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Data parallelism

Known as: Data level parallelism, Data-parallelism, Data-level parallelism 
Data parallelism is a form of parallelization across multiple processors in parallel computing environments. It focuses on distributing the data… Expand
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Papers overview

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Highly Cited
2019
Highly Cited
2019
Recent hardware developments have dramatically increased the scale of data parallelism available for neural network training… Expand
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Highly Cited
2011
Highly Cited
2011
For more than thirty years, the parallel programming community has used the dependence graph as the main abstraction for… Expand
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Highly Cited
2010
Highly Cited
2010
With the increase in available data parallel machine learning has become an increasingly pressing problem. In this paper we… Expand
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Highly Cited
2009
Highly Cited
2009
  • J. Xu
  • 2009
  • Corpus ID: 16804330
Today's computers are becoming increasing reliant on parallel computing. Processors are shipping with multiple cores, and new… Expand
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Highly Cited
2007
Highly Cited
2007
Irregular applications, which manipulate large, pointer-based data structures like graphs, are difficult to parallelize manually… Expand
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Highly Cited
2005
Highly Cited
2005
This chapter describes the design and features of a visualization tool called ParaView, a tool that allows scientists to… Expand
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Highly Cited
1998
Highly Cited
1998
The most exciting development in parallel computer architecture is the convergence of traditionally disparate approaches on a… Expand
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Highly Cited
1996
Highly Cited
1996
A complete Alpine cross section integrates numerous seismic reflection and refraction profiles, across and along strike, with… Expand
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Highly Cited
1993
Highly Cited
1993
Loop fusion is a program transformation that merges multiple loops into one. It is effective for reducing the synchronization… Expand
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Highly Cited
1986
Highly Cited
1986
Parallel computers with tens of thousands of processors are typically programmed in a data parallel style, as opposed to the… Expand
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