Results 161 to 170 of about 27,095 (213)
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ACM SIGGRAPH 2008 classes, 2008
Users always care about performance. Although often it's just a matter of making sure the software is doing only what it should, there are many cases where it is vital to get down to the metal and leverage the fundamental characteristics of the processor.Until recently, performance improvement was not difficult.
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Users always care about performance. Although often it's just a matter of making sure the software is doing only what it should, there are many cases where it is vital to get down to the metal and leverage the fundamental characteristics of the processor.Until recently, performance improvement was not difficult.
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1993
Is the owner-computes style of parallelism, captured in a variety of data parallel languages, attractive as a paradigm for designing explicitly parallel codes? This question gives rise to a number of others. Will such use be unwieldy? Will the resulting code run well?
Nicholas Carriero, David Gelernter
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Is the owner-computes style of parallelism, captured in a variety of data parallel languages, attractive as a paradigm for designing explicitly parallel codes? This question gives rise to a number of others. Will such use be unwieldy? Will the resulting code run well?
Nicholas Carriero, David Gelernter
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Function-Parallel Computation in a Data-Parallel Environment
1993 International Conference on Parallel Processing - ICPP'93 Vol2, 1993Asynchromus 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.
Alex L. Cheung, Anthony P. Reeves
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Data parallelism in logic programming [PDF]
, 1991 Many researchers have been trying to use the implicit parallelism of logic languages parallelizing the execution of independent clauses. However this approach has the disadvantage of requiring a heavy overhead for processes scheduling and synchronizing, for data migration and for collecting the results. In this paper it is proposed a different approach,
Succi G, Marino G
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Data-Parallel Sparse Factorization
SIAM Journal on Scientific Computing, 1998The data-parallel implementation of the multifrontal algorithm for the LU factorization, without pivoting, of matrices having symmetric structure and nonsymmetric coefficients is considered. A simple yet efficient and scalable implementation of the multifrontal sparse LU factorization is presented.
John M. Conroy +3 more
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Proceedings of the 2nd ACM SIGPLAN workshop on Functional high-performance computing, 2013
The implicit data parallelism in collective operations on aggregate data structures constitutes an attractive parallel programming model for functional languages. Beginning with our work on integrating nested data parallelism into Haskell, we explored a variety of different approaches to array-centric data parallel programming in Haskell, experimented ...
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The implicit data parallelism in collective operations on aggregate data structures constitutes an attractive parallel programming model for functional languages. Beginning with our work on integrating nested data parallelism into Haskell, we explored a variety of different approaches to array-centric data parallel programming in Haskell, experimented ...
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Journal of Parallel and Distributed Computing, 1994
Abstract In data-parallel programming, operations are performed simultaneously on all elements of large data structures. Backus′s FP functional language promotes this view. FP provides a large set of data rearrangement primitives, and a useful set of functional combining forms that are applied to entire data structures.
Clifford Walinsky, Deb Banerjee
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Abstract In data-parallel programming, operations are performed simultaneously on all elements of large data structures. Backus′s FP functional language promotes this view. FP provides a large set of data rearrangement primitives, and a useful set of functional combining forms that are applied to entire data structures.
Clifford Walinsky, Deb Banerjee
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1994
This article presents a data-parallel language, which has been designed around the concepts of relations and reduction operations. Many parallel machines provide hardware support for reduction operations (such as summing all elements of an array), and these operations are widely used in parallel scientific computing.
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This article presents a data-parallel language, which has been designed around the concepts of relations and reduction operations. Many parallel machines provide hardware support for reduction operations (such as summing all elements of an array), and these operations are widely used in parallel scientific computing.
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COMPCON Spring '91 Digest of Papers, 2002
The author examines a method of applying parallelism to data-moving operations to enhance performance so that they may fit into today's maintenance windows. She specifically discusses converting the algorithm used to load an alternate key file (index) from serial to parallel using Tandem's Non-Stop SQL.
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The author examines a method of applying parallelism to data-moving operations to enhance performance so that they may fit into today's maintenance windows. She specifically discusses converting the algorithm used to load an alternate key file (index) from serial to parallel using Tandem's Non-Stop SQL.
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On Parallelizing the MRRR Algorithm for Data-Parallel Coprocessors
2010The eigenvalues and eigenvectors of a symmetric matrix are of interest in a myriad of applications. One of the fastest and most accurate numerical techniques for the eigendecomposition is the Algorithm of Multiple Relatively Robust Representations (MRRR), the first stable algorithm that computes the eigenvalues and eigenvectors of a tridiagonal ...
Christian Lessig, Paolo Bientinesi
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