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dc.contributor.author
Ziogas, Alexandros N.
dc.contributor.author
Ben-Nun, Tal
dc.contributor.author
Schneider, Timo
dc.contributor.author
Hoefler, Torsten
dc.date.accessioned
2021-06-17T05:27:05Z
dc.date.available
2021-06-17T02:50:36Z
dc.date.available
2021-06-17T05:27:05Z
dc.date.issued
2021-06
dc.identifier.isbn
978-1-4503-8335-6
en_US
dc.identifier.other
10.1145/3447818.3460360
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/490045
dc.description.abstract
Python, already one of the most popular languages for scientific computing, has made significant inroads in High Performance Computing (HPC). At the center of Python's ecosystem is NumPy, an efficient implementation of the multi-dimensional array (tensor) structure, together with basic arithmetic and linear algebra. Compared to traditional HPC languages, the relatively low performance of Python and NumPy has spawned significant research in compilers and frameworks that decouple Python's compact representation from the underlying implementation. However, it is challenging to compare language compatibility and performance among different frameworks and architectures without a standard set of benchmarks and metrics. To that end, we introduce NPBench, a set of NumPy code samples representing a large variety of HPC applications. We use NPBench to test popular NumPy-accelerating compilers and frameworks on a variety of metrics. NPBench will guide both end-users and framework developers focusing on performance and will drive further use of Python in the high-performance scientific domains.
en_US
dc.language.iso
en
en_US
dc.publisher
ACM
en_US
dc.subject
High Performance Computing
en_US
dc.subject
Benchmark
en_US
dc.subject
Python
en_US
dc.subject
NumPy
en_US
dc.title
NPBench: a benchmarking suite for high-performance NumPy
en_US
dc.type
Conference Paper
dc.date.published
2021-06-03
ethz.book.title
ICS '21: Proceedings of the ACM International Conference on Supercomputing
en_US
ethz.pages.start
63
en_US
ethz.pages.end
74
en_US
ethz.event
35th ACM International Conference on Supercomputing (ICS-2021)
en_US
ethz.event.location
Online
en_US
ethz.event.date
June 14-18, 2021
en_US
ethz.identifier.scopus
ethz.publication.place
New York, NY
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02150 - Dep. Informatik / Dep. of Computer Science::02666 - Institut für Hochleistungsrechnersysteme / Inst. f. High Performance Computing Syst::03950 - Hoefler, Torsten / Hoefler, Torsten
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02150 - Dep. Informatik / Dep. of Computer Science::02666 - Institut für Hochleistungsrechnersysteme / Inst. f. High Performance Computing Syst::03950 - Hoefler, Torsten / Hoefler, Torsten
ethz.date.deposited
2021-06-17T02:50:45Z
ethz.source
SCOPUS
ethz.eth
yes
en_US
ethz.availability
Metadata only
en_US
ethz.rosetta.installDate
2021-06-17T05:27:11Z
ethz.rosetta.lastUpdated
2022-03-29T08:49:32Z
ethz.rosetta.versionExported
true
ethz.COinS
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