuous time random process and we simulate the latter in parallel using a method similar to the one previously employed for simulating Ising spins. We augment the parallel algorithm for simulating Ising spins with several techniques aimed at the increase of efficiency of producing the particle configuration and statistics collection. Some of these techniques are similar to earlier ones. We implement the resulting algorithm on a 16K PE MasPar MP-1 and a 4K PE MasPar MP-2. The parallel code runs on MasPar computers nearly two orders of magnitude faster than an optimized sequential code runs on a fast workstation.
Parallel and Serial Processes in Visual Search
ERIC Educational Resources Information Center
Thornton, Thomas L.; Gilden, David L.
2007-01-01
A long-standing issue in the study of how people acquire visual information centers around the scheduling and deployment of attentional resources: Is the process serial, or is it parallel? A substantial empirical effort has been dedicated to resolving this issue. However, the results remain largely inconclusive because the methodologies that have…
Hypercluster parallel processing library user's manual
NASA Technical Reports Server (NTRS)
Quealy, Angela
1990-01-01
This User's Manual describes the Hypercluster Parallel Processing Library, composed of FORTRAN-callable subroutines which enable a FORTRAN programmer to manipulate and transfer information throughout the Hypercluster at NASA Lewis Research Center. Each subroutine and its parameters are described in detail. A simple heat flow application using Laplace's equation is included to demonstrate the use of some of the library's subroutines. The manual can be used initially as an introduction to the parallel features provided by the library. Thereafter it can be used as a reference when programming an application.
Efficient wiring of reconfigurable parallel processors
Greenberg, D.S.
1992-08-28
The advent of chips which include one or more CPUS, some local memory, and rudimentary communications and routing hardware has opened a new area in computer architecture design. What is the best way to connect these chips to solve particular problems This paper defines the efficiency of a wiring scheme for a set of communication patterns. It then gives upper and lower bounds on the best efficiency achievable. It also presents simple wiring schemes for some stencil patterns used in mesh-based discrete simulations.
Efficient wiring of reconfigurable parallel processors
Greenberg, D.S.
1992-08-28
The advent of chips which include one or more CPUS, some local memory, and rudimentary communications and routing hardware has opened a new area in computer architecture design. What is the best way to connect these chips to solve particular problems? This paper defines the efficiency of a wiring scheme for a set of communication patterns. It then gives upper and lower bounds on the best efficiency achievable. It also presents simple wiring schemes for some stencil patterns used in mesh-based discrete simulations.
Efficiency Evaluation of Cray XT Parallel IO Stack
Yu, Weikuan; Oral, H Sarp; Vetter, Jeffrey S; Barrett, Richard F
2007-01-01
PetaScale computing platforms need to be coupled with efficient IO subsystems that can deliver commensurate IO throughput to scientific applications. In order to gain insights into the deliverable IO efficiency on the Cray XT platform at ORNL, this paper presents an in-depth efficiency evaluation of its parallel IO software stack. Our evaluation covers the performance of a variety of parallel IO interfaces, including POSIX IO, MPI-IO, and HDF5. Moreover, we describe several tuning parameters for these interfaces and present their effectiveness in enhancing the IO efficiency.
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.
Parallel heterogeneous architectures for efficient OMP compressive sensing reconstruction
NASA Astrophysics Data System (ADS)
Kulkarni, Amey; Stanislaus, Jerome L.; Mohsenin, Tinoosh
2014-05-01
Compressive Sensing (CS) is a novel scheme, in which a signal that is sparse in a known transform domain can be reconstructed using fewer samples. The signal reconstruction techniques are computationally intensive and have sluggish performance, which make them impractical for real-time processing applications . The paper presents novel architectures for Orthogonal Matching Pursuit algorithm, one of the popular CS reconstruction algorithms. We show the implementation results of proposed architectures on FPGA, ASIC and on a custom many-core platform. For FPGA and ASIC implementation, a novel thresholding method is used to reduce the processing time for the optimization problem by at least 25%. Whereas, for the custom many-core platform, efficient parallelization techniques are applied, to reconstruct signals with variant signal lengths of N and sparsity of m. The algorithm is divided into three kernels. Each kernel is parallelized to reduce execution time, whereas efficient reuse of the matrix operators allows us to reduce area. Matrix operations are efficiently paralellized by taking advantage of blocked algorithms. For demonstration purpose, all architectures reconstruct a 256-length signal with maximum sparsity of 8 using 64 measurements. Implementation on Xilinx Virtex-5 FPGA, requires 27.14 μs to reconstruct the signal using basic OMP. Whereas, with thresholding method it requires 18 μs. ASIC implementation reconstructs the signal in 13 μs. However, our custom many-core, operating at 1.18 GHz, takes 18.28 μs to complete. Our results show that compared to the previous published work of the same algorithm and matrix size, proposed architectures for FPGA and ASIC implementations perform 1.3x and 1.8x respectively faster. Also, the proposed many-core implementation performs 3000x faster than the CPU and 2000x faster than the GPU.
High-speed parallel-processing networks for advanced architectures
Morgan, D.R.
1988-06-01
This paper describes various parallel-processing architecture networks that are candidates for eventual airborne use. An attempt at projecting which type of network is suitable or optimum for specific metafunction or stand-alone applications is made. However, specific algorithms will need to be developed and bench marks executed before firm conclusions can be drawn. Also, a conceptual projection of how these processors can be built in small, flyable units through the use of wafer-scale integration is offered. The use of the PAVE PILLAR system architecture to provide system level support for these tightly coupled networks is described. The author concludes that: (1) extremely high processing speeds implemented in flyable hardware is possible through parallel-processing networks if development programs are pursued; (2) dramatic speed enhancements through parallel processing requires an excellent match between the algorithm and computer-network architecture; (3) matching several high speed parallel oriented algorithms across the aircraft system to a limited set of hardware modules may be the most cost-effective approach to achieving speed enhancements; and (4) software-development tools and improved operating systems will need to be developed to support efficient parallel-processor use.
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.
Efficient sequential and parallel algorithms for record linkage
Mamun, Abdullah-Al; Mi, Tian; Aseltine, Robert; Rajasekaran, Sanguthevar
2014-01-01
Background and objective Integrating data from multiple sources is a crucial and challenging problem. Even though there exist numerous algorithms for record linkage or deduplication, they suffer from either large time needs or restrictions on the number of datasets that they can integrate. In this paper we report efficient sequential and parallel algorithms for record linkage which handle any number of datasets and outperform previous algorithms. Methods Our algorithms employ hierarchical clustering algorithms as the basis. A key idea that we use is radix sorting on certain attributes to eliminate identical records before any further processing. Another novel idea is to form a graph that links similar records and find the connected components. Results Our sequential and parallel algorithms have been tested on a real dataset of 1 083 878 records and synthetic datasets ranging in size from 50 000 to 9 000 000 records. Our sequential algorithm runs at least two times faster, for any dataset, than the previous best-known algorithm, the two-phase algorithm using faster computation of the edit distance (TPA (FCED)). The speedups obtained by our parallel algorithm are almost linear. For example, we get a speedup of 7.5 with 8 cores (residing in a single node), 14.1 with 16 cores (residing in two nodes), and 26.4 with 32 cores (residing in four nodes). Conclusions We have compared the performance of our sequential algorithm with TPA (FCED) and found that our algorithm outperforms the previous one. The accuracy is the same as that of this previous best-known algorithm. PMID:24154837
An efficient parallel algorithm for accelerating computational protein design
Zhou, Yichao; Xu, Wei; Donald, Bruce R.; Zeng, Jianyang
2014-01-01
Motivation: Structure-based computational protein design (SCPR) is an important topic in protein engineering. Under the assumption of a rigid backbone and a finite set of discrete conformations of side-chains, various methods have been proposed to address this problem. A popular method is to combine the dead-end elimination (DEE) and A* tree search algorithms, which provably finds the global minimum energy conformation (GMEC) solution. Results: In this article, we improve the efficiency of computing A* heuristic functions for protein design and propose a variant of A* algorithm in which the search process can be performed on a single GPU in a massively parallel fashion. In addition, we make some efforts to address the memory exceeding problem in A* search. As a result, our enhancements can achieve a significant speedup of the A*-based protein design algorithm by four orders of magnitude on large-scale test data through pre-computation and parallelization, while still maintaining an acceptable memory overhead. We also show that our parallel A* search algorithm could be successfully combined with iMinDEE, a state-of-the-art DEE criterion, for rotamer pruning to further improve SCPR with the consideration of continuous side-chain flexibility. Availability: Our software is available and distributed open-source under the GNU Lesser General License Version 2.1 (GNU, February 1999). The source code can be downloaded from http://www.cs.duke.edu/donaldlab/osprey.php or http://iiis.tsinghua.edu.cn/∼compbio/software.html. Contact: zengjy321@tsinghua.edu.cn Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24931991
An Expert System for the Development of Efficient Parallel Code
NASA Technical Reports Server (NTRS)
Jost, Gabriele; Chun, Robert; Jin, Hao-Qiang; Labarta, Jesus; Gimenez, Judit
2004-01-01
We have built the prototype of an expert system to assist the user in the development of efficient parallel code. The system was integrated into the parallel programming environment that is currently being developed at NASA Ames. The expert system interfaces to tools for automatic parallelization and performance analysis. It uses static program structure information and performance data in order to automatically determine causes of poor performance and to make suggestions for improvements. In this paper we give an overview of our programming environment, describe the prototype implementation of our expert system, and demonstrate its usefulness with several case studies.
A multiarchitecture parallel-processing development environment
NASA Technical Reports Server (NTRS)
Townsend, Scott; Blech, Richard; Cole, Gary
1993-01-01
A description is given of the hardware and software of a multiprocessor test bed - the second generation Hypercluster system. The Hypercluster architecture consists of a standard hypercube distributed-memory topology, with multiprocessor shared-memory nodes. By using standard, off-the-shelf hardware, the system can be upgraded to use rapidly improving computer technology. The Hypercluster's multiarchitecture nature makes it suitable for researching parallel algorithms in computational field simulation applications (e.g., computational fluid dynamics). The dedicated test-bed environment of the Hypercluster and its custom-built software allows experiments with various parallel-processing concepts such as message passing algorithms, debugging tools, and computational 'steering'. Such research would be difficult, if not impossible, to achieve on shared, commercial systems.
Oxytocin: parallel processing in the social brain?
Dölen, Gül
2015-06-01
Early studies attempting to disentangle the network complexity of the brain exploited the accessibility of sensory receptive fields to reveal circuits made up of synapses connected both in series and in parallel. More recently, extension of this organisational principle beyond the sensory systems has been made possible by the advent of modern molecular, viral and optogenetic approaches. Here, evidence supporting parallel processing of social behaviours mediated by oxytocin is reviewed. Understanding oxytocinergic signalling from this perspective has significant implications for the design of oxytocin-based therapeutic interventions aimed at disorders such as autism, where disrupted social function is a core clinical feature. Moreover, identification of opportunities for novel technology development will require a better appreciation of the complexity of the circuit-level organisation of the social brain. PMID:25912257
Efficient Multidisciplinary Analysis Procedure Using Multi-Level Parallelization Approach
NASA Technical Reports Server (NTRS)
Byun, Chansup; Hatay, Ferhat; Farhangnia, Mehrdad; Guruswamy, Guru; VanDalsem, William R. (Technical Monitor)
1997-01-01
Multidisciplinary applications are suitable for parallel computing environment by adopting the domain decomposition method. Immediately, a multidisciplinary application can be parallelized by solving each discipline separately. In order to perform coupled multidisciplinary analysis, coupling of each discipline can be accomplished by exchanging boundary data at the interfaces. This is regarded as discipline-level parallelization. Next level could be a "coarse-grain" parallelization of each discipline, which mainly depends on the physical geometry and nature of each discipline. For example, it is almost impossible for structured-grid based computational fluid dynamics codes to do flow analysis of an aircraft by using a single grid because of the complexity of its configuration. Thus, multi-block grid is commonly used to describe the details of complex geometry. Similarly, in structural analysis, the structure is frequently subdivided into substructures. Thus, the computation of each subdomain can be easily parallelized since each subdomain is solved separately independent of other domains. The parallelization is accomplished by solving each subdomain separately on a separate processor and exchanging the boundary conditions at domain interfaces periodically. However, the physical decomposition of the domain introduces explicit boundary conditions at the domain interfaces. This is not desirable for critical areas such as those containing shock waves or flow separations. Thus, a "fine-grain" parallelization is introduced to overcome this problem. The "fine-grain" parallelization is one that solves exactly the same system of equations of a subdomain by using more than one processors without introducing any explicit boundary conditions. An efficient multidisciplinary analysis procedure can be accomplished by successfully combining the above multi-level parallelism. A multidisciplinary analysis code, ENSAERO developed at NASA Ames Research Center is used in this study to
Parallel processing in the mammalian retina.
Wässle, Heinz
2004-10-01
Our eyes send different 'images' of the outside world to the brain - an image of contours (line drawing), a colour image (watercolour painting) or an image of moving objects (movie). This is commonly referred to as parallel processing, and starts as early as the first synapse of the retina, the cone pedicle. Here, the molecular composition of the transmitter receptors of the postsynaptic neurons defines which images are transferred to the inner retina. Within the second synaptic layer - the inner plexiform layer - circuits that involve complex inhibitory and excitatory interactions represent filters that select 'what the eye tells the brain'. PMID:15378035
Parallel-Processing Algorithms For Dynamics Of Manipulators
NASA Technical Reports Server (NTRS)
Fijany, Amir; Bejczy, Antal K.
1991-01-01
Class of parallel and parallel/pipeline algorithms presented for more efficient computation of manipulator inertia matrix. Essential for implementing advanced dynamic control schemes as well as dynamic simulation of manipulator motion.
Parallel Processing Strategies of the Primate Visual System
Nassi, Jonathan J.; Callaway, Edward M.
2009-01-01
Preface Incoming sensory information is sent to the brain along modality-specific channels corresponding to the five senses. Each of these channels further parses the incoming signals into parallel streams to provide a compact, efficient input to the brain. Ultimately, these parallel input signals must be elaborated upon and integrated within the cortex to provide a unified and coherent percept. Recent studies in the primate visual cortex have greatly contributed to our understanding of how this goal is accomplished. Multiple strategies including retinal tiling, hierarchical and parallel processing and modularity, defined spatially and by cell type-specific connectivity, are all used by the visual system to recover the rich detail of our visual surroundings. PMID:19352403
Parallel processing for digital picture comparison
NASA Technical Reports Server (NTRS)
Cheng, H. D.; Kou, L. T.
1987-01-01
In picture processing an important problem is to identify two digital pictures of the same scene taken under different lighting conditions. This kind of problem can be found in remote sensing, satellite signal processing and the related areas. The identification can be done by transforming the gray levels so that the gray level histograms of the two pictures are closely matched. The transformation problem can be solved by using the packing method. Researchers propose a VLSI architecture consisting of m x n processing elements with extensive parallel and pipelining computation capabilities to speed up the transformation with the time complexity 0(max(m,n)), where m and n are the numbers of the gray levels of the input picture and the reference picture respectively. If using uniprocessor and a dynamic programming algorithm, the time complexity will be 0(m(3)xn). The algorithm partition problem, as an important issue in VLSI design, is discussed. Verification of the proposed architecture is also given.
Memory Scalability and Efficiency Analysis of Parallel Codes
Janjusic, Tommy; Kartsaklis, Christos
2015-01-01
Memory scalability is an enduring problem and bottleneck that plagues many parallel codes. Parallel codes designed for High Performance Systems are typically designed over the span of several, and in some instances 10+, years. As a result, optimization practices which were appropriate for earlier systems may no longer be valid and thus require careful optimization consideration. Specifically, parallel codes whose memory footprint is a function of their scalability must be carefully considered for future exa-scale systems. In this paper we present a methodology and tool to study the memory scalability of parallel codes. Using our methodology we evaluate an application s memory footprint as a function of scalability, which we coined memory efficiency, and describe our results. In particular, using our in-house tools we can pinpoint the specific application components which contribute to the application s overall memory foot-print (application data- structures, libraries, etc.).
Parallel tools in HEVC for high-throughput processing
NASA Astrophysics Data System (ADS)
Zhou, Minhua; Sze, Vivienne; Budagavi, Madhukar
2012-10-01
HEVC (High Efficiency Video Coding) is the next-generation video coding standard being jointly developed by the ITU-T VCEG and ISO/IEC MPEG JCT-VC team. In addition to the high coding efficiency, which is expected to provide 50% more bit-rate reduction when compared to H.264/AVC, HEVC has built-in parallel processing tools to address bitrate, pixel-rate and motion estimation (ME) throughput requirements. This paper describes how CABAC, which is also used in H.264/AVC, has been redesigned for improved throughput, and how parallel merge/skip and tiles, which are new tools introduced for HEVC, enable high-throughput processing. CABAC has data dependencies which make it difficult to parallelize and thus limit its throughput. The prediction error/residual, represented as quantized transform coefficients, accounts for the majority of the CABAC workload. Various improvements have been made to the context selection and scans in transform coefficient coding that enable CABAC in HEVC to potentially achieve higher throughput and increased coding gains relative to H.264/AVC. The merge/skip mode is a coding efficiency enhancement tool in HEVC; the parallel merge/skip breaks dependency between the regular and merge/skip ME, which provides flexibility for high throughput and high efficiency HEVC encoder designs. For ultra high definition (UHD) video, such as 4kx2k and 8kx4k resolutions, low-latency and real-time processing may be beyond the capability of a single core codec. Tiles are an effective tool which enables pixel-rate balancing among the cores to achieve parallel processing with a throughput scalable implementation of multi-core UHD video codec. With the evenly divided tiles, a multi-core video codec can be realized by simply replicating single core codec and adding a tile boundary processing core on top of that. These tools illustrate that accounting for implementation cost when designing video coding algorithms can enable higher processing speed and reduce
Parallel-processing a large scientific problem
Hiromoto, R.
1982-01-01
The author discusses a parallel-processing experiment that uses a particle-in-cell (PIC) code to study the feasibility of doing large-scale scientific calculations on multiple-processor architectures. A multithread version of this Los Alamos PIC code was successfully implemented and timed on a Univac system 1100/80 computer. Use of a single copy of the instruction stream, and common memory to hold data, eliminated data transmission between processors. The multiple-processing algorithm exploits the Pic code's high degree of large, independent tasks, as well as the configuration of the Univac system 1100/80. Timing results for the multithread version of the PIC code using one, two, three, and four identical processors are given and are shown to have promising speedup times when compared to the overall run times measured for a single-thread version of the PIC code. 4 references.
Parallel processing a large scientific problem
Hiromoto, R.
1982-01-01
A parallel-processing experiment is discussed that uses a particle-in-cell (PIC) code to study the feasibility of doing large-scale scientific calculations on multiple-processor architectures. A multithread version of this Los Alamos PIC code was successfully implemented and timed on a UNIVAC System 1100/80 computer. Use of a single copy of the instruction stream, and common memory to hold data, eliminated data transmission between processors. The multiple-processing algorithm exploits the PIC code's high degree of large, independent tasks, as well as the configuration of the UNIVAC System 1100/80. Timing results for the multithread version of the PIC code using one, two, three, and four identical processors are given and are shown to have promising speedup times when compared to the overall run times measured for a single-thread version of the PIC code.
Parallel digital signal processing architectures for image processing
NASA Astrophysics Data System (ADS)
Kshirsagar, Shirish P.; Hartley, David A.; Harvey, David M.; Hobson, Clifford A.
1994-10-01
This paper describes research into a high speed image processing system using parallel digital signal processors for the processing of electro-optic images. The objective of the system is to reduce the processing time of non-contact type inspection problems including industrial and medical applications. A single processor can not deliver sufficient processing power required for the use of applications hence, a MIMD system is designed and constructed to enable fast processing of electro-optic images. The Texas Instruments TMS320C40 digital signal processor is used due to its high speed floating point CPU and the support for the parallel processing environment. A custom designed VISION bus is provided to transfer images between processors. The system is being applied for solder joint inspection of high technology printed circuit boards.
Organizing Compression of Hyperspectral Imagery to Allow Efficient Parallel Decompression
NASA Technical Reports Server (NTRS)
Klimesh, Matthew A.; Kiely, Aaron B.
