The DOI matches its Crossref record.
OpenCL: A Parallel Programming Standard for Heterogeneous Computing Systems
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OpenCL provides a higher abstraction programming framework and enables the programmer to write programs which are portable across a wide variety of processing units, although it may not achieve the highest possible performance on a PU.
“It provides a higher abstraction programming framework and hence, it enables the programmer to write programs which are portable across wide variety of processing units, although it may not be able to achieve the highest possible performance on a PU.”
From A Survey of CPU-GPU Heterogeneous Computing Techniques (2015) · cites this paper as Stone et al. 2010
OpenCL is an open standard and has been adopted by several vendors.
“OpenCL [Stone et al. 2010] is an open standard and has been adopted by several vendors.”
From A Survey of CPU-GPU Heterogeneous Computing Techniques (2015) · cites this paper as Stone et al. 2010
OpenCL facilitates both task-parallelism and data-parallelism.
“It facilitates both task-parallelism and data-parallelism.”
From A Survey of CPU-GPU Heterogeneous Computing Techniques (2015) · cites this paper as Stone et al. 2010
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Research works printed but not linked: 11
- 10.1109/SC.2008.5217926 · DOI
- 10.1109/MCSE.2009.204 · DOI
- 10.1073/pnas.181342398 · DOI
- 10.1145/1365490.1365500 · DOI
- 10.1016/0263-7855(96)00018-5 · DOI · Paper page
- 2008, OpenCL Specification Version 1 0
- 10.1145/1513895.1513897 · DOI
- 10.1002/jcc.20829 · DOI
- 10.1109/MCSE.2009.144 · DOI
- 10.1109/HPCA.2005.26 · DOI
- 10.1109/MCSE.2010.4 · DOI
Cited by
Sorted by citations
A Survey of CPU-GPU Heterogeneous Computing Techniques
Mittal, S., & Vetter, J. S. (2015) · ACM Computing Surveys · doi:10.1145/2788396 · Cited by 568
The transformational role of GPU computing and deep learning in drug discovery
Pandey, M., Fernandez, M., Gentile, F., Isayev, O., Tropsha, A., Stern, A. C., & Cherkasov, A. (2022) · Nature Machine Intelligence · doi:10.1038/s42256-022-00463-x · Cited by 255
Metadata
- Authors
- Stone, J. E., Gohara, D., & Shi, G.
- Venue
- Computing in Science & Engineering
- Published
- 2010-05
- Volume
- 12
- Issue
- 3
- Pages
- 66-73
- ISSN
- 1521-9615
- PMC
- PMC2964860
- Cited by
- 1,086
- References
- 0
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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