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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… 
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Broader (1)

Parallel computing

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2019
Highly Cited
2019
Measuring the Effects of Data Parallelism on Neural Network Training
Recent hardware developments have dramatically increased the scale of data parallelism available for neural network training… 
Highly Cited
2011
Highly Cited
2011
The tao of parallelism in algorithms
For more than thirty years, the parallel programming community has used the dependence graph as the main abstraction for… 
Highly Cited
2010
Highly Cited
2010
Parallelized Stochastic Gradient Descent
With the increase in available data parallel machine learning has become an increasingly pressing problem. In this paper we… 
Highly Cited
2010
Highly Cited
2010
Twister: a runtime for iterative MapReduce
MapReduce programming model has simplified the implementation of many data parallel applications. The simplicity of the… 
Highly Cited
2009
Highly Cited
2009
OpenCL – The Open Standard for Parallel Programming of Heterogeneous Systems
  • J. Xu
  • 2009
  • Corpus ID: 16804330
Today's computers are becoming increasing reliant on parallel computing. Processors are shipping with multiple cores, and new… 
Highly Cited
2007
Highly Cited
2007
Optimistic parallelism requires abstractions
Irregular applications, which manipulate large, pointer-based data structures like graphs, are difficult to parallelize manually… 
Highly Cited
2005
Highly Cited
2005
ParaView: An End-User Tool for Large-Data Visualization
Highly Cited
1998
Highly Cited
1998
Parallel computer architecture - a hardware / software approach
The most exciting development in parallel computer architecture is the convergence of traditionally disparate approaches on a… 
Highly Cited
1993
Highly Cited
1993
Maximizing Loop Parallelism and Improving Data Locality via Loop Fusion and Distribution
Loop fusion is a program transformation that merges multiple loops into one. It is effective for reducing the synchronization… 
Highly Cited
1986
Highly Cited
1986
Data parallel algorithms
Parallel computers with tens of thousands of processors are typically programmed in a data parallel style, as opposed to the… 
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