2014-01-01
family of schemes has been devised for organizing the output of an algorithm for predictive data compression of hyperspectral imagery so as to allow efficient parallelization in both the compressor and decompressor. In these schemes, the compressor performs a number of iterations, during each of which a portion of the data is compressed via parallel threads operating on independent portions of the data. The general idea is that for each iteration it is predetermined how much compressed data will be produced from each thread.
A Parallel Processing Algorithm for Gravity Inversion
NASA Astrophysics Data System (ADS)
Frasheri, Neki; Bushati, Salvatore; Frasheri, Alfred
2013-04-01
The paper presents results of using MPI parallel processing for the 3D inversion of gravity anomalies. The work is done under the FP7 project HP-SEE (http://www.hp-see.eu/). The inversion of geophysical anomalies remains a challenge, and the use of parallel processing can be a tool to achieve better results, "compensating" the complexity of the ill-posed problem of inversion with the increase of volume of calculations. We considered the gravity as the simplest case of physical fields and experimented an algorithm based in the methodology known as CLEAN and developed by Högbom in 1974. The 3D geosection was discretized in finite cuboid elements and represented by a 3D array of nodes, while the ground surface where the anomaly is observed as a 2D array of points. Starting from a geosection with mass density zero in all nodes, iteratively the algorithm defines the 3D node that offers the best anomaly shape that approximates the observed anomaly minimizing the least squares error; the mass density in the best 3D node is modified with a prefixed density step and the related effect subtracted from the observed anomaly; the process continues until some criteria is fulfilled. Theoretical complexity of he algorithm was evaluated on the basis of iterations and run-time for a geosection discretized in different scales. We considered the average number N of nodes in one edge of the 3D array. The order of number of iterations was evaluated O(N^3); and the order of run-time was evaluated O(N^8). We used several different methods for the identification of the 3D node which effect offers the best least squares error in approximating the observed anomaly: unweighted least squares error for the whole 2D array of anomalous points; weighting least squares error by the inverted value of observed anomaly over each 3D node; and limiting the area of 2D anomalous points where least squares are calculated over shallow 3D nodes. By comparing results from the inversion of single body and two
Fault Tolerance and Parallel Processing for NGST
NASA Astrophysics Data System (ADS)
Sengupta, R.; Offenberg, J. D.; Fixsen, D. J.; Nieto-Santisteban, M. A.; Hanisch, R. J.; Stockman, H. S.; Mather, J. C.
1999-12-01
The Next Generation Space Telescope (NGST) Image Processing Group is developing scalable cosmic ray rejection and data compression algorithms for parallel processors as part of NASA's Remote Exploration and Experimentation (REE) Project. The primary intention of the REE project is to use commercial-off-the shelf (COTS) technology to develop scalable, low-power, fault tolerant, high performance computers in space. NGST is one of the applications selected to demonstrate the benefit of having on-board supercomputing power. Real-time cosmic ray rejection would enable us to reduce the downlink data volume by as much as two orders of magnitude by combining multiple read-outs on the spacecraft rather than downlinking them separately. The combined read-outs can be further reduced in size by applying lossy and/or lossless data compression algorithms. This work is funded by NASA's REE project, managed by JPL.
Enjoying Sad Music: Paradox or Parallel Processes?
Schubert, Emery
2016-01-01
Enjoyment of negative emotions in music is seen by many as a paradox. This article argues that the paradox exists because it is difficult to view the process that generates enjoyment as being part of the same system that also generates the subjective negative feeling. Compensation theories explain the paradox as the compensation of a negative emotion by the concomitant presence of one or more positive emotions. But compensation brings us no closer to explaining the paradox because it does not explain how experiencing sadness itself is enjoyed. The solution proposed is that an emotion is determined by three critical processes-labeled motivational action tendency (MAT), subjective feeling (SF) and Appraisal. For many emotions the MAT and SF processes are coupled in valence. For example, happiness has positive MAT and positive SF, annoyance has negative MAT and negative SF. However, it is argued that in an aesthetic context, such as listening to music, emotion processes can become decoupled. The decoupling is controlled by the Appraisal process, which can assess if the context of the sadness is real-life (where coupling occurs) or aesthetic (where decoupling can occur). In an aesthetic context sadness retains its negative SF but the aversive, negative MAT is inhibited, leaving sadness to still be experienced as a negative valanced emotion, while contributing to the overall positive MAT. Individual differences, mood and previous experiences mediate the degree to which the aversive aspects of MAT are inhibited according to this Parallel Processing Hypothesis (PPH). The reason for hesitancy in considering or testing PPH, as well as the preponderance of research on sadness at the exclusion of other negative emotions, are discussed. PMID:27445752
Enjoying Sad Music: Paradox or Parallel Processes?
Schubert, Emery
2016-01-01
Enjoyment of negative emotions in music is seen by many as a paradox. This article argues that the paradox exists because it is difficult to view the process that generates enjoyment as being part of the same system that also generates the subjective negative feeling. Compensation theories explain the paradox as the compensation of a negative emotion by the concomitant presence of one or more positive emotions. But compensation brings us no closer to explaining the paradox because it does not explain how experiencing sadness itself is enjoyed. The solution proposed is that an emotion is determined by three critical processes—labeled motivational action tendency (MAT), subjective feeling (SF) and Appraisal. For many emotions the MAT and SF processes are coupled in valence. For example, happiness has positive MAT and positive SF, annoyance has negative MAT and negative SF. However, it is argued that in an aesthetic context, such as listening to music, emotion processes can become decoupled. The decoupling is controlled by the Appraisal process, which can assess if the context of the sadness is real-life (where coupling occurs) or aesthetic (where decoupling can occur). In an aesthetic context sadness retains its negative SF but the aversive, negative MAT is inhibited, leaving sadness to still be experienced as a negative valanced emotion, while contributing to the overall positive MAT. Individual differences, mood and previous experiences mediate the degree to which the aversive aspects of MAT are inhibited according to this Parallel Processing Hypothesis (PPH). The reason for hesitancy in considering or testing PPH, as well as the preponderance of research on sadness at the exclusion of other negative emotions, are discussed. PMID:27445752
Fully efficient time-parallelized quantum optimal control algorithm
NASA Astrophysics Data System (ADS)
Riahi, M. K.; Salomon, J.; Glaser, S. J.; Sugny, D.
2016-04-01
We present a time-parallelization method that enables one to accelerate the computation of quantum optimal control algorithms. We show that this approach is approximately fully efficient when based on a gradient method as optimization solver: the computational time is approximately divided by the number of available processors. The control of spin systems, molecular orientation, and Bose-Einstein condensates are used as illustrative examples to highlight the wide range of applications of this numerical scheme.
Efficient parallel tempering for first-order phase transitions.
Neuhaus, T; Magiera, M P; Hansmann, U H E
2007-10-01
We present a Monte Carlo algorithm that facilitates efficient parallel tempering simulations of the density of states g(E) . We show that the algorithm eliminates the supercritical slowing down in the case of the Q=20 and Q=256 Potts models in two dimensions, typical examples for systems with extreme first-order phase transitions. As recently predicted, and shown here, the microcanonical heat capacity along the calorimetric curve has negative values for finite systems. PMID:17995052
Communication-efficient parallel-graph algorithms. Master's thesis
Maggs, B.M.
1986-06-01
Communication bandwidth is a resource ignored by most parallel random-access machine (PRAM) models. This thesis shows that many graph problems can be solved in parallel, not only with polylogarithmic performance, but with efficient communication at each step of the computation. The communication requirements of an algorithm are measured in a restricted PRAM model called the distributed random-access machine (DRAM), which can be viewed as an abstraction of volume-universal networks such as fat trees. In this model, communication cost is measured in terms of the congestion of memory accesses across cuts of the machine. It is demonstrated that the recursive doubling technique frequently used in PRAM algorithms is wasteful of communication resources, and that recursive pairing can be used to perform many of the same functions more efficiently. The prefix computation is generalized on linear lists to trees and show that these tree-fix computations, which can be performed in a communication-efficient fashion using a variant of the tree-contraction technique of Miller and Reif, simplify many parallel graph algorithms in the literature.
Development and Applications of a Modular Parallel Process for Large Scale Fluid/Structures Problems
NASA Technical Reports Server (NTRS)
Guruswamy, Guru P.; Byun, Chansup; Kwak, Dochan (Technical Monitor)
2001-01-01
A modular process that can efficiently solve large scale multidisciplinary problems using massively parallel super computers is presented. The process integrates disciplines with diverse physical characteristics by retaining the efficiency of individual disciplines. Computational domain independence of individual disciplines is maintained using a meta programming approach. The process integrates disciplines without affecting the combined performance. Results are demonstrated for large scale aerospace problems on several supercomputers. The super scalability and portability of the approach is demonstrated on several parallel computers.
Development and Applications of a Modular Parallel Process for Large Scale Fluid/Structures Problems
NASA Technical Reports Server (NTRS)
Guruswamy, Guru P.; Kwak, Dochan (Technical Monitor)
2002-01-01
A modular process that can efficiently solve large scale multidisciplinary problems using massively parallel supercomputers is presented. The process integrates disciplines with diverse physical characteristics by retaining the efficiency of individual disciplines. Computational domain independence of individual disciplines is maintained using a meta programming approach. The process integrates disciplines without affecting the combined performance. Results are demonstrated for large scale aerospace problems on several supercomputers. The super scalability and portability of the approach is demonstrated on several parallel computers.
An intelligent allocation algorithm for parallel processing
NASA Technical Reports Server (NTRS)
Carroll, Chester C.; Homaifar, Abdollah; Ananthram, Kishan G.
1988-01-01
The problem of allocating nodes of a program graph to processors in a parallel processing architecture is considered. The algorithm is based on critical path analysis, some allocation heuristics, and the execution granularity of nodes in a program graph. These factors, and the structure of interprocessor communication network, influence the allocation. To achieve realistic estimations of the executive durations of allocations, the algorithm considers the fact that nodes in a program graph have to communicate through varying numbers of tokens. Coarse and fine granularities have been implemented, with interprocessor token-communication duration, varying from zero up to values comparable to the execution durations of individual nodes. The effect on allocation of communication network structures is demonstrated by performing allocations for crossbar (non-blocking) and star (blocking) networks. The algorithm assumes the availability of as many processors as it needs for the optimal allocation of any program graph. Hence, the focus of allocation has been on varying token-communication durations rather than varying the number of processors. The algorithm always utilizes as many processors as necessary for the optimal allocation of any program graph, depending upon granularity and characteristics of the interprocessor communication network.
Filtering versus parallel processing in RSVP tasks.
Botella, J; Eriksen, C W
1992-04-01
An experiment of McLean, D. E. Broadbent, and M. H. P. Broadbent (1983) using rapid serial visual presentation (RSVP) was replicated. A series of letters in one of 5 colors was presented, and the subject was asked to identify the letter that appeared in a designated color. There were several innovations in our procedure, the most important of which was the use of a response menu. After each trial, the subject was presented with 7 candidate letters from which to choose his/her response. In three experimental conditions, the target, the letter following the target, and all letters other than the target were, respectively, eliminated from the menu. In other conditions, the stimulus list was manipulated by repeating items in the series, repeating the color of successive items, or even eliminating the target color. By means of these manipulations, we were able to determine more precisely the information that subjects had obtained from the presentation of the stimulus series. Although we replicated the results of McLean et al. (1983), the more extensive information that our procedure produced was incompatible with the serial filter model that McLean et al. had used to describe their data. Overall, our results were more compatible with a parallel-processing account. Furthermore, intrusion errors are apparently not only a perceptual phenomenon but a memory problem as well. PMID:1603647
Fault tolerant massively parallel processing architecture
Balasubramanian, V.; Banerjee, P.
1987-08-01
This paper presents two massively parallel processing architectures suitable for solving a wide variety of algorithms of divide-and-conquer type for problems such as the discrete Fourier transform, production systems, design automation, and others. The first architecture, called the Chain-structured Butterfly ARchitecture (CBAR), consists of a two-dimensional array of N-L . (log/sub 2/(L)+1) processing elements (PE) organized as L levels of log/sub 2/(L)+1 stages, and which has the butterfly connection between PEs in consecutive stages with straight-through feedback between PEs in the last and first stages. This connection system has the desirable property of allowing thousands of PEs to be connected with O(N) connection cost, O(log/sub 2/(N/log/sub 2/N)) communication paths, and a small number (=4) of I/O ports per PE. However, this architecture is not fault tolerant. The authors, therefore, propose a second architecture, called the REconfigurable Chain-structured Butterfly ARchitecture (RECBAR), which is a modified version of the CBAR. The RECBAR possesses all the desirable features of the CBAR, with the number of I/O ports per PE increased to six, and uses O(log/sub 2/N)/N) overhead in PEs and approximately 50% overhead in links to achieve single-level fault tolerance. Reliability improvements of the RECBAR over the CBAR are studied. This paper also presents a distributed diagnostic and structuring algorithm for the RECBAR that enables the architecture to detect faults and structure itself accordingly within 2 . log/sub 2/(L)+1 time steps, thus making it a truly fault tolerant architecture.
Partitioning And Packing Equations For Parallel Processing
NASA Technical Reports Server (NTRS)
Arpasi, Dale J.; Milner, Edward J.
1989-01-01
Algorithm developed to identify parallelism in set of coupled ordinary differential equations that describe physical system and to divide set into parallel computational paths, along with parts of solution proceeds independently of others during at least part of time. Path-identifying algorithm creates number of paths consisting of equations that must be computed serially and table that gives dependent and independent arguments and "can start," "can end," and "must end" times of each equation. "Must end" time used subsequently by packing algorithm.
Programming Probabilistic Structural Analysis for Parallel Processing Computer
NASA Technical Reports Server (NTRS)
Sues, Robert H.; Chen, Heh-Chyun; Twisdale, Lawrence A.; Chamis, Christos C.; Murthy, Pappu L. N.
1991-01-01
The ultimate goal of this research program is to make Probabilistic Structural Analysis (PSA) computationally efficient and hence practical for the design environment by achieving large scale parallelism. The paper identifies the multiple levels of parallelism in PSA, identifies methodologies for exploiting this parallelism, describes the development of a parallel stochastic finite element code, and presents results of two example applications. It is demonstrated that speeds within five percent of those theoretically possible can be achieved. A special-purpose numerical technique, the stochastic preconditioned conjugate gradient method, is also presented and demonstrated to be extremely efficient for certain classes of PSA problems.
Time efficient 3-D electromagnetic modeling on massively parallel computers
Alumbaugh, D.L.; Newman, G.A.
1995-08-01
A numerical modeling algorithm has been developed to simulate the electromagnetic response of a three dimensional earth to a dipole source for frequencies ranging from 100 to 100MHz. The numerical problem is formulated in terms of a frequency domain--modified vector Helmholtz equation for the scattered electric fields. The resulting differential equation is approximated using a staggered finite difference grid which results in a linear system of equations for which the matrix is sparse and complex symmetric. The system of equations is solved using a preconditioned quasi-minimum-residual method. Dirichlet boundary conditions are employed at the edges of the mesh by setting the tangential electric fields equal to zero. At frequencies less than 1MHz, normal grid stretching is employed to mitigate unwanted reflections off the grid boundaries. For frequencies greater than this, absorbing boundary conditions must be employed by making the stretching parameters of the modified vector Helmholtz equation complex which introduces loss at the boundaries. To allow for faster calculation of realistic models, the original serial version of the code has been modified to run on a massively parallel architecture. This modification involves three distinct tasks; (1) mapping the finite difference stencil to a processor stencil which allows for the necessary information to be exchanged between processors that contain adjacent nodes in the model, (2) determining the most efficient method to input the model which is accomplished by dividing the input into ``global`` and ``local`` data and then reading the two sets in differently, and (3) deciding how to output the data which is an inherently nonparallel process.
Parallel Processing with Digital Signal Processing Hardware and Software
NASA Technical Reports Server (NTRS)
Swenson, Cory V.
1995-01-01
The assembling and testing of a parallel processing system is described which will allow a user to move a Digital Signal Processing (DSP) application from the design stage to the execution/analysis stage through the use of several software tools and hardware devices. The system will be used to demonstrate the feasibility of the Algorithm To Architecture Mapping Model (ATAMM) dataflow paradigm for static multiprocessor solutions of DSP applications. The individual components comprising the system are described followed by the installation procedure, research topics, and initial program development.
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.
NASA Technical Reports Server (NTRS)
Yarrow, Maurice; VanderWijngaart, Rob; Kutler, Paul (Technical Monitor)
1997-01-01
The first release of the MPI version of the LU NAS Parallel Benchmark (NPB2.0) performed poorly compared to its companion NPB2.0 codes. The later LU release (NPB2.1 & 2.2) runs up to two and a half times faster, thanks to a revised point access scheme and related communications scheme. The new scheme sends substantially fewer messages. is cache "friendly", and has a better load balance. We detail the, observations and modifications that resulted in this efficiency improvement, and show that the poor behavior of the original code resulted from deriving a message passing scheme from an algorithm originally devised for a vector architecture.
Experience in highly parallel processing using DAP
NASA Technical Reports Server (NTRS)
Parkinson, D.
1987-01-01
Distributed Array Processors (DAP) have been in day to day use for ten years and a large amount of user experience has been gained. The profile of user applications is similar to that of the Massively Parallel Processor (MPP) working group. Experience has shown that contrary to expectations, highly parallel systems provide excellent performance on so-called dirty problems such as the physics part of meteorological codes. The reasons for this observation are discussed. The arguments against replacing bit processors with floating point processors are also discussed.
The efficient parallel iterative solution of large sparse linear systems
Jones, M.T.; Plassmann, P.E.
1992-06-01
The development of efficient, general-purpose software for the iterative solution of sparse linear systems on a parallel MIMD computer requires an interesting combination of expertise. Parallel graph heuristics, convergence analysis, and basic linear algebra implementation issues must all be considered. In this paper, we discuss how we have incorporated recent results in these areas into a general-purpose iterative solver. First, we consider two recently developed parallel graph coloring heuristics. We show how the method proposed by Luby, based on determining maximal independent sets, can be modified to run in an asynchronous manner and give aa expected running time bound for this modified heuristic. In addition, a number of graph reduction heuristics are described that are used in our implementation to improve the individual processor performance. The effect of these various graph reductions on the solution of sparse triangular systems is categorized. Finally, we discuss the performance of this solver from the perspective of two large-scale applications: a piezoelectric crystal finite-element modeling problem, and a nonlinear optimization problem to determine the minimum energy configuration of a three-dimensional, layered superconductor model.
Parallel Processing in Visual Search Asymmetry
ERIC Educational Resources Information Center
Dosher, Barbara Anne; Han, Songmei; Lu, Zhong-Lin
2004-01-01
The difficulty of visual search may depend on assignment of the same visual elements as targets and distractors-search asymmetry. Easy C-in-O searches and difficult O-in-C searches are often associated with parallel and serial search, respectively. Here, the time course of visual search was measured for both tasks with speed-accuracy methods. The…
Functional & para-functional parallel processing
Not Available
1994-11-01
For years (about 20, in fact) dataflow researchers have argued for the use of dataflow (a subset of functional) languages for parallel computing, resting their proof on the ability to construct large-scale dataflow machines to realize the inherent parallelism in Functional programs. Unfortunately, such machines have never materialized as commercial products - instead, the market shows a vast variety of parallel multiprocessors that require special skills to program. It may be the case that these machines reflect a wrong direction in computer architecture design, and it may be the case that dataflow machines are the right way to go, but the proof is in the pudding, and thus far there does not exist even a prototype dataflow machine that can prove the {open_quote}dataflow thesis.{close_quote} Under the circumstances it would seem rather foolhardy simply to ignore the commercial parallel machines that are available now, regardless of one`s favorite programming methodology or concurrency model. It has been the authors` thesis that one can in fact use such machines effectively, while maintaining the concomitant thesis that functional programming is good for parallel computation. During the last two years the author has made considerable progress to support this two-fold thesis, and is now prepared to extend this work in several ways. The authors` particular interest, and presumably the primary interest to DOE, is to concentrate the work in the area of scientific computing, including functional language features, program development tools, and systems support tailored for scientific computing applications. The authors` desire to do this reflects confidence that this approach really will work for scientific computing - the author has spent two years proving the viability of the ideas, and now it`s time to put them into action.
