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Data parallelism

Data parallelism is parallelization across multiple processors in parallel computing environments. It focuses on distributing the data across different nodes, which operate on the data in parallel. It can be applied on regular data structures like arrays and matrices by working on each element in parallel. It contrasts to task parallelism as another form…

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Mixed data and task parallelism

Data parallel programming environments

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Data parallelism

Nodes40
Edges39
Triples24
Avg. degree1.95
Density0.05
Components1

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Data parallelism

Top relations

related to history · 15
Data parallelism → Concurrency, Connection Machines, Data Parallel Haskell, Exploitation, Futhark, GPUs, In, Most, NESL, Solomon, The, The Solomon, These, This, Today
has application · 3
Data parallelism → Data, Driving, Sciences
related to Description · 3
Data parallelism → For, In, SIMD

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Important terminology

data parallel parallelism task time processors programming units matrix array computing processing addition sequential execution elements mixed applications model multiplication

Entity relationships Subject–Predicate–Object triples

SubjectPredicateObjectConfidenceSrc
Data Parallel Haskellinstance ofThis work was continued by other languages0.80text
Futharkinstance ofThis work was continued by other languages0.80text
although arbitrary nested data parallelism is not widely available in current data-parallel programming languagesinstance ofThis work was continued by other languages0.80text
Data parallelismhas applicationData0.60section
Data parallelismhas applicationSciences0.60section
Data parallelismhas applicationDriving0.60section
Data parallelismrelated to DescriptionIn0.60section
Data parallelismrelated to DescriptionSIMD0.60section
Data parallelismrelated to DescriptionFor0.60section
Data parallelismrelated to historyExploitation0.60section
Data parallelismrelated to historySolomon0.60section
Data parallelismrelated to historyThe Solomon0.60section

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