Results 281 to 290 of about 178,091 (333)

Integrating task parallelism in data parallel languages for parallel programming on NOWs

Concurrency: Practice and Experience, 2000
Summary: A number of high-level parallel programming platforms for networks of workstations (NOWs) have been developed in recent times. Most of these platforms target the exploitation of data parallelism in applications. They do not allow expressibility of applications as a collection of tasks along with their precedence relationships. As a result, the
K. J. Binu, D. Janaki Ram
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Function-Parallel Computation in a Data-Parallel Environment

1993 International Conference on Parallel Processing - ICPP'93 Vol2, 1993
Asynchromus problems are those which may be decomposed into a set of independenr sub-tasks which are suitable for concurrent execution. Th function paraIIeIism of these problems cannot normally be direcrly expressed using the data-parallel programming model.
Anthony P. Reeves, Alex L. Cheung
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Data-Parallel Programming on A Reconfigurable Parallel Computer

IETE Technical Review, 1998
We present a preprocessor which converts programs written in a data parallel version of C into standard C to run on CDOT CHiPPS, a reconfigurable parallel computer. The main contribution is the development of rewriting methods and an optimizing protocol for inter-processor communication during barrier synchronization.
Ranjan K Sen, M Periswamy, Rajesh K, S Selvakumar   +3 more
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Parallelizing data race detection

ACM SIGARCH Computer Architecture News, 2013
Detecting data races in multithreaded programs is a crucial part of debugging such programs, but traditional data race detectors are too slow to use routinely. This paper shows how to speed up race detection by spreading the work across multiple cores.
Peter M. Chen, Benjamin Wester, Jason Flinn, David Devecsery, Satish Narayanasamy   +4 more
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Exploitation of control parallelism in data parallel algorithms

Proceedings Frontiers '95. The Fifth Symposium on the Frontiers of Massively Parallel Computation, 2002
This paper considers the matrix decomposition A=LDL/sup T/, as a vehicle to explore the improvement in performance obtainable through the execution of multiple streams of control on SIMD architectures. Several methods for partitioning the SIMD array are considered.
V. Garg, D.E. Schimmel
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Parallel simulation of data parallel programs

1996
Accurate simulations of parallel programs for large datasets can often be slow; parallel execution has been shown to offer significant potential in reducing the execution time of many discrete-event simulators. In this paper, we describe the design and implementation of a parallel simulator called DPSIM that simulates the execution of data parallel ...
Sundeep Prakash, Rajive Bagrodia
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PROBLEMS WITH DATA PARALLELISM

Parallel Processing Letters, 2001
The gradual evolution of language features and approaches used for the programming of distributed memory machines underwent substantial advances in the 1990s. One of the most promising and widely praised approaches was based on data parallelism and resulted in High Performance Fortran. This paper reports on an experiment using that approach based on a
Carol Phillips, Ronald H. Perrott
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Parallel Image Processing with the Block Data Parallel Architecture

IBM Journal of Research and Development, 1996
Many digital signal and image processing algorithms can be speeded up by executing them in parallel on multiple processors. The speed of parallel execution is limited by the need for communication and synchronization between processors. In this paper, we present a paradigm for parallel processing that we call the block data flow paradigm (BDFP).
Douglas S. Reeves, Winser E. Alexander, Clay Gloster   +2 more
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Data Parallelism, Control Parallelism, and Related Issues

2000
This Chapter focuses on the differences between control parallelism and data parallelism, which are important to understand the discussion about parallel data mining in later Chapters of this book. After an introduction to control and data parallelism, we discuss the effect of exploiting these two kinds of parallelism in three important issues, namely ...
Simon H. Lavington, Alex A. Freitas
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Data parallel algorithms

Communications of the ACM, 1986
Parallel computers with tens of thousands of processors are typically programmed in a data parallel style, as opposed to the control parallel style used in multiprocessing. The success of data parallel algorithms—even on problems that at first glance seem inherently serial—suggests that this style of programming has much wider applicability than was ...
W. Daniel Hillis, Guy L. Steele
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