Extraction of Hydrological Proximity Measures from DEMs using Parallel Processing
Tesfa, Teklu K.; Tarboton, David G.; Watson, Daniel W.; Schreuders, Kimberly A.; Baker, Matthew M.; Wallace, Robert M.
2011-12-01
queue data structure to order the processing of cells so that each cell is visited only once and the cross-process communications that are a standard part of MPI are handled in an efficient manner. This parallel approach allows analysis of much larger DEMs as compared to the serial recursive algorithms. In this paper, we present the definitions of the HPMs, the serial and parallel algorithms used in their extraction and their potential applications in hydrology, geomorphology and ecology.
Inverting Magnetic Data Using Parallel Processing
NASA Astrophysics Data System (ADS)
Connor, L. M.; Connor, C. B.
2002-12-01
We have collaborated to develop an innovative method for inverting magnetic data from high-resolution geomagnetic maps. Our method uses parallel computations and asynchronous communication among multiple nodes of a Beowulf cluster to produce geologically constrained 3-D models of magnetic anomalies. This modeling effort comes in response to the current revolution in gathering geophysical data. Interfacing kinematic differential GPS to magnetometers has presented geo-scientists with the daunting task of interpreting very high-resolution geomagnetic maps. Traditional methods of data interpretation, such as forward modeling, are sorely taxed. Our method manipulates a set of geologically constrained parameters to eventually build a geometric model that accurately represents the magnetic anomaly. Iterations of the code execute in parallel on multiple networked nodes via MPI, a message passing interface. Each node computes a magnetic solution at different geographical field locations based on a modeled set of geological parameters, using various forward calculations. The parameter sets are continually adjusted by the downhill simplex method. Calculated values are continually compared to the observed data using a goodness-of-fit test until all parameter sets generate the same result within a specified tolerance. A set of parameters producing an anomaly mimicking the observed anomaly is the result. By changing bounds on input parameters it is practical to quickly identify equivalent solutions. These techniques are applied to a high resolution geomagnetic data set consisting of 30,000 data points and four discrete magnetic anomalies. Data were smoothed and inverted using the parallel code. The subsurface was discretized and the depth to each unit, magnetization, and depth to the base of the entire structure were allowed to vary as independent parameters. Inversion clearly highlights volcanic features of the source rocks, including the truncated cone, crater, lava flows, and
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.
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.
ENERGY EFFICIENT LAUNDRY PROCESS
Tim Richter
2005-04-01
With the rising cost of energy and increased concerns for pollution and greenhouse gas emissions from power generation, increased focus is being put on energy efficiency. This study looks at several approaches to reducing energy consumption in clothes care appliances by considering the appliances and laundry chemistry as a system, rather than individually.
Parallel perfusion imaging processing using GPGPU
Zhu, Fan; Gonzalez, David Rodriguez; Carpenter, Trevor; Atkinson, Malcolm; Wardlaw, Joanna
2012-01-01
Background and purpose The objective of brain perfusion quantification is to generate parametric maps of relevant hemodynamic quantities such as cerebral blood flow (CBF), cerebral blood volume (CBV) and mean transit time (MTT) that can be used in diagnosis of acute stroke. These calculations involve deconvolution operations that can be very computationally expensive when using local Arterial Input Functions (AIF). As time is vitally important in the case of acute stroke, reducing the analysis time will reduce the number of brain cells damaged and increase the potential for recovery. Methods GPUs originated as graphics generation dedicated co-processors, but modern GPUs have evolved to become a more general processor capable of executing scientific computations. It provides a highly parallel computing environment due to its large number of computing cores and constitutes an affordable high performance computing method. In this paper, we will present the implementation of a deconvolution algorithm for brain perfusion quantification on GPGPU (General Purpose Graphics Processor Units) using the CUDA programming model. We present the serial and parallel implementations of such algorithms and the evaluation of the performance gains using GPUs. Results Our method has gained a 5.56 and 3.75 speedup for CT and MR images respectively. Conclusions It seems that using GPGPU is a desirable approach in perfusion imaging analysis, which does not harm the quality of cerebral hemodynamic maps but delivers results faster than the traditional computation. PMID:22824549
Efficient parallel algorithms for string editing and related problems
NASA Technical Reports Server (NTRS)
Apostolico, Alberto; Atallah, Mikhail J.; Larmore, Lawrence; Mcfaddin, H. S.
1988-01-01
The string editing problem for input strings x and y consists of transforming x into y by performing a series of weighted edit operations on x of overall minimum cost. An edit operation on x can be the deletion of a symbol from x, the insertion of a symbol in x or the substitution of a symbol x with another symbol. This problem has a well known O((absolute value of x)(absolute value of y)) time sequential solution (25). The efficient Program Requirements Analysis Methods (PRAM) parallel algorithms for the string editing problem are given. If m = ((absolute value of x),(absolute value of y)) and n = max((absolute value of x),(absolute value of y)), then the CREW bound is O (log m log n) time with O (mn/log m) processors. In all algorithms, space is O (mn).
Parafrase restructuring of FORTRAN code for parallel processing
NASA Technical Reports Server (NTRS)
Wadhwa, Atul
1988-01-01
Parafrase transforms a FORTRAN code, subroutine by subroutine, into a parallel code for a vector and/or shared-memory multiprocessor system. Parafrase is not a compiler; it transforms a code and provides information for a vector or concurrent process. Parafrase uses a data dependency to reveal parallelism among instructions. The data dependency test distinguishes between recurrences and statements that can be directly vectorized or parallelized. A number of transformations are required to build a data dependency graph.
Parallel-Processing Test Bed For Simulation Software
NASA Technical Reports Server (NTRS)
Blech, Richard; Cole, Gary; Townsend, Scott
1996-01-01
Second-generation Hypercluster computing system is multiprocessor test bed for research on parallel algorithms for simulation in fluid dynamics, electromagnetics, chemistry, and other fields with large computational requirements but relatively low input/output requirements. Built from standard, off-shelf hardware readily upgraded as improved technology becomes available. System used for experiments with such parallel-processing concepts as message-passing algorithms, debugging software tools, and computational steering. First-generation Hypercluster system described in "Hypercluster Parallel Processor" (LEW-15283).
Multiple-spot parallel processing for laser micronanofabrication
NASA Astrophysics Data System (ADS)
Kato, Jun-ichi; Takeyasu, Nobuyuki; Adachi, Yoshihiro; Sun, Hong-Bo; Kawata, Satoshi
2005-01-01
A tightly focused femtosecond laser has been established as a unique tool for micronanostructure fabrication due to its intrinsic three-dimensional processing. In this letter, we utilize a microlens array to produce multiple spots for parallel fabrication, giving rise to a revolutionary augmentation for our previously developed single-beam two-photon photopolymerization technology [S. Kawata, H.-B. Sun, T. Tanaka, and K. Takada, Nature (London) 412, 697 (2001)]. Two- and three-dimensional multiple structures, such as microletter set and self-standing microspring array, are demonstrated as examples of mass production. More than 200 spot simultaneous fabrication has been realized by optimizing the exposure condition for the photopolymerizable resin, i.e., a two-order increase of yield efficiency. Potential applications of this technique are discussed.
Parallel processing near supercomputers for science, engineering and AI
Walker, T.C.; Miller, R.K.
1987-01-01
The book explains the workings of several SIMD, MIMD, and dataflow architectures in non-theoretical terminology. The impact of parallel processing computer is examined. Application areas are described, and several case studies are included. The parallel processing projects and products of 37 international research groups and 27 leading corporations are presented. A survey of experts in the field explores opinions and forecasts on general architecture, problem solving strategies, and applications. Views of experts in the United States, Japan, and Europe are compared. The international markets for parallel processing computers are examined for 1986, 1988, and 1990.
An Airborne Onboard Parallel Processing Testbed
NASA Technical Reports Server (NTRS)
Mandl, Daniel J.
2014-01-01
This presentation provides information on the progress the Intelligent Payload Module (IPM) development effort. In addition, a vision is presented on integration of the IPM architecture with the GeoSocial Application Program Interface (API) architecture to enable efficient distribution of satellite data products.
Boost Process Heating Efficiency - PHAST
2005-05-01
Use the Process Heating Assessment and Survey Tool (PHAST) to survey all process heating equipment within a facility, select the equipment that uses the most energy, and identify ways to increase efficiency.
Roadmap for efficient parallelization of breast anatomy simulation
NASA Astrophysics Data System (ADS)
Chui, Joseph H.; Pokrajac, David D.; Maidment, Andrew D. A.; Bakic, Predrag R.
2012-03-01
A roadmap has been proposed to optimize the simulation of breast anatomy by parallel implementation, in order to reduce the time needed to generate software breast phantoms. The rapid generation of high resolution phantoms is needed to support virtual clinical trials of breast imaging systems. We have recently developed an octree-based recursive partitioning algorithm for breast anatomy simulation. The algorithm has good asymptotic complexity; however, its current MATLAB implementation cannot provide optimal execution times. The proposed roadmap for efficient parallelization includes the following steps: (i) migrate the current code to a C/C++ platform and optimize it for single-threaded implementation; (ii) modify the code to allow for multi-threaded CPU implementation; (iii) identify and migrate the code to a platform designed for multithreaded GPU implementation. In this paper, we describe our results in optimizing the C/C++ code for single-threaded and multi-threaded CPU implementations. As the first step of the proposed roadmap we have identified a bottleneck component in the MATLAB implementation using MATLAB's profiling tool, and created a single threaded CPU implementation of the algorithm using C/C++'s overloaded operators and standard template library. The C/C++ implementation has been compared to the MATLAB version in terms of accuracy and simulation time. A 520-fold reduction of the execution time was observed in a test of phantoms with 50- 400 μm voxels. In addition, we have identified several places in the code which will be modified to allow for the next roadmap milestone of the multithreaded CPU implementation.
Efficient parallel implementation of active appearance model fitting algorithm on GPU.
Wang, Jinwei; Ma, Xirong; Zhu, Yuanping; Sun, Jizhou
2014-01-01
The active appearance model (AAM) is one of the most powerful model-based object detecting and tracking methods which has been widely used in various situations. However, the high-dimensional texture representation causes very time-consuming computations, which makes the AAM difficult to apply to real-time systems. The emergence of modern graphics processing units (GPUs) that feature a many-core, fine-grained parallel architecture provides new and promising solutions to overcome the computational challenge. In this paper, we propose an efficient parallel implementation of the AAM fitting algorithm on GPUs. Our design idea is fine grain parallelism in which we distribute the texture data of the AAM, in pixels, to thousands of parallel GPU threads for processing, which makes the algorithm fit better into the GPU architecture. We implement our algorithm using the compute unified device architecture (CUDA) on the Nvidia's GTX 650 GPU, which has the latest Kepler architecture. To compare the performance of our algorithm with different data sizes, we built sixteen face AAM models of different dimensional textures. The experiment results show that our parallel AAM fitting algorithm can achieve real-time performance for videos even on very high-dimensional textures. PMID:24723812
Efficient Parallel Implementation of Active Appearance Model Fitting Algorithm on GPU
Wang, Jinwei; Ma, Xirong; Zhu, Yuanping; Sun, Jizhou
2014-01-01
The active appearance model (AAM) is one of the most powerful model-based object detecting and tracking methods which has been widely used in various situations. However, the high-dimensional texture representation causes very time-consuming computations, which makes the AAM difficult to apply to real-time systems. The emergence of modern graphics processing units (GPUs) that feature a many-core, fine-grained parallel architecture provides new and promising solutions to overcome the computational challenge. In this paper, we propose an efficient parallel implementation of the AAM fitting algorithm on GPUs. Our design idea is fine grain parallelism in which we distribute the texture data of the AAM, in pixels, to thousands of parallel GPU threads for processing, which makes the algorithm fit better into the GPU architecture. We implement our algorithm using the compute unified device architecture (CUDA) on the Nvidia's GTX 650 GPU, which has the latest Kepler architecture. To compare the performance of our algorithm with different data sizes, we built sixteen face AAM models of different dimensional textures. The experiment results show that our parallel AAM fitting algorithm can achieve real-time performance for videos even on very high-dimensional textures. PMID:24723812
Parallel Processing of Large Scale Microphone Arrays for Sound Capture
NASA Astrophysics Data System (ADS)
Jan, Ea-Ee.
1995-01-01
Performance of microphone sound pick up is degraded by deleterious properties of the acoustic environment, such as multipath distortion (reverberation) and ambient noise. The degradation becomes more prominent in a teleconferencing environment in which the microphone is positioned far away from the speaker. Besides, the ideal teleconference should feel as easy and natural as face-to-face communication with another person. This suggests hands-free sound capture with no tether or encumbrance by hand-held or body-worn sound equipment. Microphone arrays for this application represent an appropriate approach. This research develops new microphone array and signal processing techniques for high quality hands-free sound capture in noisy, reverberant enclosures. The new techniques combine matched-filtering of individual sensors and parallel processing to provide acute spatial volume selectivity which is capable of mitigating the deleterious effects of noise interference and multipath distortion. The new method outperforms traditional delay-and-sum beamformers which provide only directional spatial selectivity. The research additionally explores truncated matched-filtering and random distribution of transducers to reduce complexity and improve sound capture quality. All designs are first established by computer simulation of array performance in reverberant enclosures. The simulation is achieved by a room model which can efficiently calculate the acoustic multipath in a rectangular enclosure up to a prescribed order of images. It also calculates the incident angle of the arriving signal. Experimental arrays were constructed and their performance was measured in real rooms. Real room data were collected in a hard-walled laboratory and a controllable variable acoustics enclosure of similar size, approximately 6 x 6 x 3 m. An extensive speech database was also collected in these two enclosures for future research on microphone arrays. The simulation results are shown to be
Applying Parallel Processing Techniques to Tether Dynamics Simulation
NASA Technical Reports Server (NTRS)
Wells, B. Earl
1996-01-01
The focus of this research has been to determine the effectiveness of applying parallel processing techniques to a sizable real-world problem, the simulation of the dynamics associated with a tether which connects two objects in low earth orbit, and to explore the degree to which the parallelization process can be automated through the creation of new software tools. The goal has been to utilize this specific application problem as a base to develop more generally applicable techniques.
Parallel astronomical data processing with Python: Recipes for multicore machines
NASA Astrophysics Data System (ADS)
Singh, Navtej; Browne, Lisa-Marie; Butler, Ray
2013-08-01
High performance computing has been used in various fields of astrophysical research. But most of it is implemented on massively parallel systems (supercomputers) or graphical processing unit clusters. With the advent of multicore processors in the last decade, many serial software codes have been re-implemented in parallel mode to utilize the full potential of these processors. In this paper, we propose parallel processing recipes for multicore machines for astronomical data processing. The target audience is astronomers who use Python as their preferred scripting language and who may be using PyRAF/IRAF for data processing. Three problems of varied complexity were benchmarked on three different types of multicore processors to demonstrate the benefits, in terms of execution time, of parallelizing data processing tasks. The native multiprocessing module available in Python makes it a relatively trivial task to implement the parallel code. We have also compared the three multiprocessing approaches-Pool/Map, Process/Queue and Parallel Python. Our test codes are freely available and can be downloaded from our website.
Parallel Signal Processing and System Simulation using aCe
NASA Technical Reports Server (NTRS)
Dorband, John E.; Aburdene, Maurice F.
2003-01-01
Recently, networked and cluster computation have become very popular for both signal processing and system simulation. A new language is ideally suited for parallel signal processing applications and system simulation since it allows the programmer to explicitly express the computations that can be performed concurrently. In addition, the new C based parallel language (ace C) for architecture-adaptive programming allows programmers to implement algorithms and system simulation applications on parallel architectures by providing them with the assurance that future parallel architectures will be able to run their applications with a minimum of modification. In this paper, we will focus on some fundamental features of ace C and present a signal processing application (FFT).
Parallel Processing of Distributed Video Coding to Reduce Decoding Time
NASA Astrophysics Data System (ADS)
Tonomura, Yoshihide; Nakachi, Takayuki; Fujii, Tatsuya; Kiya, Hitoshi
This paper proposes a parallelized DVC framework that treats each bitplane independently to reduce the decoding time. Unfortunately, simple parallelization generates inaccurate bit probabilities because additional side information is not available for the decoding of subsequent bitplanes, which degrades encoding efficiency. Our solution is an effective estimation method that can calculate the bit probability as accurately as possible by index assignment without recourse to side information. Moreover, we improve the coding performance of Rate-Adaptive LDPC (RA-LDPC), which is used in the parallelized DVC framework. This proposal selects a fitting sparse matrix for each bitplane according to the syndrome rate estimation results at the encoder side. Simulations show that our parallelization method reduces the decoding time by up to 35[%] and achieves a bit rate reduction of about 10[%].
Digital signal processor and programming system for parallel signal processing
Van den Bout, D.E.
1987-01-01
This thesis describes an integrated assault upon the problem of designing high-throughput, low-cost digital signal-processing systems. The dual prongs of this assault consist of: (1) the design of a digital signal processor (DSP) which efficiently executes signal-processing algorithms in either a uniprocessor or multiprocessor configuration, (2) the PaLS programming system which accepts an arbitrary algorithm, partitions it across a group of DSPs, synthesizes an optimal communication link topology for the DSPs, and schedules the partitioned algorithm upon the DSPs. The results of applying a new quasi-dynamic analysis technique to a set of high-level signal-processing algorithms were used to determine the uniprocessor features of the DSP design. For multiprocessing applications, the DSP contains an interprocessor communications port (IPC) which supports simple, flexible, dataflow communications while allowing the total communication bandwidth to be incrementally allocated to achieve the best link utilization. The net result is a DSP with a simple architecture that is easy to program for both uniprocessor and multi-processor modes of operation. The PaLS programming system simplifies the task of parallelizing an algorithm for execution upon a multiprocessor built with the DSP.
High efficiency solar cell processing
NASA Technical Reports Server (NTRS)
Ho, F.; Iles, P. A.
1985-01-01
At the time of writing, cells made by several groups are approaching 19% efficiency. General aspects of the processing required for such cells are discussed. Most processing used for high efficiency cells is derived from space-cell or concentrator cell technology, and recent advances have been obtained from improved techniques rather than from better understanding of the limiting mechanisms. Theory and modeling are fairly well developed, and adequate to guide further asymptotic increases in performance of near conventional cells. There are several competitive cell designs with promise of higher performance ( 20%) but for these designs further improvements are required. The available cell processing technology to fabricate high efficiency cells is examined.
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.
Hardware Efficient and High-Performance Networks for Parallel Computers.
NASA Astrophysics Data System (ADS)
Chien, Minze Vincent
High performance interconnection networks are the key to high utilization and throughput in large-scale parallel processing systems. Since many interconnection problems in parallel processing such as concentration, permutation and broadcast problems can be cast as sorting problems, this dissertation considers the problem of sorting on a new model, called an adaptive sorting network. It presents four adaptive binary sorters the first two of which are ordinary combinational circuits while the last two exploit time-multiplexing and pipelining techniques. These sorter constructions demonstrate that any sequence of n bits can be sorted in O(log^2n) bit-level delay, using O(n) constant fanin gates. This improves the cost complexity of Batcher's binary sorters by a factor of O(log^2n) while matching their sorting time. It is further shown that any sequence of n numbers can be sorted on the same model in O(log^2n) comparator-level delay using O(nlog nloglog n) comparators. The adaptive binary sorter constructions lead to new O(n) bit-level cost concentrators and superconcentrators with O(log^2n) bit-level delay. Their employment in recently constructed permutation and generalized connectors lead to permutation and generalized connection networks with O(nlog n) bit-level cost and O(log^3n) bit-level delay. These results provide the least bit-level cost for such networks with competitive delays. Finally, the dissertation considers a key issue in the implementation of interconnection networks, namely, the pin constraint. Current VLSI technologies can house a large number of switches in a single chip, but the mere fact that one chip cannot have too many pins precludes the possibility of implementing a large connection network on a single chip. The dissertation presents techniques for partitioning connection networks into identical modules of switches in such a way that each module is contained in a single chip with an arbitrarily specified number of pins, and that the cost of
Efficient graph algorithms for sequential and parallel computers. Doctoral thesis
Goldberg, A.V.
