Skip to search formSkip to main content
You are currently offline. Some features of the site may not work correctly.

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
Wikipedia

Related topics

Related topics

42 relations
APLActive messageAlliant Computer SystemsApache Flink
Expand

Broader (1)

Parallel computing

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2018
Highly Cited
2018
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… Expand
  • table 1
  • table 2
  • figure 1
  • figure 2
  • figure 3
Is this relevant?
Highly Cited
2013
Highly Cited
2013
Enhancing data parallelism for Ant Colony Optimization on GPUs
Graphics Processing Units (GPUs) have evolved into highly parallel and fully programmable architecture over the past five years… Expand
  • figure 1
  • figure 3
  • figure 2
  • figure 4
  • figure 5
Is this relevant?
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… Expand
  • figure 2
  • figure 1
  • figure 3
  • figure 4
  • figure 6
Is this relevant?
2011
2011
Data and task parallelism in ILP using MapReduce
Nearly two decades of research in the area of Inductive Logic Programming (ILP) have seen steady progress in clarifying its… Expand
  • figure 1
  • figure 3
  • figure 5
  • figure 6
  • figure 7
Is this relevant?
Highly Cited
2009
Highly Cited
2009
How much parallelism is there in irregular applications?
Irregular programs are programs organized around pointer-based data structures such as trees and graphs. Recent investigations by… Expand
  • figure 1
  • figure 2
  • figure 6
  • figure 5
  • figure 7
Is this relevant?
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… Expand
  • figure 2
  • figure 10
  • figure 11
Is this relevant?
Highly Cited
2006
Highly Cited
2006
Accelerator: using data parallelism to program GPUs for general-purpose uses
GPUs are difficult to program for general-purpose uses. Programmers can either learn graphics APIs and convert their applications… Expand
  • figure 1
  • table 1
  • table 2
  • table 3
  • table 4
Is this relevant?
Highly Cited
2001
Highly Cited
2001
Preface
  • Frank Müller
  • IEEE International Symposium on Parallel…
  • 2001
    • Corpus ID: 29979536
Cognitive Radio Networks (CRNs) are the key enabling technology for realizing Opportunistic Spectrum Access (OSA) to alleviate… Expand
  • figure 6
  • table 3
  • table 4
  • table 3
  • table 4
Is this relevant?
Highly Cited
2000
Highly Cited
2000
Exploiting superword level parallelism with multimedia instruction sets
Increasing focus on multimedia applications has prompted the additionof multimedia extensions to most existing general purpose… Expand
  • figure 2-1
  • figure 3-1
  • table 3.1
  • table 3.2
  • figure 4-1
Is this relevant?
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… Expand
  • figure 1
  • figure 2
  • table I
  • figure 3
  • figure 4
Is this relevant?
By clicking accept or continuing to use the site, you agree to the terms outlined in our Privacy Policy, Terms of Service, and Dataset License
ACCEPT & CONTINUE