Data-parallel flattening by expansion

Martin Elsman, Troels Henriksen, Niels Gustav Westphal Serup

2 Citationer (Scopus)

Abstract

We present a higher-order programmer-level technique for compiling particular kinds of irregular data-parallel problems to parallel hardware. The technique, which we have named “flattening-by-expansion” builds on a number of segmented data-parallel operations but is itself implemented as a higher-order generic function, which makes it useful for many irregular problems. Concretely, the implementation is given in Futhark and we demonstrate the usefulness of the functionality for a number of irregular problems and show that, in practice, the irregular problems are compiled to efficient parallel code that can be executed on GPUs. The technique is useful in any data-parallel language that provides a key set of primitives.

OriginalsprogEngelsk
TitelARRAY 2019 - Proceedings of the 6th ACM SIGPLAN International Workshop on Libraries, Languages and Compilers for Array Programming, co-located with PLDI 2019
RedaktørerJeremy Gibbons
Antal sider11
ForlagAssociation for Computing Machinery, Inc.
Publikationsdato8 jun. 2019
Sider14-24
ISBN (Elektronisk)9781450367172
DOI
StatusUdgivet - 8 jun. 2019
Begivenhed6th ACM SIGPLAN International Workshop on Libraries, Languages and Compilers for Array Programming, ARRAY 2019, co-located with PLDI 2019 - Phoenix, USA
Varighed: 22 jun. 2019 → …

Konference

Konference6th ACM SIGPLAN International Workshop on Libraries, Languages and Compilers for Array Programming, ARRAY 2019, co-located with PLDI 2019
Land/OmrådeUSA
ByPhoenix
Periode22/06/2019 → …
SponsorACM SIGPLAN
NavnProceedings of the ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI)

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