1987-02-01
This thesis studies graph algorithms, both in sequential and parallel contexts. In the outline of the thesis, algorithm complexities are stated in terms of the the number of vertices n, the number of edges m, the largest absolute value of capacities U, and the largest absolute value of costs C. Chapter 1 introduces a new approach to the maximum flow problem that leads to better algorithms for the problem. Chapter 2 is devoted to the minimum cost flow problem, which is a generalization of the maximum flow problem. Chapter 3 addresses implementation of parallel algorithms through a case study of an implementation of a parallel maximum flow algorithm. Parallel prefix operations play an important role in the implementation. Present experimental results achieved by the implementation are presented. Present parallel symmetry-breaking techniques are the main topic of Chapter 4.
Parallel ALLSPD-3D: Speeding Up Combustor Analysis Via Parallel Processing
NASA Technical Reports Server (NTRS)
Fricker, David M.
1997-01-01
The ALLSPD-3D Computational Fluid Dynamics code for reacting flow simulation was run on a set of benchmark test cases to determine its parallel efficiency. These test cases included non-reacting and reacting flow simulations with varying numbers of processors. Also, the tests explored the effects of scaling the simulation with the number of processors in addition to distributing a constant size problem over an increasing number of processors. The test cases were run on a cluster of IBM RS/6000 Model 590 workstations with ethernet and ATM networking plus a shared memory SGI Power Challenge L workstation. The results indicate that the network capabilities significantly influence the parallel efficiency, i.e., a shared memory machine is fastest and ATM networking provides acceptable performance. The limitations of ethernet greatly hamper the rapid calculation of flows using ALLSPD-3D.
Parallel algorithms for high-speed SAR processing
NASA Astrophysics Data System (ADS)
Mallorqui, Jordi J.; Bara, Marc; Broquetas, Antoni; Wis, Mariano; Martinez, Antonio; Nogueira, Leonardo; Moreno, Victoriano
1998-11-01
The mass production of SAR products and its usage on monitoring emergency situations (oil spill detection, floods, etc.) requires high-speed SAR processors. Two different parallel strategies for near real time SAR processing based on a multiblock version of the Chirp Scaling Algorithm (CSA) have been studied. The first one is useful for small companies that would like to reduce computation times with no extra investment. It uses a cluster of heterogeneous UNIX workstations as a parallel computer. The second one is oriented to institutions, which have to process large amounts of data in short times and can afford the cost of large parallel computers. The parallel programming has reduced in both cases the computational times when compared with the sequential versions.
Study of image processing system based on parallel structure of multiple DSPs
NASA Astrophysics Data System (ADS)
Song, Jianxun; Wu, Qin-zhang
2008-03-01
A novel parallel image processing architecture using multiple DSPs which can satisfy real-time image processing demands is proposed, The architecture is structured with high performance DSP interconnected by FPGA. Within FPGA the interconnection network by IRAM and the specific data communication protocol are implemented. The system inherits merits from the tightly coupled parallel system and the loosely coupled parallel system. The system architecture is reconfigurable and scalable. The performances measured in this platform show the high data transfer rate, and it can satisfy parallel real-time image processing demands of the complex task, large computation and high-speed data transfer. From the designed parallel hardware we analyze the benchmarks including acceleration ratio, parallel efficiency, selection of processing units, interconnection network etc. Finally some suggestions are given to further improve the system performance. The real-time image processing system based on parallel structure of multiple DSPs is easy to be implemented. Because the system structure is reconfigurable and scalable, it is easy to change the number of DSP and change the DSP into other series. So it has a bright future for the application of real-time image processing system.
Watermarking scheme for large images using parallel processing
NASA Astrophysics Data System (ADS)
Debes, Eric; Dardier, Genevieve; Ebrahimi, Touradj; Herrigel, Alexander
2001-08-01
Large and high-resolution images usually have a high commercial value. Thus they are very good candidates for watermarking. If many images have to be signed in a Client-Server setup, memory and computational requirements could become unrealistic for current and near future solutions. In this paper, we propose to tile the image into sub-images. The watermarking scheme is then applied to each sub-image in the embedding and retrieval process. Thanks to this solution, the first possible optimization consists in creating different threads to read and write the image tile by tile. The time spent in input/output operations, which can be a bottleneck for large images, is reduced. In addition to this optimization, we show that the memory consumption of the application is also highly reduced for large images. Finally, the application can be multithreaded so that different tiles can be watermarked in parallel. Therefore the scheme can take advantage of the processing power of the different processors available in current servers. We show that the correct tile size and the right amount of threads have to be created to efficiently distribute the workload. Eventually, security, robustness and invisibility issues are addressed considering the signal redundancy.
Parallel processing implementation for the coupled transport of photons and electrons using OpenMP
NASA Astrophysics Data System (ADS)
Doerner, Edgardo
2016-05-01
In this work the use of OpenMP to implement the parallel processing of the Monte Carlo (MC) simulation of the coupled transport for photons and electrons is presented. This implementation was carried out using a modified EGSnrc platform which enables the use of the Microsoft Visual Studio 2013 (VS2013) environment, together with the developing tools available in the Intel Parallel Studio XE 2015 (XE2015). The performance study of this new implementation was carried out in a desktop PC with a multi-core CPU, taking as a reference the performance of the original platform. The results were satisfactory, both in terms of scalability as parallelization efficiency.
FPGA-Based Filterbank Implementation for Parallel Digital Signal Processing
NASA Technical Reports Server (NTRS)
Berner, Stephan; DeLeon, Phillip
1999-01-01
One approach to parallel digital signal processing decomposes a high bandwidth signal into multiple lower bandwidth (rate) signals by an analysis bank. After processing, the subband signals are recombined into a fullband output signal by a synthesis bank. This paper describes an implementation of the analysis and synthesis banks using (Field Programmable Gate Arrays) FPGAs.
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.
Automatic Mapping Of Large Signal Processing Systems To A Parallel Machine
NASA Astrophysics Data System (ADS)
Printz, Harry; Kung, H. T.; Mummert, Todd; Scherer, Paul M.
1989-12-01
Since the spring of 1988, Carnegie Mellon University and the Naval Air Development Center have been working together to implement several large signal processing systems on the Warp parallel computer. In the course of this work, we have developed a prototype of a software tool that can automatically and efficiently map signal processing systems to distributed-memory parallel machines, such as Warp. We have used this tool to produce Warp implementations of small test systems. The automatically generated programs compare favorably with hand-crafted code. We believe this tool will be a significant aid in the creation of high speed signal processing systems. We assume that signal processing systems have the following characteristics: •They can be described by directed graphs of computational tasks; these graphs may contain thousands of task vertices. • Some tasks can be parallelized in a systolic or data-partitioned manner, while others cannot be parallelized at all. • The side effects of each task, if any, are limited to changes in local variables. • Each task has a data-independent execution time bound, which may be expressed as a function of the way it is parallelized, and the number of processors it is mapped to. In this paper we describe techniques to automatically map such systems to Warp-like parallel machines. We identify and address key issues in gracefully combining different parallel programming styles, in allocating processor, memory and communication bandwidth, and in generating and scheduling efficient parallel code. When iWarp, the VLSI version of the Warp machine, becomes available in 1990, we will extend this tool to generate efficient code for very large applications, which may require as many as 3000 iWarp processors, with an aggregate peak performance of 60 gigaflops.
Mapping Pixel Windows To Vectors For Parallel Processing
NASA Technical Reports Server (NTRS)
Duong, Tuan A.
1996-01-01
Mapping performed by matrices of transistor switches. Arrays of transistor switches devised for use in forming simultaneous connections from square subarray (window) of n x n pixels within electronic imaging device containing np x np array of pixels to linear array of n(sup2) input terminals of electronic neural network or other parallel-processing circuit. Method helps to realize potential for rapidity in parallel processing for such applications as enhancement of images and recognition of patterns. In providing simultaneous connections, overcomes timing bottleneck or older multiplexing, serial-switching, and sample-and-hold methods.
Parallel evolution of image processing tools for multispectral imagery
NASA Astrophysics Data System (ADS)
Harvey, Neal R.; Brumby, Steven P.; Perkins, Simon J.; Porter, Reid B.; Theiler, James P.; Young, Aaron C.; Szymanski, John J.; Bloch, Jeffrey J.
2000-11-01
We describe the implementation and performance of a parallel, hybrid evolutionary-algorithm-based system, which optimizes image processing tools for feature-finding tasks in multi-spectral imagery (MSI) data sets. Our system uses an integrated spatio-spectral approach and is capable of combining suitably-registered data from different sensors. We investigate the speed-up obtained by parallelization of the evolutionary process via multiple processors (a workstation cluster) and develop a model for prediction of run-times for different numbers of processors. We demonstrate our system on Landsat Thematic Mapper MSI , covering the recent Cerro Grande fire at Los Alamos, NM, USA.
On Efficient Parallel Implementation of Moving Body Overset Grid Methods
NASA Technical Reports Server (NTRS)
Wissink, Andrew M.; Meakin, Robert L.; Warmbrodt, William (Technical Monitor)
1997-01-01
An investigation into the parallel performance of moving-body overset grid methods will be presented. Parallel versions of the OVERFLOW flow solver, DCF3D domain connectivity software, and SIXDO six-degree-of-freedom routine are coupled with an automatic load balance routine and tested for 3D Navier-Stokes calculations on the IBM SP2. The primary source of parallel inefficiency in moving and problems are the domain connectivity costs with DCF 3D. Although this algorithm constitutes a relatively low fraction of the total solution cost (e.g. 10-20%) in calculations on serial machines, the consequently cause a significant degradation in the overall parallel performance. The paper will highlight some approaches for improving the scalability of DCF3D. The paper will present results of a proposed new load balancing scheme that seeks more equal distribution of the inter-grid boundary points in order to more evenly load balance the donor search costs associated with DCF3D. Some preliminary results will also be given from a new solution-adaption algorithm coupled with OVERFLOW which incorporates overset cartesian grids with various levels of refinement. The measured parallel performance from a descending delta-wing configuration and a generic store-separation from a wing/pylon case will be presented.
Active Storage Processing in a Parallel File System
Felix, Evan J.; Fox, Kevin M.; Regimbal, Kevin M.; Nieplocha, Jarek
2006-01-01
By creating a processing system within a parallel file system one can harness the power of unused processing power on servers that have very fast access to the disks they are serving. By inserting a module the Lustre file system the Active Storage Concept is able to perform processing with the file system architecture. Results of using this technology are presented as the results of the Supercomputing StorCloud Challenge Application are reviewed.
FORTRAN M. FORTRAN Extensions for Modular Parallel Processing
Foster, Ian; Olson, Robert; Tuecke, Steven
1993-08-01
FORTRAN M is a small set of extensions to FORTRAN that supports a modular approach to the construction of sequential and parallel programs. FORTRAN M programs use channels to plug together processes which may be written in FORTRAN M or FORTRAN 77. Processes communicate by sending and receiving messages on channels. Channels and processes can be created dynamically, but programs remain deterministic unless specialized nondeterministic constructs are used.
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.
A single user efficiency measure for evaluation of parallel or pipeline computer architectures
NASA Technical Reports Server (NTRS)
Jones, W. P.
1978-01-01
A precise statement of the relationship between sequential computation at one rate, parallel or pipeline computation at a much higher rate, the data movement rate between levels of memory, the fraction of inherently sequential operations or data that must be processed sequentially, the fraction of data to be moved that cannot be overlapped with computation, and the relative computational complexity of the algorithms for the two processes, scalar and vector, was developed. The relationship should be applied to the multirate processes that obtain in the employment of various new or proposed computer architectures for computational aerodynamics. The relationship, an efficiency measure that the single user of the computer system perceives, argues strongly in favor of separating scalar and vector processes, sometimes referred to as loosely coupled processes, to achieve optimum use of hardware.
Parallel processing of atmospheric chemistry calculations: Preliminary considerations
Elliott, S.; Jones, P.
1995-01-01
Global climate calculations are already saturating the class modern vector supercomputers with only a few central processing units. Increased resolution and inclusion of routines to deal with biogeochemical portions of the terrestrial climate system will soon demand massively parallel approaches. The atmospheric photochemistry ensemble is intimately linked to climate through the trace greenhouse gases ozone and methane and modules for representing it are being attached to global three dimensional transport and GCM frameworks. Atmospheric kinetics involve dozens of highly interactive tracers and so will accentuate the need for parallel processing of earth system simulations. In the present text we lay some of the groundwork for addition of atmospheric kinetics packages to GCM and global scale atmospheric models on multiply parallel computers. The discussion is tailored for consumption by the photochemical modelling community. After a review of numerical atmospheric chemistry methods, we examine how kinetics can be implemented on a parallel computer. We concentrate especially on data layout and flexibility and how these can be implemented in various programming models. We conclude that chemistry can be implemented rather easily within existing frameworks of several parallel atmospheric models. However, memory limitations may preclude high resolution studies of global chemistry.
Partitioning Rectangular and Structurally Nonsymmetric Sparse Matrices for Parallel Processing
B. Hendrickson; T.G. Kolda
1998-09-01
A common operation in scientific computing is the multiplication of a sparse, rectangular or structurally nonsymmetric matrix and a vector. In many applications the matrix- transpose-vector product is also required. This paper addresses the efficient parallelization of these operations. We show that the problem can be expressed in terms of partitioning bipartite graphs. We then introduce several algorithms for this partitioning problem and compare their performance on a set of test matrices.
Efficient Parallel Learning of Hidden Markov Chain Models on SMPs
NASA Astrophysics Data System (ADS)
Li, Lei; Fu, Bin; Faloutsos, Christos
Quad-core cpus have been a common desktop configuration for today's office. The increasing number of processors on a single chip opens new opportunity for parallel computing. Our goal is to make use of the multi-core as well as multi-processor architectures to speed up large-scale data mining algorithms. In this paper, we present a general parallel learning framework, Cut-And-Stitch, for training hidden Markov chain models. Particularly, we propose two model-specific variants, CAS-LDS for learning linear dynamical systems (LDS) and CAS-HMM for learning hidden Markov models (HMM). Our main contribution is a novel method to handle the data dependencies due to the chain structure of hidden variables, so as to parallelize the EM-based parameter learning algorithm. We implement CAS-LDS and CAS-HMM using OpenMP on two supercomputers and a quad-core commercial desktop. The experimental results show that parallel algorithms using Cut-And-Stitch achieve comparable accuracy and almost linear speedups over the traditional serial version.
Using Motivational Interviewing Techniques to Address Parallel Process in Supervision
ERIC Educational Resources Information Center
Giordano, Amanda; Clarke, Philip; Borders, L. DiAnne
2013-01-01
Supervision offers a distinct opportunity to experience the interconnection of counselor-client and counselor-supervisor interactions. One product of this network of interactions is parallel process, a phenomenon by which counselors unconsciously identify with their clients and subsequently present to their supervisors in a similar fashion…
The Extended Parallel Process Model: Illuminating the Gaps in Research
ERIC Educational Resources Information Center
Popova, Lucy
2012-01-01
This article examines constructs, propositions, and assumptions of the extended parallel process model (EPPM). Review of the EPPM literature reveals that its theoretical concepts are thoroughly developed, but the theory lacks consistency in operational definitions of some of its constructs. Out of the 12 propositions of the EPPM, a few have not…
Rapid Parallel Semantic Processing of Numbers without Awareness
ERIC Educational Resources Information Center
Van Opstal, Filip; de Lange, Floris P.; Dehaene, Stanislas
2011-01-01
In this study, we investigate whether multiple digits can be processed at a semantic level without awareness, either serially or in parallel. In two experiments, we presented participants with two successive sets of four simultaneous Arabic digits. The first set was masked and served as a subliminal prime for the second, visible target set.…
Parallel Processing of Objects in a Naming Task
ERIC Educational Resources Information Center
Meyer, Antje S.; Ouellet, Marc; Hacker, Christine
2008-01-01
The authors investigated whether speakers who named several objects processed them sequentially or in parallel. Speakers named object triplets, arranged in a triangle, in the order left, right, and bottom object. The left object was easy or difficult to identify and name. During the saccade from the left to the right object, the right object shown…
Postscript: Parallel Distributed Processing in Localist Models without Thresholds
ERIC Educational Resources Information Center
Plaut, David C.; McClelland, James L.
2010-01-01
The current authors reply to a response by Bowers on a comment by the current authors on the original article. Bowers (2010) mischaracterizes the goals of parallel distributed processing (PDP research)--explaining performance on cognitive tasks is the primary motivation. More important, his claim that localist models, such as the interactive…
Parallel Processing Method for Airborne Laser Scanning Data Using a PC Cluster and a Virtual Grid.
Han, Soo Hee; Heo, Joon; Sohn, Hong Gyoo; Yu, Kiyun
2009-01-01
In this study, a parallel processing method using a PC cluster and a virtual grid is proposed for the fast processing of enormous amounts of airborne laser scanning (ALS) data. The method creates a raster digital surface model (DSM) by interpolating point data with inverse distance weighting (IDW), and produces a digital terrain model (DTM) by local minimum filtering of the DSM. To make a consistent comparison of performance between sequential and parallel processing approaches, the means of dealing with boundary data and of selecting interpolation centers were controlled for each processing node in parallel approach. To test the speedup, efficiency and linearity of the proposed algorithm, actual ALS data up to 134 million points were processed with a PC cluster consisting of one master node and eight slave nodes. The results showed that parallel processing provides better performance when the computational overhead, the number of processors, and the data size become large. It was verified that the proposed algorithm is a linear time operation and that the products obtained by parallel processing are identical to those produced by sequential processing. PMID:22574032
DNA encoding for an efficient 'Omics processing.
Murovec, Bostjan; Tiedje, James M; Stres, Blaz
2010-11-01
The exponential growth of available DNA sequences and the increased interoperability of biological information is triggering intergovernmental efforts aimed at increasing the access, dissemination, and analysis of sequence data. Achieving the efficient storage and processing of DNA material is an important goal that parallels well with the foreseen coding standardization on the horizon. This paper proposes novel coding approaches, for both the dissemination and processing of sequences, where the speed of the DNA processing is shown to be boosted by exploring more than the normally utilized eight bits for encoding a single nucleotide. Further gains are achieved by encoding the nucleotides together with their trailing alignment information as a single 64-bit data structure. The paper also proposes a slight modification to the established FASTA scheme in order to improve on its representation of alignment information. The significance of the propositions is confirmed by the encouraging results from empirical tests. PMID:20444519
Idaho Chemical Processing Plant Process Efficiency improvements
Griebenow, B.
1996-03-01
In response to decreasing funding levels available to support activities at the Idaho Chemical Processing Plant (ICPP) and a desire to be cost competitive, the Department of Energy Idaho Operations Office (DOE-ID) and Lockheed Idaho Technologies Company have increased their emphasis on cost-saving measures. The ICPP Effectiveness Improvement Initiative involves many activities to improve cost effectiveness and competitiveness. This report documents the methodology and results of one of those cost cutting measures, the Process Efficiency Improvement Activity. The Process Efficiency Improvement Activity performed a systematic review of major work processes at the ICPP to increase productivity and to identify nonvalue-added requirements. A two-phase approach was selected for the activity to allow for near-term implementation of relatively easy process modifications in the first phase while obtaining long-term continuous improvement in the second phase and beyond. Phase I of the initiative included a concentrated review of processes that had a high potential for cost savings with the intent of realizing savings in Fiscal Year 1996 (FY-96.) Phase II consists of implementing long-term strategies too complex for Phase I implementation and evaluation of processes not targeted for Phase I review. The Phase II effort is targeted for realizing cost savings in FY-97 and beyond.
ERIC Educational Resources Information Center
Miller, Jeff; Ulrich, Rolf; Rolke, Bettina
2009-01-01
Within the context of the psychological refractory period (PRP) paradigm, we developed a general theoretical framework for deciding when it is more efficient to process two tasks in serial and when it is more efficient to process them in parallel. This analysis suggests that a serial mode is more efficient than a parallel mode under a wide variety…
The remote sensing image segmentation mean shift algorithm parallel processing based on MapReduce
NASA Astrophysics Data System (ADS)
Chen, Xi; Zhou, Liqing
2015-12-01
With the development of satellite remote sensing technology and the remote sensing image data, traditional remote sensing image segmentation technology cannot meet the massive remote sensing image processing and storage requirements. This article put cloud computing and parallel computing technology in remote sensing image segmentation process, and build a cheap and efficient computer cluster system that uses parallel processing to achieve MeanShift algorithm of remote sensing image segmentation based on the MapReduce model, not only to ensure the quality of remote sensing image segmentation, improved split speed, and better meet the real-time requirements. The remote sensing image segmentation MeanShift algorithm parallel processing algorithm based on MapReduce shows certain significance and a realization of value.
