Results 161 to 170 of about 1,316 (216)

Parallelism-Optimizing Data Placement for Faster Data-Parallel Computations

Proceedings of the VLDB Endowment, 2022
Systems performing large data-parallel computations, including online analytical processing (OLAP) systems like Druid and search engines like Elasticsearch, are increasingly being used for business-critical real-time applications where providing low query latency is paramount.
Nirvik Baruah, Peter Kraft, Fiodar Kazhamiaka, Peter Bailis, Matei Zaharia   +4 more
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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 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 L. Bagrodia
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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 Jr.
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Data-parallel computing

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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Data parallelism and Linda

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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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 parallelism in Haskell

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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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.
Alex L. Cheung, Anthony P. Reeves
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Moving data in parallel

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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