Automating the parallel processing of fluid and structural dynamics calculations
NASA Technical Reports Server (NTRS)
Arpasi, Dale J.; Cole, Gary L.
1987-01-01
The NASA Lewis Research Center is actively involved in the development of expert system technology to assist users in applying parallel processing to computational fluid and structural dynamic analysis. The goal of this effort is to eliminate the necessity for the physical scientist to become a computer scientist in order to effectively use the computer as a research tool. Programming and operating software utilities have previously been developed to solve systems of ordinary nonlinear differential equations on parallel scalar processors. Current efforts are aimed at extending these capabilties to systems of partial differential equations, that describe the complex behavior of fluids and structures within aerospace propulsion systems. This paper presents some important considerations in the redesign, in particular, the need for algorithms and software utilities that can automatically identify data flow patterns in the application program and partition and allocate calculations to the parallel processors. A library-oriented multiprocessing concept for integrating the hardware and software functions is described.
Automating the parallel processing of fluid and structural dynamics calculations
NASA Technical Reports Server (NTRS)
Arpasi, Dale J.; Cole, Gary L.
1987-01-01
The NASA Lewis Research Center is actively involved in the development of expert system technology to assist users in applying parallel processing to computational fluid and structural dynamic analysis. The goal of this effort is to eliminate the necessity for the physical scientist to become a computer scientist in order to effectively use the computer as a research tool. Programming and operating software utilities have previously been developed to solve systems of ordinary nonlinear differential equations on parallel scalar processors. Current efforts are aimed at extending these capabilities to systems of partial differential equations, that describe the complex behavior of fluids and structures within aerospace propulsion systems. This paper presents some important considerations in the redesign, in particular, the need for algorithms and software utilities that can automatically identify data flow patterns in the application program and partition and allocate calculations to the parallel processors. A library-oriented multiprocessing concept for integrating the hardware and software functions is described.
NASA Astrophysics Data System (ADS)
Zhang, Shanghong; Yuan, Rui; Wu, Yu; Yi, Yujun
2016-01-01
The Open Accelerator (OpenACC) application programming interface is a relatively new parallel computing standard. In this paper, particle-based flow field simulations are examined as a case study of OpenACC parallel computation. The parallel conversion process of the OpenACC standard is explained, and further, the performance of the flow field parallel model is analysed using different directive configurations and grid schemes. With careful implementation and optimisation of the data transportation in the parallel algorithm, a speedup factor of 18.26× is possible. In contrast, a speedup factor of just 11.77× was achieved with the conventional Open Multi-Processing (OpenMP) parallel mode on a 20-kernel computer. These results demonstrate that optimised feature settings greatly influence the degree of speedup, and models involving larger numbers of calculations exhibit greater efficiency and higher speedup factors. In addition, the OpenACC parallel mode is found to have good portability, making it easy to implement parallel computation from the original serial model.
Parallel-Processing Software for Correlating Stereo Images
NASA Technical Reports Server (NTRS)
Klimeck, Gerhard; Deen, Robert; Mcauley, Michael; DeJong, Eric
2007-01-01
A computer program implements parallel- processing algorithms for cor relating images of terrain acquired by stereoscopic pairs of digital stereo cameras on an exploratory robotic vehicle (e.g., a Mars rove r). Such correlations are used to create three-dimensional computatio nal models of the terrain for navigation. In this program, the scene viewed by the cameras is segmented into subimages. Each subimage is assigned to one of a number of central processing units (CPUs) opera ting simultaneously.
Parallel Processing of Broad-Band PPM Signals
NASA Technical Reports Server (NTRS)
Gray, Andrew; Kang, Edward; Lay, Norman; Vilnrotter, Victor; Srinivasan, Meera; Lee, Clement
2010-01-01
A parallel-processing algorithm and a hardware architecture to implement the algorithm have been devised for timeslot synchronization in the reception of pulse-position-modulated (PPM) optical or radio signals. As in the cases of some prior algorithms and architectures for parallel, discrete-time, digital processing of signals other than PPM, an incoming broadband signal is divided into multiple parallel narrower-band signals by means of sub-sampling and filtering. The number of parallel streams is chosen so that the frequency content of the narrower-band signals is low enough to enable processing by relatively-low speed complementary metal oxide semiconductor (CMOS) electronic circuitry. The algorithm and architecture are intended to satisfy requirements for time-varying time-slot synchronization and post-detection filtering, with correction of timing errors independent of estimation of timing errors. They are also intended to afford flexibility for dynamic reconfiguration and upgrading. The architecture is implemented in a reconfigurable CMOS processor in the form of a field-programmable gate array. The algorithm and its hardware implementation incorporate three separate time-varying filter banks for three distinct functions: correction of sub-sample timing errors, post-detection filtering, and post-detection estimation of timing errors. The design of the filter bank for correction of timing errors, the method of estimating timing errors, and the design of a feedback-loop filter are governed by a host of parameters, the most critical one, with regard to processing very broadband signals with CMOS hardware, being the number of parallel streams (equivalently, the rate-reduction parameter).
Parallel processing and pipelining usher DSP model into the future
Kampen, T.V.; Anders, P.
1986-02-20
The course of digital signal processing is well plotted into the future. When standard microprocessors, constrained by their von Neumann architectures and weak arithmetic ability, proved inadequate for the task, the first specialized chips appeared. The devices were fortified with Harvard-like parallel architecture, multiplication-accumulation hardware, and instruction pipelines. In the next stage of their evolution, DSP chips will have to rely on faster IC technologies and even greater degrees of parallel operation. Two versions of such a DSP chip are planned, one with and one without data ROM and program memory, and the latter has been cast in silicon. The processor relies on high-speed CMOS technology and a parallel architecture to start an instruction every 125 ns. The chip has the processing power to handle many of the most sophisticated DSP algorithms needed in telecommunications, speech and image processing, and general industry applications. As a result, either version can replace multiple ICs in current designs, affording a single-chip solution that makes many applications practical for the first time. Moreover, its flexible I/O structure qualifies the chip for the multiple processor configurations that offer still more signal-processing power. Architecturally, twin 16-bit data buses, X and Y, connect five functional sections within the chip, all working in parallel. The sections include a 16-bit multiplier and 40-bit accumulator, an ALU teamed with a multiport register file, and combined data memory and address computation logic. Rounding out the chip's functional foundation are a versatile program control section and 16-bit serial and parallel I/O circuits.
Efficient separations & processing crosscutting program
1996-08-01
The Efficient Separations and Processing Crosscutting Program (ESP) was created in 1991 to identify, develop, and perfect chemical and physical separations technologies and chemical processes which treat wastes and address environmental problems throughout the DOE complex. The ESP funds several multiyear tasks that address high-priority waste remediation problems involving high-level, low-level, transuranic, hazardous, and mixed (radioactive and hazardous) wastes. The ESP supports applied research and development (R & D) leading to the demonstration or use of these separations technologies by other organizations within the Department of Energy (DOE), Office of Environmental Management.
Airbreathing Propulsion System Analysis Using Multithreaded Parallel Processing
NASA Technical Reports Server (NTRS)
Schunk, Richard Gregory; Chung, T. J.; Rodriguez, Pete (Technical Monitor)
2000-01-01
In this paper, parallel processing is used to analyze the mixing, and combustion behavior of hypersonic flow. Preliminary work for a sonic transverse hydrogen jet injected from a slot into a Mach 4 airstream in a two-dimensional duct combustor has been completed [Moon and Chung, 1996]. Our aim is to extend this work to three-dimensional domain using multithreaded domain decomposition parallel processing based on the flowfield-dependent variation theory. Numerical simulations of chemically reacting flows are difficult because of the strong interactions between the turbulent hydrodynamic and chemical processes. The algorithm must provide an accurate representation of the flowfield, since unphysical flowfield calculations will lead to the faulty loss or creation of species mass fraction, or even premature ignition, which in turn alters the flowfield information. Another difficulty arises from the disparity in time scales between the flowfield and chemical reactions, which may require the use of finite rate chemistry. The situations are more complex when there is a disparity in length scales involved in turbulence. In order to cope with these complicated physical phenomena, it is our plan to utilize the flowfield-dependent variation theory mentioned above, facilitated by large eddy simulation. Undoubtedly, the proposed computation requires the most sophisticated computational strategies. The multithreaded domain decomposition parallel processing will be necessary in order to reduce both computational time and storage. Without special treatments involved in computer engineering, our attempt to analyze the airbreathing combustion appears to be difficult, if not impossible.
Highly scalable parallel processing of extracellular recordings of Multielectrode Arrays.
Gehring, Tiago V; Vasilaki, Eleni; Giugliano, Michele
2015-01-01
Technological advances of Multielectrode Arrays (MEAs) used for multisite, parallel electrophysiological recordings, lead to an ever increasing amount of raw data being generated. Arrays with hundreds up to a few thousands of electrodes are slowly seeing widespread use and the expectation is that more sophisticated arrays will become available in the near future. In order to process the large data volumes resulting from MEA recordings there is a pressing need for new software tools able to process many data channels in parallel. Here we present a new tool for processing MEA data recordings that makes use of new programming paradigms and recent technology developments to unleash the power of modern highly parallel hardware, such as multi-core CPUs with vector instruction sets or GPGPUs. Our tool builds on and complements existing MEA data analysis packages. It shows high scalability and can be used to speed up some performance critical pre-processing steps such as data filtering and spike detection, helping to make the analysis of larger data sets tractable. PMID:26737215
A dataflow analysis tool for parallel processing of algorithms
NASA Technical Reports Server (NTRS)
Jones, Robert L., III
1993-01-01
A graph-theoretic design process and software tool is presented for selecting a multiprocessing scheduling solution for a class of computational problems. The problems of interest are those that can be described using a dataflow graph and are intended to be executed repetitively on a set of identical parallel processors. Typical applications include signal processing and control law problems. Graph analysis techniques are introduced and shown to effectively determine performance bounds, scheduling constraints, and resource requirements. The software tool is shown to facilitate the application of the design process to a given problem.
Digital intermediate frequency QAM modulator using parallel processing
Pao, Hsueh-Yuan; Tran, Binh-Nien
2008-05-27
The digital Intermediate Frequency (IF) modulator applies to various modulation types and offers a simple and low cost method to implement a high-speed digital IF modulator using field programmable gate arrays (FPGAs). The architecture eliminates multipliers and sequential processing by storing the pre-computed modulated cosine and sine carriers in ROM look-up-tables (LUTs). The high-speed input data stream is parallel processed using the corresponding LUTs, which reduces the main processing speed, allowing the use of low cost FPGAs.
NASA Astrophysics Data System (ADS)
Cortés, Guillermo; García, Luz; Álvarez, Isaac; Benítez, Carmen; de la Torre, Ángel; Ibáñez, Jesús
2014-02-01
Automatic recognition of volcano-seismic events is becoming one of the most demanded features in the early warning area at continuous monitoring facilities. While human-driven cataloguing is time-consuming and often an unreliable task, an appropriate machine framework allows expert technicians to focus only on result analysis and decision-making. This work presents an alternative to serial architectures used in classic recognition systems introducing a parallel implementation of the whole process: configuration, feature extraction, feature selection and classification stages are independently carried out for each type of events in order to exploit the intrinsic properties of each signal class. The system uses Gaussian Mixture Models (GMMs) to classify the database recorded at Deception Volcano Island (Antarctica) obtaining a baseline recognition rate of 84% with a cepstral-based waveform parameterization in the serial architecture. The parallel approach increases the results to close to 92% using mixture-based parameterization vectors or up to 91% when the vector size is reduced by 19% via the Discriminative Feature Selection (DFS) algorithm. Besides the result improvement, the parallel architecture represents a major step in terms of flexibility and reliability thanks to the class-focused analysis, providing an efficient tool for monitoring observatories which require real-time solutions.
Applications of massively parallel computers in telemetry processing
NASA Technical Reports Server (NTRS)
El-Ghazawi, Tarek A.; Pritchard, Jim; Knoble, Gordon
1994-01-01
Telemetry processing refers to the reconstruction of full resolution raw instrumentation data with artifacts, of space and ground recording and transmission, removed. Being the first processing phase of satellite data, this process is also referred to as level-zero processing. This study is aimed at investigating the use of massively parallel computing technology in providing level-zero processing to spaceflights that adhere to the recommendations of the Consultative Committee on Space Data Systems (CCSDS). The workload characteristics, of level-zero processing, are used to identify processing requirements in high-performance computing systems. An example of level-zero functions on a SIMD MPP, such as the MasPar, is discussed. The requirements in this paper are based in part on the Earth Observing System (EOS) Data and Operation System (EDOS).
Morphological evidence for parallel processing of information in rat macula
NASA Technical Reports Server (NTRS)
Ross, M. D.
1988-01-01
Study of montages, tracings and reconstructions prepared from a series of 570 consecutive ultrathin sections shows that rat maculas are morphologically organized for parallel processing of linear acceleratory information. Type II cells of one terminal field distribute information to neighboring terminals as well. The findings are examined in light of physiological data which indicate that macular receptor fields have a preferred directional vector, and are interpreted by analogy to a computer technology known as an information network.
Parallel Visualization Co-Processing of Overnight CFD Propulsion Applications
NASA Technical Reports Server (NTRS)
Edwards, David E.; Haimes, Robert
1999-01-01
An interactive visualization system pV3 is being developed for the investigation of advanced computational methodologies employing visualization and parallel processing for the extraction of information contained in large-scale transient engineering simulations. Visual techniques for extracting information from the data in terms of cutting planes, iso-surfaces, particle tracing and vector fields are included in this system. This paper discusses improvements to the pV3 system developed under NASA's Affordable High Performance Computing project.
Study of parallel efficiency in message passing environments
Hanebutte, U.R.; Tatsumi, Masahiro
1996-03-01
A benchmark test using the Message Passing Interface (MPI, an emerging standard for writing message passing programs) has been developed, to study parallel performance in message passing environments. The test is comprised of a computational task of independent calculations followed by a round-robin data communication step. Performance data as a function of computational granularity and message passing requirements are presented for the IBM SPx at Argonne National Laboratory and for a cluster of quasi-dedicated SUN SPARC Station 20`s. In the later portion of the paper a widely accepted communication cost model combined with Amdahl`s law is used to obtain performance predictions for uneven distributed computational work loads.
Efficient Identification of Assembly Neurons within Massively Parallel Spike Trains
Berger, Denise; Borgelt, Christian; Louis, Sebastien; Morrison, Abigail; Grün, Sonja
2010-01-01
The chance of detecting assembly activity is expected to increase if the spiking activities of large numbers of neurons are recorded simultaneously. Although such massively parallel recordings are now becoming available, methods able to analyze such data for spike correlation are still rare, as a combinatorial explosion often makes it infeasible to extend methods developed for smaller data sets. By evaluating pattern complexity distributions the existence of correlated groups can be detected, but their member neurons cannot be identified. In this contribution, we present approaches to actually identify the individual neurons involved in assemblies. Our results may complement other methods and also provide a way to reduce data sets to the “relevant” neurons, thus allowing us to carry out a refined analysis of the detailed correlation structure due to reduced computation time. PMID:19809521
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.
NASA Astrophysics Data System (ADS)
Bonnin, Patrick J.; Hoeltzener-Douarin, Brigitte; Aubin, N.; Cartier, S.; Porcher, Thierry; Fiorini, P.; Zavidovique, Bertrand
1993-10-01
A great number of parallel computer architectures have been proposed, whether they are SIMD machines (Single Instruction Multiple Data) with lots of quite simple processors, or MIMD machines (Multiple Instruction Multiple Data) containing few, but powerful processors. Each one claims to offer some kind of an optimality at the hardware level. But implementing parallel image processing algorithms to make them run in real time will remain a real challenge; it addresses rather the control of communication networks between processors (message passing, circuit switching..) or the computing model (e.g. data parallel model). In that respect, our goal here is to point out some algorithmic needs to distribute image processing operators. They will be translated first in terms of programming models, more general then image processing applications, and then as hardware properties of the processor network. In that way, we do not design yet another parallel machine dedicated to image processing, but a more general parallel architecture which one will be able to efficiently implement different kinds of programming models.
[Multi-DSP parallel processing technique of hyperspectral RX anomaly detection].
Guo, Wen-Ji; Zeng, Xiao-Ru; Zhao, Bao-Wei; Ming, Xing; Zhang, Gui-Feng; Lü, Qun-Bo
2014-05-01
To satisfy the requirement of high speed, real-time and mass data storage etc. for RX anomaly detection of hyperspectral image data, the present paper proposes a solution of multi-DSP parallel processing system for hyperspectral image based on CPCI Express standard bus architecture. Hardware topological architecture of the system combines the tight coupling of four DSPs sharing data bus and memory unit with the interconnection of Link ports. On this hardware platform, by assigning parallel processing task for each DSP in consideration of the spectrum RX anomaly detection algorithm and the feature of 3D data in the spectral image, a 4DSP parallel processing technique which computes and solves the mean matrix and covariance matrix of the whole image by spatially partitioning the image is proposed. The experiment result shows that, in the case of equivalent detective effect, it can reach the time efficiency 4 times higher than single DSP process with the 4-DSP parallel processing technique of RX anomaly detection algorithm proposed by this paper, which makes a breakthrough in the constraints to the huge data image processing of DSP's internal storage capacity, meanwhile well meeting the demands of the spectral data in real-time processing. PMID:25095443
Seny, Bruno Lambrechts, Jonathan; Toulorge, Thomas; Legat, Vincent; Remacle, Jean-François
2014-01-01
Although explicit time integration schemes require small computational efforts per time step, their efficiency is severely restricted by their stability limits. Indeed, the multi-scale nature of some physical processes combined with highly unstructured meshes can lead some elements to impose a severely small stable time step for a global problem. Multirate methods offer a way to increase the global efficiency by gathering grid cells in appropriate groups under local stability conditions. These methods are well suited to the discontinuous Galerkin framework. The parallelization of the multirate strategy is challenging because grid cells have different workloads. The computational cost is different for each sub-time step depending on the elements involved and a classical partitioning strategy is not adequate any more. In this paper, we propose a solution that makes use of multi-constraint mesh partitioning. It tends to minimize the inter-processor communications, while ensuring that the workload is almost equally shared by every computer core at every stage of the algorithm. Particular attention is given to the simplicity of the parallel multirate algorithm while minimizing computational and communication overheads. Our implementation makes use of the MeTiS library for mesh partitioning and the Message Passing Interface for inter-processor communication. Performance analyses for two and three-dimensional practical applications confirm that multirate methods preserve important computational advantages of explicit methods up to a significant number of processors.
Massively parallel spatial light modulation-based optical signal processing
NASA Astrophysics Data System (ADS)
Li, Yao
1993-03-01
A new optical parallel arithmetic processing scheme using a nonholographic optoelectronic content-addressable memory (CAM) was proposed. The design of a four-bit CAM-based optical carry look-ahead adder was studied. Compared with existing optoelectronic binary addition approaches, this nonholographic CAM Scheme offers a number of practical advantages, such as faster processing speed and ease of optical implementation and alignment. For an addition of numbers longer than four bits, by incorporating the previous stage's carry, a number of four-bit CLA's can be cascaded. Experimental results were also demonstrated. One paper to the Optics Letters was published.
Parallel-Processing Equalizers for Multi-Gbps Communications
NASA Technical Reports Server (NTRS)
Gray, Andrew; Ghuman, Parminder; Hoy, Scott; Satorius, Edgar H.
2004-01-01
Architectures have been proposed for the design of frequency-domain least-mean-square complex equalizers that would be integral parts of parallel- processing digital receivers of multi-gigahertz radio signals and other quadrature-phase-shift-keying (QPSK) or 16-quadrature-amplitude-modulation (16-QAM) of data signals at rates of multiple gigabits per second. Equalizers as used here denotes receiver subsystems that compensate for distortions in the phase and frequency responses of the broad-band radio-frequency channels typically used to convey such signals. The proposed architectures are suitable for realization in very-large-scale integrated (VLSI) circuitry and, in particular, complementary metal oxide semiconductor (CMOS) application- specific integrated circuits (ASICs) operating at frequencies lower than modulation symbol rates. A digital receiver of the type to which the proposed architecture applies (see Figure 1) would include an analog-to-digital converter (A/D) operating at a rate, fs, of 4 samples per symbol period. To obtain the high speed necessary for sampling, the A/D and a 1:16 demultiplexer immediately following it would be constructed as GaAs integrated circuits. The parallel-processing circuitry downstream of the demultiplexer, including a demodulator followed by an equalizer, would operate at a rate of only fs/16 (in other words, at 1/4 of the symbol rate). The output from the equalizer would be four parallel streams of in-phase (I) and quadrature (Q) samples.
Efficient solid state NMR powder simulations using SMP and MPP parallel computation.
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. PMID:12713968
Graphics Processing Unit Enhanced Parallel Document Flocking Clustering
Cui, Xiaohui; Potok, Thomas E; ST Charles, Jesse Lee
2010-01-01
Analyzing and clustering documents is a complex problem. One explored method of solving this problem borrows from nature, imitating the flocking behavior of birds. One limitation of this method of document clustering is its complexity O(n2). As the number of documents grows, it becomes increasingly difficult to generate results in a reasonable amount of time. In the last few years, the graphics processing unit (GPU) has received attention for its ability to solve highly-parallel and semi-parallel problems much faster than the traditional sequential processor. In this paper, we have conducted research to exploit this archi- tecture and apply its strengths to the flocking based document clustering problem. Using the CUDA platform from NVIDIA, we developed a doc- ument flocking implementation to be run on the NVIDIA GEFORCE GPU. Performance gains ranged from thirty-six to nearly sixty times improvement of the GPU over the CPU implementation.
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.
Reducing neural network training time with parallel processing
NASA Technical Reports Server (NTRS)
Rogers, James L., Jr.; Lamarsh, William J., II
1995-01-01
Obtaining optimal solutions for engineering design problems is often expensive because the process typically requires numerous iterations involving analysis and optimization programs. Previous research has shown that a near optimum solution can be obtained in less time by simulating a slow, expensive analysis with a fast, inexpensive neural network. A new approach has been developed to further reduce this time. This approach decomposes a large neural network into many smaller neural networks that can be trained in parallel. Guidelines are developed to avoid some of the pitfalls when training smaller neural networks in parallel. These guidelines allow the engineer: to determine the number of nodes on the hidden layer of the smaller neural networks; to choose the initial training weights; and to select a network configuration that will capture the interactions among the smaller neural networks. This paper presents results describing how these guidelines are developed.
Efficiency of cellular information processing
NASA Astrophysics Data System (ADS)
Barato, Andre C.; Hartich, David; Seifert, Udo
2014-10-01
We show that a rate of conditional Shannon entropy reduction, characterizing the learning of an internal process about an external process, is bounded by the thermodynamic entropy production. This approach allows for the definition of an informational efficiency that can be used to study cellular information processing. We analyze three models of increasing complexity inspired by the Escherichia coli sensory network, where the external process is an external ligand concentration jumping between two values. We start with a simple model for which ATP must be consumed so that a protein inside the cell can learn about the external concentration. With a second model for a single receptor we show that the rate at which the receptor learns about the external environment can be nonzero even without any dissipation inside the cell since chemical work done by the external process compensates for this learning rate. The third model is more complete, also containing adaptation. For this model we show inter alia that a bacterium in an environment that changes at a very slow time-scale is quite inefficient, dissipating much more than it learns. Using the concept of a coarse-grained learning rate, we show for the model with adaptation that while the activity learns about the external signal the option of changing the methylation level increases the concentration range for which the learning rate is substantial.
Efficient data IO for a Parallel Global Cloud Resolving Model
Palmer, Bruce J.; Koontz, Annette S.; Schuchardt, Karen L.; Heikes, Ross P.; Randall, David A.
2011-11-26
Execution of a Global Cloud Resolving Model (GCRM) at target resolutions of 2-4 km will generate, at a minimum, 10s of Gigabytes of data per variable per snapshot. Writing this data to disk without creating a serious bottleneck in the execution of the GCRM code while also supporting efficient post-execution data analysis is a significant challenge. This paper discusses an Input/Output (IO) application programmer interface (API) for the GCRM that efficiently moves data from the model to disk while maintaining support for community standard formats, avoiding the creation of very large numbers of files, and supporting efficient analysis. Several aspects of the API will be discussed in detail. First, we discuss the output data layout which linearizes the data in a consistent way that is independent of the number of processors used to run the simulation and provides a convenient format for subsequent analyses of the data. Second, we discuss the flexible API interface that enables modelers to easily add variables to the output stream by specifying where in the GCRM code these variables are located and to flexibly configure the choice of outputs and distribution of data across files. The flexibility of the API is designed to allow model developers to add new data fields to the output as the model develops and new physics is added and also provides a mechanism for allowing users of the GCRM code itself to adjust the output frequency and the number of fields written depending on the needs of individual calculations. Third, we describe the mapping to the NetCDF data model with an emphasis on the grid description. Fourth, we describe our messaging algorithms and IO aggregation strategies that are used to achieve high bandwidth while simultaneously writing concurrently from many processors to shared files. We conclude with initial performance results.
A simple hyperbolic model for communication in parallel processing environments
NASA Technical Reports Server (NTRS)
Stoica, Ion; Sultan, Florin; Keyes, David
1994-01-01
We introduce a model for communication costs in parallel processing environments called the 'hyperbolic model,' which generalizes two-parameter dedicated-link models in an analytically simple way. Dedicated interprocessor links parameterized by a latency and a transfer rate that are independent of load are assumed by many existing communication models; such models are unrealistic for workstation networks. The communication system is modeled as a directed communication graph in which terminal nodes represent the application processes that initiate the sending and receiving of the information and in which internal nodes, called communication blocks (CBs), reflect the layered structure of the underlying communication architecture. The direction of graph edges specifies the flow of the information carried through messages. Each CB is characterized by a two-parameter hyperbolic function of the message size that represents the service time needed for processing the message. The parameters are evaluated in the limits of very large and very small messages. Rules are given for reducing a communication graph consisting of many to an equivalent two-parameter form, while maintaining an approximation for the service time that is exact in both large and small limits. The model is validated on a dedicated Ethernet network of workstations by experiments with communication subprograms arising in scientific applications, for which a tight fit of the model predictions with actual measurements of the communication and synchronization time between end processes is demonstrated. The model is then used to evaluate the performance of two simple parallel scientific applications from partial differential equations: domain decomposition and time-parallel multigrid. In an appropriate limit, we also show the compatibility of the hyperbolic model with the recently proposed LogP model.
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.
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
Parallel Processing Systems for Passive Ranging During Helicopter Flight
NASA Technical Reports Server (NTRS)
Sridhar, Bavavar; Suorsa, Raymond E.; Showman, Robert D. (Technical Monitor)
1994-01-01
The complexity of rotorcraft missions involving operations close to the ground result in high pilot workload. In order to allow a pilot time to perform mission-oriented tasks, sensor-aiding and automation of some of the guidance and control functions are highly desirable. Images from an electro-optical sensor provide a covert way of detecting objects in the flight path of a low-flying helicopter. Passive ranging consists of processing a sequence of images using techniques based on optical low computation and recursive estimation. The passive ranging algorithm has to extract obstacle information from imagery at rates varying from five to thirty or more frames per second depending on the helicopter speed. We have implemented and tested the passive ranging algorithm off-line using helicopter-collected images. However, the real-time data and computation requirements of the algorithm are beyond the capability of any off-the-shelf microprocessor or digital signal processor. This paper describes the computational requirements of the algorithm and uses parallel processing technology to meet these requirements. Various issues in the selection of a parallel processing architecture are discussed and four different computer architectures are evaluated regarding their suitability to process the algorithm in real-time. Based on this evaluation, we conclude that real-time passive ranging is a realistic goal and can be achieved with a short time.
Application of parallel distributed processing to space based systems
NASA Technical Reports Server (NTRS)
Macdonald, J. R.; Heffelfinger, H. L.
1987-01-01
The concept of using Parallel Distributed Processing (PDP) to enhance automated experiment monitoring and control is explored. Recent very large scale integration (VLSI) advances have made such applications an achievable goal. The PDP machine has demonstrated the ability to automatically organize stored information, handle unfamiliar and contradictory input data and perform the actions necessary. The PDP machine has demonstrated that it can perform inference and knowledge operations with greater speed and flexibility and at lower cost than traditional architectures. In applications where the rule set governing an expert system's decisions is difficult to formulate, PDP can be used to extract rules by associating the information an expert receives with the actions taken.
Parallel-Processing Software for Creating Mosaic Images
NASA Technical Reports Server (NTRS)
Klimeck, Gerhard; Deen, Robert; McCauley, Michael; DeJong, Eric
2008-01-01
A computer program implements parallel processing for nearly real-time creation of panoramic mosaics of images of terrain acquired by video cameras on an exploratory robotic vehicle (e.g., a Mars rover). Because the original images are typically acquired at various camera positions and orientations, it is necessary to warp the images into the reference frame of the mosaic before stitching them together to create the mosaic. [Also see "Parallel-Processing Software for Correlating Stereo Images," Software Supplement to NASA Tech Briefs, Vol. 31, No. 9 (September 2007) page 26.] The warping algorithm in this computer program reflects the considerations that (1) for every pixel in the desired final mosaic, a good corresponding point must be found in one or more of the original images and (2) for this purpose, one needs a good mathematical model of the cameras and a good correlation of individual pixels with respect to their positions in three dimensions. The desired mosaic is divided into slices, each of which is assigned to one of a number of central processing units (CPUs) operating simultaneously. The results from the CPUs are gathered and placed into the final mosaic. The time taken to create the mosaic depends upon the number of CPUs, the speed of each CPU, and whether a local or a remote data-staging mechanism is used.
XTP as a transport protocol for distributed parallel processing
Strayer, W.T.; Lewis, M.J.; Cline, R.E. Jr.
1994-12-31
The Xpress Transfer Protocol (XTP) is a flexible transport layer protocol designed to provide efficient service without dictating the communication paradigm or the delivery characteristics that quality the paradigm. XTP provides the tools to build communication services appropriate to the application. Current data delivery solutions for many popular cluster computing environments use TCP and UDP. We examine TCP, UDP, and XTP with respect to the communication characteristics typical of parallel applications. We perform measurements of end-to-end latency for several paradigms important to cluster computing. An implementation of XTP is shown to be comparable to TCP in end-to-end latency on preestablished connections, and does better for paradigms where connections must be constructed on the fly.
Parallel processing environment for multi-flexible body dynamics
NASA Technical Reports Server (NTRS)
Venugopal, Ravi; Kumar, Manoj N.; Singh, Ramen P.; Taylor, Lawrence W., Jr.
1989-01-01
The implementation of a dynamics solution algorithm with inherent parallelism which is applicable to the dynamics of large flexible space structures is described. The algorithm is unique in that parts of the solution can be computed simultaneously by working with different branches of its tree topology. The algorithm exhibits close to 0(n) type behavior. The data flow within the solution algorithm is discussed along with results from its implementation in a multiprocessing environment. A model of the United States Space Station is used as an example. The results show that, with fast multiple scalar processors, an efficient algorithm, and symbolically generated equations of motion, real-time performance can be achieved with present-day hardware technology, even with complex dynamical models.
Efficient parallel algorithm for statistical ion track simulations in crystalline materials
NASA Astrophysics Data System (ADS)
Jeon, Byoungseon; Grønbech-Jensen, Niels
2009-02-01
We present an efficient parallel algorithm for statistical Molecular Dynamics simulations of ion tracks in solids. The method is based on the Rare Event Enhanced Domain following Molecular Dynamics (REED-MD) algorithm, which has been successfully applied to studies of, e.g., ion implantation into crystalline semiconductor wafers. We discuss the strategies for parallelizing the method, and we settle on a host-client type polling scheme in which a multiple of asynchronous processors are continuously fed to the host, which, in turn, distributes the resulting feed-back information to the clients. This real-time feed-back consists of, e.g., cumulative damage information or statistics updates necessary for the cloning in the rare event algorithm. We finally demonstrate the algorithm for radiation effects in a nuclear oxide fuel, and we show the balanced parallel approach with high parallel efficiency in multiple processor configurations.
Parallel Latent Semantic Analysis using a Graphics Processing Unit
Cui, Xiaohui; Potok, Thomas E; Cavanagh, Joseph M
2009-01-01
Latent Semantic Analysis (LSA) can be used to reduce the dimensions of large Term-Document datasets using Singular Value Decomposition. However, with the ever expanding size of data sets, current implementations are not fast enough to quickly and easily compute the results on a standard PC. The Graphics Processing Unit (GPU) can solve some highly parallel problems much faster than the traditional sequential processor (CPU). Thus, a deployable system using a GPU to speedup large-scale LSA processes would be a much more effective choice (in terms of cost/performance ratio) than using a computer cluster. In this paper, we presented a parallel LSA implementation on the GPU, using NVIDIA Compute Unified Device Architecture (CUDA) and Compute Unified Basic Linear Algebra Subprograms (CUBLAS). The performance of this implementation is compared to traditional LSA implementation on CPU using an optimized Basic Linear Algebra Subprograms library. For large matrices that have dimensions divisible by 16, the GPU algorithm ran five to six times faster than the CPU version.
Implementing a Gaussian Process Learning Algorithm in Mixed Parallel Environment
Chandola, Varun; Vatsavai, Raju
2011-01-01
In this paper, we present a scalability analysis of a parallel Gaussian process training algorithm to simultaneously analyze a massive number of time series. We study three different parallel implementations: using threads, MPI, and a hybrid implementation using threads and MPI. We compare the scalability for the multi-threaded implementation on three different hardware platforms: a Mac desktop with two quad-core Intel Xeon processors (16 virtual cores), a Linux cluster node with four quad-core 2.3 GHz AMD Opteron processors, and SGI Altix ICE 8200 cluster node with two quad-core Intel Xeon processors (16 virtual cores). We also study the scalability of the MPI based and the hybrid MPI and thread based implementations on the SGI cluster with 128 nodes (2048 cores). Experimental results show that the hybrid implementation scales better than the multi-threaded and MPI based implementations. The hybrid implementation, using 1536 cores, can analyze a remote sensing data set with over 4 million time series in nearly 5 seconds while the serial algorithm takes nearly 12 hours to process the same data set.
NASA Astrophysics Data System (ADS)
Makino, Junichiro
2002-10-01
We present a novel, highly efficient algorithm to parallelize O( N2) direct summation method for N-body problems with individual timesteps on distributed-memory parallel machines such as Beowulf clusters. Previously known algorithms, in which all processors have complete copies of the N-body system, has the serious problem that the communication-computation ratio increases as we increase the number of processors, since the communication cost is independent of the number of processors. In the new algorithm, p processors are organized as a p×p two-dimensional array. Each processor has N/ p particles, but the data are distributed in such a way that complete system is presented if we look at any row or column consisting of p processors. In this algorithm, the communication cost scales as N/ p, while the calculation cost scales as N2/ p. Thus, we can use a much larger number of processors without losing efficiency compared to what was practical with previously known algorithms.
Beta operations: efficient implementation of a primitive parallel operation. Technical report
Cohn, E.R.; Haddad, R.W.
1986-08-01
The ever-decreasing cost of computer processors has created a great interest in multi-processor computers. However, along with the increased power that this parallelism brings comes increased complexity in programming. One approach to lessening this complexity is to provide the programmer with general-purpose parallel primitives that shield him from the structure of the underlying machine. In The Connection Machine, Hillis suggests the beta operation as a parallel primitive for his hypercube-based machine. This paper explores efficient ways to perform this operation on several different well known architectures, including the hypercube. It presents some lower bounds associated with the problem.
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
Komarov, Sergey; Song, Tae Yong; Wu, Heyu; Tai, Yuan-Chuan
2014-01-01
In this work we propose a parallel beam approximation for the computation of the detection efficiency of crystals in a PET detector array. In this approximation the detection efficiency of a crystal is estimated using the distance between source and the crystal and the pre-calculated detection cross section of the crystal in a crystal array which is calculated for a uniform parallel beam of gammas. The pre-calculated detection cross sections for a few representative incident angles and gamma energies can be used to create a look-up table to be used in simulation studies or practical implementation of scatter or random correction algorithms. Utilizing the symmetries of the square crystal array, the pre-calculated look-up tables can be relatively small. The detection cross sections can be measured experimentally, calculated analytically or simulated using a Monte Carlo (MC) approach. In this work we used a MC simulation that takes into account the energy windowing, Compton scattering and factors in the “block effect”. The parallel beam approximation was validated by a separate MC simulation using point sources located at different positions around a crystal array. Experimentally measured detection efficiencies were compared with Monte Carlo simulated detection efficiencies. Results suggest that the parallel beam approximation provides an efficient and accurate way to compute the crystal detection efficiency, which can be used for estimation of random and scatter coincidences for PET data corrections. PMID:25400292
Parallel information processing channels created in the retina
Schiller, Peter H.
2010-01-01
In the retina, several parallel channels originate that extract different attributes from the visual scene. This review describes how these channels arise and what their functions are. Following the introduction four sections deal with these channels. The first discusses the “ON” and “OFF” channels that have arisen for the purpose of rapidly processing images in the visual scene that become visible by virtue of either light increment or light decrement; the ON channel processes images that become visible by virtue of light increment and the OFF channel processes images that become visible by virtue of light decrement. The second section examines the midget and parasol channels. The midget channel processes fine detail, wavelength information, and stereoscopic depth cues; the parasol channel plays a central role in processing motion and flicker as well as motion parallax cues for depth perception. Both these channels have ON and OFF subdivisions. The third section describes the accessory optic system that receives input from the retinal ganglion cells of Dogiel; these cells play a central role, in concert with the vestibular system, in stabilizing images on the retina to prevent the blurring of images that would otherwise occur when an organism is in motion. The last section provides a brief overview of several additional channels that originate in the retina. PMID:20876118
Parallel distributed processing: Implications for cognition and development. Technical report
McClelland, J.L.
1988-07-11
This paper provides a brief overview of the connectionist or parallel distributed processing framework for modeling cognitive processes, and considers the application of the connectionist framework to problems of cognitive development. Several aspects of cognitive development might result from the process of learning as it occurs in multi-layer networks. This learning process has the characteristic that it reduces the discrepancy between expected and observed events. As it does this, representations develop on hidden units which dramatically change both the way in which the network represents the environment from which it learns and the expectations that the network generates about environmental events. The learning process exhibits relatively abrupt transitions corresponding to stage shifts in cognitive development. These points are illustrated using a network that learns to anticipate which side of a balance beam will go down, based on the number of weights on each side of the fulcrum and their distance from the fulcrum on each side of the beam. The network is trained in an environment in which weight more frequently governs which side will go down. It recapitulates the states of development seen in children, as well as the stage transitions, as it learns to represent weight and distance information.
Massively Parallel Processing for Fast and Accurate Stamping Simulations
NASA Astrophysics Data System (ADS)
Gress, Jeffrey J.; Xu, Siguang; Joshi, Ramesh; Wang, Chuan-tao; Paul, Sabu
2005-08-01
The competitive automotive market drives automotive manufacturers to speed up the vehicle development cycles and reduce the lead-time. Fast tooling development is one of the key areas to support fast and short vehicle development programs (VDP). In the past ten years, the stamping simulation has become the most effective validation tool in predicting and resolving all potential formability and quality problems before the dies are physically made. The stamping simulation and formability analysis has become an critical business segment in GM math-based die engineering process. As the simulation becomes as one of the major production tools in engineering factory, the simulation speed and accuracy are the two of the most important measures for stamping simulation technology. The speed and time-in-system of forming analysis becomes an even more critical to support the fast VDP and tooling readiness. Since 1997, General Motors Die Center has been working jointly with our software vendor to develop and implement a parallel version of simulation software for mass production analysis applications. By 2001, this technology was matured in the form of distributed memory processing (DMP) of draw die simulations in a networked distributed memory computing environment. In 2004, this technology was refined to massively parallel processing (MPP) and extended to line die forming analysis (draw, trim, flange, and associated spring-back) running on a dedicated computing environment. The evolution of this technology and the insight gained through the implementation of DM0P/MPP technology as well as performance benchmarks are discussed in this publication.
MASSIVELY PARALLEL LATENT SEMANTIC ANALYSES USING A GRAPHICS PROCESSING UNIT
Cavanagh, J.; Cui, S.
2009-01-01
Latent Semantic Analysis (LSA) aims to reduce the dimensions of large term-document datasets using Singular Value Decomposition. However, with the ever-expanding size of datasets, current implementations are not fast enough to quickly and easily compute the results on a standard PC. A graphics processing unit (GPU) can solve some highly parallel problems much faster than a traditional sequential processor or central processing unit (CPU). Thus, a deployable system using a GPU to speed up large-scale LSA processes would be a much more effective choice (in terms of cost/performance ratio) than using a PC cluster. Due to the GPU’s application-specifi c architecture, harnessing the GPU’s computational prowess for LSA is a great challenge. We presented a parallel LSA implementation on the GPU, using NVIDIA® Compute Unifi ed Device Architecture and Compute Unifi ed Basic Linear Algebra Subprograms software. The performance of this implementation is compared to traditional LSA implementation on a CPU using an optimized Basic Linear Algebra Subprograms library. After implementation, we discovered that the GPU version of the algorithm was twice as fast for large matrices (1 000x1 000 and above) that had dimensions not divisible by 16. For large matrices that did have dimensions divisible by 16, the GPU algorithm ran fi ve to six times faster than the CPU version. The large variation is due to architectural benefi ts of the GPU for matrices divisible by 16. It should be noted that the overall speeds for the CPU version did not vary from relative normal when the matrix dimensions were divisible by 16. Further research is needed in order to produce a fully implementable version of LSA. With that in mind, the research we presented shows that the GPU is a viable option for increasing the speed of LSA, in terms of cost/performance ratio.
Efficient parallel algorithms for (5+1)-coloring and maximal independent set problems
Goldberg, A.V.; Plotkin, S.A.
1987-01-01
An efficient technique for breaking symmetry in parallel is described. The technique works especially well on rooted trees and on graphs with a small maximum degree. In particular, a maximal independent set can be found on a constant-degree graph in O(lg*n) time on an EREW PRAM using a linear number of processors. It is shown how to apply this technique to construct more efficient parallel algorithms for several problems, including coloring of planar graphs and (delta + 1)-coloring of constant-degree graphs. Lower bounds for two related problems are proved.
Parallel Processing of Adaptive Meshes with Load Balancing
NASA Technical Reports Server (NTRS)
Das, Sajal K.; Harvey, Daniel J.; Biswas, Rupak; Biegel, Bryan (Technical Monitor)
2001-01-01
Many scientific applications involve grids that lack a uniform underlying structure. These applications are often also dynamic in nature in that the grid structure significantly changes between successive phases of execution. In parallel computing environments, mesh adaptation of unstructured grids through selective refinement/coarsening has proven to be an effective approach. However, achieving load balance while minimizing interprocessor communication and redistribution costs is a difficult problem. Traditional dynamic load balancers are mostly inadequate because they lack a global view of system loads across processors. In this paper, we propose a novel and general-purpose load balancer that utilizes symmetric broadcast networks (SBN) as the underlying communication topology, and compare its performance with a successful global load balancing environment, called PLUM, specifically created to handle adaptive unstructured applications. Our experimental results on an IBM SP2 demonstrate that the SBN-based load balancer achieves lower redistribution costs than that under PLUM by overlapping processing and data migration.
Applying the Extended Parallel Process Model to workplace safety messages.
Basil, Michael; Basil, Debra; Deshpande, Sameer; Lavack, Anne M
2013-01-01
The extended parallel process model (EPPM) proposes fear appeals are most effective when they combine threat and efficacy. Three studies conducted in the workplace safety context examine the use of various EPPM factors and their effects, especially multiplicative effects. Study 1 was a content analysis examining the use of EPPM factors in actual workplace safety messages. Study 2 experimentally tested these messages with 212 construction trainees. Study 3 replicated this experiment with 1,802 men across four English-speaking countries-Australia, Canada, the United Kingdom, and the United States. The results of these three studies (1) demonstrate the inconsistent use of EPPM components in real-world work safety communications, (2) support the necessity of self-efficacy for the effective use of threat, (3) show a multiplicative effect where communication effectiveness is maximized when all model components are present (severity, susceptibility, and efficacy), and (4) validate these findings with gory appeals across four English-speaking countries. PMID:23330856
A Design Verification of the Parallel Pipelined Image Processings
NASA Astrophysics Data System (ADS)
Wasaki, Katsumi; Harai, Toshiaki
2008-11-01
This paper presents a case study of the design and verification of a parallel and pipe-lined image processing unit based on an extended Petri net, which is called a Logical Colored Petri net (LCPN). This is suitable for Flexible-Manufacturing System (FMS) modeling and discussion of structural properties. LCPN is another family of colored place/transition-net(CPN) with the addition of the following features: integer value assignment of marks, representation of firing conditions as marks' value based formulae, and coupling of output procedures with transition firing. Therefore, to study the behavior of a system modeled with this net, we provide a means of searching the reachability tree for markings.
Parallel asynchronous hardware implementation of image processing algorithms
NASA Technical Reports Server (NTRS)
Coon, Darryl D.; Perera, A. G. U.
1990-01-01
Research is being carried out on hardware for a new approach to focal plane processing. The hardware involves silicon injection mode devices. These devices provide a natural basis for parallel asynchronous focal plane image preprocessing. The simplicity and novel properties of the devices would permit an independent analog processing channel to be dedicated to every pixel. A laminar architecture built from arrays of the devices would form a two-dimensional (2-D) array processor with a 2-D array of inputs located directly behind a focal plane detector array. A 2-D image data stream would propagate in neuron-like asynchronous pulse-coded form through the laminar processor. No multiplexing, digitization, or serial processing would occur in the preprocessing state. High performance is expected, based on pulse coding of input currents down to one picoampere with noise referred to input of about 10 femtoamperes. Linear pulse coding has been observed for input currents ranging up to seven orders of magnitude. Low power requirements suggest utility in space and in conjunction with very large arrays. Very low dark current and multispectral capability are possible because of hardware compatibility with the cryogenic environment of high performance detector arrays. The aforementioned hardware development effort is aimed at systems which would integrate image acquisition and image processing.
Energy efficient perlite expansion process
Jenkins, K.L.
1982-08-31
A thermally efficient process for the expansion of perlite ore is described. The inlet port and burner of a perlite expansion chamber (Preferably a vertical expander) are enclosed such that no ambient air can enter the chamber. Air and fuel are metered to the burner with the amount of air being controlled such that the fuel/air premix contains at least enough air to start and maintain minimum combustion, but not enough to provide stoichiometric combustion. At a point immediately above the burner, additional air is metered into an insulated enclosure surrounding the expansion chamber where it is preheated by the heat passing through the chamber walls. This preheated additional air is then circulated back to the burner where it provides the remainder of the air needed for combustion, normally full combustion. Flow of the burner fuel/air premix and the preheated additional air is controlled so as to maintain a long luminous flame throughout a substantial portion of the expansion chamber and also to form a moving laminar layer of air on the inner surface of the expansion chamber. Preferably the burner is a delayed mixing gas burner which materially aids in the generation of the long luminous flame. The long luminous flame and the laminar layer of air at the chamber wall eliminate hot spots in the expansion chamber, result in relatively low and uniform temperature gradients across the chamber, significantly reduce the amount of fuel consumed per unit of perlite expanded, increase the yield of expanded perlite and prevent the formation of a layer of perlite sinter on the walls of the chamber.
Efficient Parallelization of a Dynamic Unstructured Application on the Tera MTA
NASA Technical Reports Server (NTRS)
Oliker, Leonid; Biswas, Rupak
1999-01-01
The success of parallel computing in solving real-life computationally-intensive problems relies on their efficient mapping and execution on large-scale multiprocessor architectures. Many important applications are both unstructured and dynamic in nature, making their efficient parallel implementation a daunting task. This paper presents the parallelization of a dynamic unstructured mesh adaptation algorithm using three popular programming paradigms on three leading supercomputers. We examine an MPI message-passing implementation on the Cray T3E and the SGI Origin2OOO, a shared-memory implementation using cache coherent nonuniform memory access (CC-NUMA) of the Origin2OOO, and a multi-threaded version on the newly-released Tera Multi-threaded Architecture (MTA). We compare several critical factors of this parallel code development, including runtime, scalability, programmability, and memory overhead. Our overall results demonstrate that multi-threaded systems offer tremendous potential for quickly and efficiently solving some of the most challenging real-life problems on parallel computers.
Mobile Devices and GPU Parallelism in Ionospheric Data Processing
NASA Astrophysics Data System (ADS)
Mascharka, D.; Pankratius, V.
2015-12-01
Scientific data acquisition in the field is often constrained by data transfer backchannels to analysis environments. Geoscientists are therefore facing practical bottlenecks with increasing sensor density and variety. Mobile devices, such as smartphones and tablets, offer promising solutions to key problems in scientific data acquisition, pre-processing, and validation by providing advanced capabilities in the field. This is due to affordable network connectivity options and the increasing mobile computational power. This contribution exemplifies a scenario faced by scientists in the field and presents the "Mahali TEC Processing App" developed in the context of the NSF-funded Mahali project. Aimed at atmospheric science and the study of ionospheric Total Electron Content (TEC), this app is able to gather data from various dual-frequency GPS receivers. It demonstrates parsing of full-day RINEX files on mobile devices and on-the-fly computation of vertical TEC values based on satellite ephemeris models that are obtained from NASA. Our experiments show how parallel computing on the mobile device GPU enables fast processing and visualization of up to 2 million datapoints in real-time using OpenGL. GPS receiver bias is estimated through minimum TEC approximations that can be interactively adjusted by scientists in the graphical user interface. Scientists can also perform approximate computations for "quickviews" to reduce CPU processing time and memory consumption. In the final stage of our mobile processing pipeline, scientists can upload data to the cloud for further processing. Acknowledgements: The Mahali project (http://mahali.mit.edu) is funded by the NSF INSPIRE grant no. AGS-1343967 (PI: V. Pankratius). We would like to acknowledge our collaborators at Boston College, Virginia Tech, Johns Hopkins University, Colorado State University, as well as the support of UNAVCO for loans of dual-frequency GPS receivers for use in this project, and Intel for loans of
Radon-Based Image Processing In A Parallel Pipeline Architecture
NASA Astrophysics Data System (ADS)
Hinkle, Eric B.; Sanz, Jorge L. C.; Jain, Anil K.
1986-04-01
This paper deals with a novel architecture that makes real-time projection-based algorithms a reality. The design is founded on raster-mode processing, which is exploited in a powerful and flexible pipeline. This architecture, dubbed "P3 E" ( Parallel Pipeline Projection Engine), supports a large variety of image processing and image analysis applications. The image processing applications include: discrete approximations of the Radon and inverse Radon transform, among other projection operators; CT reconstructions; 2-D convolutions; rotations and translations; discrete Fourier transform computations in polar coordinates; autocorrelations; etc. There is also an extensive list of key image analysis algorithms that are supported by P E, thus making it a profound and versatile tool for projection-based computer vision. These include: projections of gray-level images along linear patterns (the Radon transform) and other curved contours; generation of multi-color digital masks; convex hull approximations; Hough transform approximations for line and curve detection; diameter computations; calculations of moments and other principal components; etc. The effectiveness of our approach and the feasibility of the proposed architecture have been demonstrated by running some of these image analysis algorithms in conventional short pipelines, to solve some important automated inspection problems. In the present paper, we will concern ourselves with reconstructing images from their linear projections, and performing convolutions via the Radon transform.
Efficient parallelization of analytic bond-order potentials for large-scale atomistic simulations
NASA Astrophysics Data System (ADS)
Teijeiro, C.; Hammerschmidt, T.; Drautz, R.; Sutmann, G.
2016-07-01
Analytic bond-order potentials (BOPs) provide a way to compute atomistic properties with controllable accuracy. For large-scale computations of heterogeneous compounds at the atomistic level, both the computational efficiency and memory demand of BOP implementations have to be optimized. Since the evaluation of BOPs is a local operation within a finite environment, the parallelization concepts known from short-range interacting particle simulations can be applied to improve the performance of these simulations. In this work, several efficient parallelization methods for BOPs that use three-dimensional domain decomposition schemes are described. The schemes are implemented into the bond-order potential code BOPfox, and their performance is measured in a series of benchmarks. Systems of up to several millions of atoms are simulated on a high performance computing system, and parallel scaling is demonstrated for up to thousands of processors.
NASA Astrophysics Data System (ADS)
Li, Baoxia; Wan, Lixi; Lv, Yao; Gao, Wei; Yang, Chengyue; Li, Zhihua; Zhang, Xu
2009-06-01
We present a cost-efficient parallel optical transceiver module based on a 1×4 VCSEL array, a 1×4 PD array, and a 12-wide multimode fiber ribbon for very-short-reach application. A passive alignment technique using through-silicon-hole (TSH) has been developed to realize high-efficient butt-coupling between optoelectronic arrays and multimode fibers. In this paper, the detail optical coupling structure, misalignment tolerance, micro-assembly process, and measurement results are mainly discussed. Finally, lensed multimode fibers formed by chemical etching are proposed, which exhibit a great potential for further improvement of coupling performance.
On the design and implementation of a parallel, object-oriented, image processing toolkit
Kamath, C; Baldwin, C; Fodor, I; Tang, N A
2000-06-22
Advanced in technology have enabled us to collect data from observations, experiments, and simulations at an ever increasing pace. As these data sets approach the terabyte and petabyte range, scientists are increasingly using semi-automated techniques from data mining and pattern recognition to find useful information in the data. In order for data mining to be successful, the raw data must first be processed into a form suitable for the detection of patterns. When the data is in the form of images, this can involve a substantial amount of processing on very large data sets. To help make this task more efficient, they are designing and implementing an object-oriented image processing toolkit that specifically targets massively-parallel, distributed-memory architectures. They first show that it is possible to use object-oriented technology to effectively address the diverse needs of image applications. Next, they describe how we abstract out the similarities in image processing algorithms to enable re-use in the software. They will also discuss the difficulties encountered in parallelizing image algorithms on massively parallel machines as well as the bottlenecks to high performance. They will demonstrate the work using images from an astronomical data set, and illustrate how techniques such as filters and denoising through the thresholding of wavelet coefficients can be applied when a large image is distributed across several processors.
Design and implementation of a parallel object-oriented image processing toolkit
NASA Astrophysics Data System (ADS)
Kamath, Chandrika; Baldwin, Chuck H.; Fodor, Imola K.; Tang, Nu A.
2000-10-01
Advances in technology have enabled us to collect data from observations, experiments, and simulations at an ever increasing pace. As these data sets approach the terabyte and petabyte range, scientists are increasingly using semi-automated techniques from data mining and pattern recognition to find useful information in the data. In order for data mining to be successful, the raw data must first be processed into a form suitable for the detection of patterns. When the data is in the form of images, this can involve a substantial amount of processing on very large data sets. To help make this task more efficient, we are designing and implementing an object-oriented image processing toolkit that specifically targets massively-parallel, distributed-memory architectures. We first show that it is possible to use object-oriented technology to effectively address the diverse needs of image applications. Next, we describe how we abstract out the similarities in image processing algorithms to enable re-use in our software. We will also discuss the difficulties encountered in parallelizing image algorithms on the massively parallel machines as well as the bottlenecks to high performance. We will demonstrate our work using images from an astronomical data set, and illustrate how techniques such as filters and denoising through the thresholding of wavelet coefficients can be applied when a large image is distributed across several processors.
Resolving Multiscale Processes in Tropical Cyclogenesis Using Parallel EEMD
NASA Astrophysics Data System (ADS)
Wu, Y.; Shen, B. W.; Cheung, S.; Li, J. L. F.; Liu, Z.
2014-12-01
The recent advance in high-resolution global models has suggested that improved multiscale simulations of tropical waves may help extend the lead time of tropical cyclone (TC) formation prediction (e.g., Shen et al., 2010ab, 2012, 2013a). In previous efforts in the multiscale analysis of tropical waves , the Ensemble Empirical Mode Decomposition (EEMD) has been successfully parallelized and used to detect atmospheric wave signals on different spatial scales (e.g. Shen et al., 2013b) that include Mixed Rossby Gravity (MRG) waves, Western Wind Belt (WWB), African Easterly Waves (AEWs), etc. We now extend the related studies to examine the evolution of the large scale waves and their association with the formation of tropical cyclones in the Atlantic for an extensive time period spanning multiple years. Our goal is to analyze the multiscale interaction in the initiation and early intensification stage of an AEW and its subsequent impact on TC genesis that involves mainly the large scale downscaling processes. Specific focus is on the impact of barotropic instability and critical level (CL, or steering level) that may appear in association with the AEW. The presence of the CL is believed to play an important role in providing a favorable environment in the early TC-genesis stage in the marsupial paradigm scenario. Preliminary analysis of the satellite data obtained from the newly launched Global Precipitation Measurement (GPM) mission linked to the TC genesis processes will be included.
NASA Astrophysics Data System (ADS)
Huang, M.; Mielikainen, J.; Huang, B.; Chen, H.; Huang, H.-L. A.; Goldberg, M. D.
2015-09-01
The planetary boundary layer (PBL) is the lowest part of the atmosphere and where its character is directly affected by its contact with the underlying planetary surface. The PBL is responsible for vertical sub-grid-scale fluxes due to eddy transport in the whole atmospheric column. It determines the flux profiles within the well-mixed boundary layer and the more stable layer above. It thus provides an evolutionary model of atmospheric temperature, moisture (including clouds), and horizontal momentum in the entire atmospheric column. For such purposes, several PBL models have been proposed and employed in the weather research and forecasting (WRF) model of which the Yonsei University (YSU) scheme is one. To expedite weather research and prediction, we have put tremendous effort into developing an accelerated implementation of the entire WRF model using graphics processing unit (GPU) massive parallel computing architecture whilst maintaining its accuracy as compared to its central processing unit (CPU)-based implementation. This paper presents our efficient GPU-based design on a WRF YSU PBL scheme. Using one NVIDIA Tesla K40 GPU, the GPU-based YSU PBL scheme achieves a speedup of 193× with respect to its CPU counterpart running on one CPU core, whereas the speedup for one CPU socket (4 cores) with respect to 1 CPU core is only 3.5×. We can even boost the speedup to 360× with respect to 1 CPU core as two K40 GPUs are applied.
Archer, Charles J; Blocksome, Michael A; Cernohous, Bob R; Ratterman, Joseph D; Smith, Brian E
2014-11-18
Methods, apparatuses, and computer program products for endpoint-based parallel data processing with non-blocking collective instructions in a parallel active messaging interface (`PAMI`) of a parallel computer are provided. Embodiments include establishing by a parallel application a data communications geometry, the geometry specifying a set of endpoints that are used in collective operations of the PAMI, including associating with the geometry a list of collective algorithms valid for use with the endpoints of the geometry. Embodiments also include registering in each endpoint in the geometry a dispatch callback function for a collective operation and executing without blocking, through a single one of the endpoints in the geometry, an instruction for the collective operation.
Variation in efficiency of parallel algorithms. [for study of stiffness matrices in planar trusses
NASA Technical Reports Server (NTRS)
Hayashi, A.; Melosh, R. J.; Utku, S.; Salama, M.
1985-01-01
The present study has the objective to investigate some iterative parallel-processor linear equation solving algorithms with respect to efficiency for analyses of typical linear engineering systems. Attention is given to a set of n linear equations, Ku = p, where K = an n x n positive definite, sparsely populated, symmetric matrix, u = an n x 1 vector of unknown responses, and p = an n x 1 vector of prescribed constants. This study is concerned with a hybrid method in which iteration is used to solve the problem, while a direct method is used on the local processor level. Variations in the efficiency of parallel algorithms are explored. Measures of the efficiency are based on computer experiments regarding the algorithms. For all the algorithms, the wall clock time is found to decrease as the number of processors increases.
An efficient parallel algorithm for the solution of a tridiagonal linear system of equations
NASA Technical Reports Server (NTRS)
Stone, H. S.
1971-01-01
Tridiagonal linear systems of equations are solved on conventional serial machines in a time proportional to N, where N is the number of equations. The conventional algorithms do not lend themselves directly to parallel computations on computers of the ILLIAC IV class, in the sense that they appear to be inherently serial. An efficient parallel algorithm is presented in which computation time grows as log sub 2 N. The algorithm is based on recursive doubling solutions of linear recurrence relations, and can be used to solve recurrence relations of all orders.
An efficient parallel algorithm for the solution of a tridiagonal linear system of equations.
NASA Technical Reports Server (NTRS)
Stone, H. S.
1973-01-01
Tridiagonal linear systems of equations can be solved on conventional serial machines in a time proportional to N, where N is the number of equations. The conventional algorithms do not lend themselves directly to parallel computation on computers of the Illiac IV class, in the sense that they appear to be inherently serial. An efficient parallel algorithm is presented in which computation time grows as log(sub-2) N. The algorithm is based on recursive doubling solutions of linear recurrence relations, and can be used to solve recurrence relations of all orders.
On the parallel efficiency of the Frederickson-McBryan multigrid
NASA Technical Reports Server (NTRS)
Decker, Naomi H.
1990-01-01
To take full advantage of the parallelism in a standard multigrid algorithm requires as many processors as points. However, since coarse grids contain fewer points, most processors are idle during the coarse grid iterations. Frederickson and McBryan claim that retaining all points on all grid levels (using all processors) can lead to a superconvergent algorithm. The purpose of this work is to show that the parellel superconvergent multigrid (PSMG) algorithm of Frederickson and McBryan, though it achieves perfect processor utilization, is no more efficient than a parallel implementation of standard multigrid methods. PSMG is simply a new and perhaps simpler way of achieving the same results.
NASA Technical Reports Server (NTRS)
Oakley, David R.; Knight, Norman F., Jr.
1994-01-01
A parallel adaptive dynamic relaxation (ADR) algorithm has been developed for nonlinear structural analysis. This algorithm has minimal memory requirements, is easily parallelizable and scalable to many processors, and is generally very reliable and efficient for highly nonlinear problems. Performance evaluations on single-processor computers have shown that the ADR algorithm is reliable and highly vectorizable, and that it is competitive with direct solution methods for the highly nonlinear problems considered. The present algorithm is implemented on the 512-processor Intel Touchstone DELTA system at Caltech, and it is designed to minimize the extent and frequency of interprocessor communication. The algorithm has been used to solve for the nonlinear static response of two and three dimensional hyperelastic systems involving contact. Impressive relative speedups have been achieved and demonstrate the high scalability of the ADR algorithm. For the class of problems addressed, the ADR algorithm represents a very promising approach for parallel-vector processing.
Efficient Extraction of Regional Subsets from Massive Climate Datasets using Parallel IO
Daily, Jeffrey A.; Schuchardt, Karen L.; Palmer, Bruce J.
2010-09-16
The size of datasets produced by current climate models is increasing rapidly to the scale of petabytes. To handle data at this scale parallel analysis tools are required, however the majority of climate analysis software remains at the scale of workstations. Further, many climate analysis tools adequately process regularly gridded data but lack sufficient features when handling unstructured grids. This paper presents a data-parallel subsetter capable of correctly handling unstructured grids while scaling to over 2000 cores. The approach is based on the partitioned global address space (PGAS) parallel programming model and one-sided communication. The paper demonstrates that IO remains the single greatest bottleneck for this domain of applications and that parallel analysis of climate data succeeds in practice.
Fast phase processing in off-axis holography by CUDA including parallel phase unwrapping.
Backoach, Ohad; Kariv, Saar; Girshovitz, Pinhas; Shaked, Natan T
2016-02-22
We present parallel processing implementation for rapid extraction of the quantitative phase maps from off-axis holograms on the Graphics Processing Unit (GPU) of the computer using computer unified device architecture (CUDA) programming. To obtain efficient implementation, we parallelized both the wrapped phase map extraction algorithm and the two-dimensional phase unwrapping algorithm. In contrast to previous implementations, we utilized unweighted least squares phase unwrapping algorithm that better suits parallelism. We compared the proposed algorithm run times on the CPU and the GPU of the computer for various sizes of off-axis holograms. Using the GPU implementation, we extracted the unwrapped phase maps from the recorded off-axis holograms at 35 frames per second (fps) for 4 mega pixel holograms, and at 129 fps for 1 mega pixel holograms, which presents the fastest processing framerates obtained so far, to the best of our knowledge. We then used common-path off-axis interferometric imaging to quantitatively capture the phase maps of a micro-organism with rapid flagellum movements. PMID:26906982
Rapid parallel semantic processing of numbers without awareness.
Van Opstal, Filip; de Lange, Floris P; Dehaene, Stanislas
2011-07-01
In this study, we investigate whether multiple digits can be processed at a semantic level without awareness, either serially or in parallel. In two experiments, we presented participants with two successive sets of four simultaneous Arabic digits. The first set was masked and served as a subliminal prime for the second, visible target set. According to the instructions, participants had to extract from the target set either the mean or the sum of the digits, and to compare it with a reference value. Results showed that participants applied the requested instruction to the entire set of digits that was presented below the threshold of conscious perception, because their magnitudes jointly affected the participant's decision. Indeed, response decision could be accurately modeled as a sigmoid logistic function that pooled together the evidence provided by the four targets and, with lower weights, the four primes. In less than 800ms, participants successfully approximated the addition and mean tasks, although they tended to overweight the large numbers, particularly in the sum task. These findings extend previous observations on ensemble coding by showing that set statistics can be extracted from abstract symbolic stimuli rather than low-level perceptual stimuli, and that an ensemble code can be represented without awareness. PMID:21489415
An integrated approach to improving the parallel applications development process
Rasmussen, Craig E; Watson, Gregory R; Tibbitts, Beth R
2009-01-01
The development of parallel applications is becoming increasingly important to a broad range of industries. Traditionally, parallel programming was a niche area that was primarily exploited by scientists trying to model extremely complicated physical phenomenon. It is becoming increasingly clear, however, that continued hardware performance improvements through clock scaling and feature-size reduction are simply not going to be achievable for much longer. The hardware vendor's approach to addressing this issue is to employ parallelism through multi-processor and multi-core technologies. While there is little doubt that this approach produces scaling improvements, there are still many significant hurdles to be overcome before parallelism can be employed as a general replacement to more traditional programming techniques. The Parallel Tools Platform (PTP) Project was created in 2005 in an attempt to provide developers with new tools aimed at addressing some of the parallel development issues. Since then, the introduction of a new generation of peta-scale and multi-core systems has highlighted the need for such a platform. In this paper, we describe some of the challenges facing parallel application developers, present the current state of PTP, and provide a simple case study that demonstrates how PTP can be used to locate a potential deadlock situation in an MPI code.
NASA Astrophysics Data System (ADS)
Jacob, R. L.; Xu, X.; Krishna, J.; Tautges, T.
2011-12-01
The relationship between the needs of post-processing climate model output and the capability of the available tools has reached a crisis point. The large volume of data currently produced by climate models is overwhelming the current, decades-old analysis workflow. The tools used to implement that workflow are now a bottleneck in the climate science discovery processes. This crisis will only worsen as ultra-high resolution global climate models with horizontal scales of 4 km or smaller, running on leadership computing facilities, begin to produce tens to hundreds of terabytes for a single, hundred-year climate simulation. While climate models have used parallelism for several years, the post-processing tools are still mostly single-threaded applications. We have created a Parallel Climate Analysis Library (ParCAL) which implements many common climate analysis operations in a data-parallel fashion using the Message Passing Interface. ParCAL has in turn been built on sophisticated packages for describing grids in parallel (the Mesh Oriented database (MOAB) and for performing vector operations on arbitrary grids (Intrepid). ParCAL is also using parallel I/O through the PnetCDF library. ParCAL has been used to implement a parallel version of the NCAR Command Language (NCL). ParNCL/ParCAL not only speeds up analysis of large datasets but also allows operations to be performed on native grids, eliminating the need to transform everything to latitude-longitude grids. In most cases, users NCL scripts can run unaltered in parallel using ParNCL.
Parallel processing experiences on the Denelcor HEP computer
Hayes, A.H.
1984-01-01
Recent experiments conducted on a Denelcor HEP (Heterogeneous Element Processor) computer are discussed in this paper. Algorithm research was done on four types of problems of interest to the Los Alamos National Laboratory: (1) Monte Carlo, using GAMTAB, in which the interaction of photons with matter is analyzed; (2) Hydrodynamics; (3) Reactor Safety, in which the operation of a nuclear reactor is simulated; and (4) Particle-in-Cell, in which electrostatic interaction of plasma beams are studied. Means of maximizing programming efficiency are analyzed with ways of speeding up processing determined.
Low-cost reconfigurable DSP-based parallel image processing computer
NASA Astrophysics Data System (ADS)
Murphy, Ciaron W.; Harvey, David M.; Nicolson, Laurence J.
1998-10-01
To develop a cost-effective re-configurable DSP engine, it has been proposed to upgrade an existing custom designed TMS320C40 based multi-processing architecture with run-time configuration capabilities. The upgrade will consist of four Xilinx XC6200 series field programmable gate arrays which will enable concurrent algorithm structures to be efficiently mapped onto the system. Furthermore, the upgraded architecture will provide a platform for the development of adaptive routing structures, self- configuration techniques and facilitate the merging of instruction and hardware based parallelism.
Parallel-processing with surface plasmons, a new strategy for converting the broad solar spectrum
NASA Technical Reports Server (NTRS)
Anderson, L. M.
1982-01-01
A new strategy for efficient solar-energy conversion is based on parallel processing with surface plasmons: guided electromagnetic waves supported on thin films of common metals like aluminum or silver. The approach is unique in identifying a broadband carrier with suitable range for energy transport and an inelastic tunneling process which can be used to extract more energy from the more energetic carriers without requiring different materials for each frequency band. The aim is to overcome the fundamental 56-percent loss associated with mismatch between the broad solar spectrum and the monoenergetic conduction electrons used to transport energy in conventional silicon solar cells. This paper presents a qualitative discussion of the unknowns and barrier problems, including ideas for coupling surface plasmons into the tunnels, a step which has been the weak link in the efficiency chain.
The finite element machine: An experiment in parallel processing
NASA Technical Reports Server (NTRS)
Storaasli, O. O.; Peebles, S. W.; Crockett, T. W.; Knott, J. D.; Adams, L.
1982-01-01
The finite element machine is a prototype computer designed to support parallel solutions to structural analysis problems. The hardware architecture and support software for the machine, initial solution algorithms and test applications, and preliminary results are described.
A methodology for exploiting parallelism in the finite element process
NASA Technical Reports Server (NTRS)
Adams, L. M.; Voigt, R. G.
1983-01-01
A methodology is described for developing a parallel system using a top down approach taking into account the requirements of the user. Substructuring, a popular technique in structural analysis, is used to illustrate this approach.
Mniszewski, S M; Cawkwell, M J; Wall, M E; Mohd-Yusof, J; Bock, N; Germann, T C; Niklasson, A M N
2015-10-13
We present an algorithm for the calculation of the density matrix that for insulators scales linearly with system size and parallelizes efficiently on multicore, shared memory platforms with small and controllable numerical errors. The algorithm is based on an implementation of the second-order spectral projection (SP2) algorithm [ Niklasson, A. M. N. Phys. Rev. B 2002 , 66 , 155115 ] in sparse matrix algebra with the ELLPACK-R data format. We illustrate the performance of the algorithm within self-consistent tight binding theory by total energy calculations of gas phase poly(ethylene) molecules and periodic liquid water systems containing up to 15,000 atoms on up to 16 CPU cores. We consider algorithm-specific performance aspects, such as local vs nonlocal memory access and the degree of matrix sparsity. Comparisons to sparse matrix algebra implementations using off-the-shelf libraries on multicore CPUs, graphics processing units (GPUs), and the Intel many integrated core (MIC) architecture are also presented. The accuracy and stability of the algorithm are illustrated with long duration Born-Oppenheimer molecular dynamics simulations of 1000 water molecules and a 303 atom Trp cage protein solvated by 2682 water molecules. PMID:26574255
Voltage and Reactive Power Control by Parallel Calculation Processing
NASA Astrophysics Data System (ADS)
Michihata, Masashi; Aoki, Hidenori; Mizutani, Yoshibumi
This paper presents a new approach to optimal voltage and reactive power control based on a genetic algorithm (GA) and a tabu search (TS). To reduce time to calculate the control procedure, the parallel computation using Linux is executed. In addition, TS and GA are calculated by the master and each slave based on the parallel program language. The effectiveness of the proposed method is demonstrated by practical 118-bus system.
NASA Technical Reports Server (NTRS)
Hsieh, Shang-Hsien
1993-01-01
The principal objective of this research is to develop, test, and implement coarse-grained, parallel-processing strategies for nonlinear dynamic simulations of practical structural problems. There are contributions to four main areas: finite element modeling and analysis of rotational dynamics, numerical algorithms for parallel nonlinear solutions, automatic partitioning techniques to effect load-balancing among processors, and an integrated parallel analysis system.
Parallelized CCHE2D flow model with CUDA Fortran on Graphics Process Units
Technology Transfer Automated Retrieval System (TEKTRAN)
This paper presents the CCHE2D implicit flow model parallelized using CUDA Fortran programming technique on Graphics Processing Units (GPUs). A parallelized implicit Alternating Direction Implicit (ADI) solver using Parallel Cyclic Reduction (PCR) algorithm on GPU is developed and tested. This solve...
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.
2013-01-01
Background Expression and purification of correctly folded proteins typically require screening of different parameters such as protein variants, solubility enhancing tags or expression hosts. Parallel vector series that cover all variations are available, but not without compromise. We have established a fast, efficient and absolutely background free cloning approach that can be applied to any selected vector. Results Here we describe a method to tailor selected expression vectors for parallel Sequence and Ligation Independent Cloning. SLIC cloning enables precise and sequence independent engineering and is based on joining vector and insert with 15–25 bp homologies on both DNA ends by homologous recombination. We modified expression vectors based on pET, pFastBac and pTT backbones for parallel PCR-based cloning and screening in E.coli, insect cells and HEK293E cells, respectively. We introduced the toxic ccdB gene under control of a strong constitutive promoter for counterselection of insert less vector. In contrast to DpnI treatment commonly used to reduce vector background, ccdB used in our vector series is 100% efficient in killing parental vector carrying cells and reduces vector background to zero. In addition, the 3’ end of ccdB functions as a primer binding site common to all vectors. The second shared primer binding site is provided by a HRV 3C protease cleavage site located downstream of purification and solubility enhancing tags for tag removal. We have so far generated more than 30 different parallel expression vectors, and successfully cloned and expressed more than 250 genes with this vector series. There is no size restriction for gene insertion, clone efficiency is > 95% with clone numbers up to 200. The procedure is simple, fast, efficient and cost-effective. All expression vectors showed efficient expression of eGFP and different target proteins requested to be produced and purified at our Core Facility services. Conclusion This new
Efficient parallelization for AMR MHD multiphysics calculations; implementation in AstroBEAR
NASA Astrophysics Data System (ADS)
Carroll-Nellenback, Jonathan J.; Shroyer, Brandon; Frank, Adam; Ding, Chen
2013-03-01
Current adaptive mesh refinement (AMR) simulations require algorithms that are highly parallelized and manage memory efficiently. As compute engines grow larger, AMR simulations will require algorithms that achieve new levels of efficient parallelization and memory management. We have attempted to employ new techniques to achieve both of these goals. Patch or grid based AMR often employs ghost cells to decouple the hyperbolic advances of each grid on a given refinement level. This decoupling allows each grid to be advanced independently. In AstroBEAR we utilize this independence by threading the grid advances on each level with preference going to the finer level grids. This allows for global load balancing instead of level by level load balancing and allows for greater parallelization across both physical space and AMR level. Threading of level advances can also improve performance by interleaving communication with computation, especially in deep simulations with many levels of refinement. While we see improvements of up to 30% on deep simulations run on a few cores, the speedup is typically more modest (5-20%) for larger scale simulations. To improve memory management we have employed a distributed tree algorithm that requires processors to only store and communicate local sections of the AMR tree structure with neighboring processors. Using this distributed approach we are able to get reasonable scaling efficiency (>80%) out to 12288 cores and up to 8 levels of AMR - independent of the use of threading.
Archer, Charles J; Blocksome, Michael A; Cernohous, Bob R; Ratterman, Joseph D; Smith, Brian E
2014-11-11
Endpoint-based parallel data processing with non-blocking collective instructions in a PAMI of a parallel computer is disclosed. The PAMI is composed of data communications endpoints, each 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 are coupled for data communications through the PAMI. The parallel application establishes a data communications geometry specifying a set of endpoints that are used in collective operations of the PAMI by associating with the geometry a list of collective algorithms valid for use with the endpoints of the geometry; registering in each endpoint in the geometry a dispatch callback function for a collective operation; and executing without blocking, through a single one of the endpoints in the geometry, an instruction for the collective operation.
NASA Astrophysics Data System (ADS)
Norman, Matthew Ross
The social need for realistic atmospheric simulation in weather prediction, climate change attribution, seasonal forecasting, and climate projection is great. To obtain realistic simulations, we need more physical processes included in the model with greater fidelity and finer spatial resolution. Spatial resolution primarily drives the need for computational resources because reducing the model grid spacing by a factor f requires f 4 times more computation (assuming 3-D refinement). This compute power comes from large parallel machines with 10,000s of separate nodes and accelerators such as graphics processing units (GPUs) making efficiency a complicated problem. Efficiency parallel integration algorithms need low internode communication, minimal synchronization, large time steps, and clustered computation. To this end, we propose new characteristics-based methods for the atmospheric dynamical equations with these properties in mind. These schemes are capable of simulating at a large CFL time step in only one stage of computations, needing only one copy of the state variables. They are implemented in a 2-D non-hydrostatic compressible equation set in an x-z (horizontal-vertical) Cartesian plane to simulate buoyancy-driven flows such as rising thermals and internal gravity waves. The schemes are implemented to run on CPU and multi-GPU architectures using Nvidia's CUDA (Compute Unified Device Architecture) language to test relative efficiency. Even with- out memory tuning, the GPU code showed roughly 2.5x (5x) better performance per Watt. With optimization, this could increase by an order of magnitude. The methods can use any spatial interpolant, so two major formulations are proposed and tested. One uses WENO interpolants which are pre-computed, and the other uses standard polynomials and computes them on-the-fly. The advantage of on-the-fly calculations is a significant reduction in the volume of data communicated to and from the GPU's slow global memory. In some
the finite element machine: An experiment in parallel processing
NASA Technical Reports Server (NTRS)
Storaasli, O. O.; Peebles, S. W.; Crockett, T. W.; Knott, J. D.; Adams, L.
1982-01-01
The Finite Element Machine at the NASA Langley Research Center is a prototype computer designed to support parallel solutions to structural analysis problems. The hardware architecture and support software for the machine, initial solution algorithms and test applications, and preliminary results are described. Directions for future work are presented.
Parallel design of JPEG-LS encoder on graphics processing units
NASA Astrophysics Data System (ADS)
Duan, Hao; Fang, Yong; Huang, Bormin
2012-01-01
With recent technical advances in graphic processing units (GPUs), GPUs have outperformed CPUs in terms of compute capability and memory bandwidth. Many successful GPU applications to high performance computing have been reported. JPEG-LS is an ISO/IEC standard for lossless image compression which utilizes adaptive context modeling and run-length coding to improve compression ratio. However, adaptive context modeling causes data dependency among adjacent pixels and the run-length coding has to be performed in a sequential way. Hence, using JPEG-LS to compress large-volume hyperspectral image data is quite time-consuming. We implement an efficient parallel JPEG-LS encoder for lossless hyperspectral compression on a NVIDIA GPU using the computer unified device architecture (CUDA) programming technology. We use the block parallel strategy, as well as such CUDA techniques as coalesced global memory access, parallel prefix sum, and asynchronous data transfer. We also show the relation between GPU speedup and AVIRIS block size, as well as the relation between compression ratio and AVIRIS block size. When AVIRIS images are divided into blocks, each with 64×64 pixels, we gain the best GPU performance with 26.3x speedup over its original CPU code.