Bohrium: A virtual machine approach to portable parallelism

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

  • Mads R.B. Kristensen
  • Simon A.F. Lund
  • Troels Blum
  • Kenneth Skovhede
  • Brian Vinter

In this paper we introduce, Bohrium, a runtime-system for mapping vector operations onto a number of different hardware platforms, from simple multi-core systems to clusters and GPU enabled systems. In order to make efficient choices Bohrium is implemented as a virtual machine that makes runtime decisions, rather than a statically compiled library, which is the more common approach. In principle, Bohrium can be used for any programming language but for now, the supported languages are limited to Python, C++ and the. Net framework, e.g. C# and F#. The primary success criteria are to maintain a complete abstraction from low-level details and to provide efficient code execution across different, current and future, processors. We evaluate the presented design through a setup that targets a multi-core CPU, an eight-node Cluster, and a GPU, all preliminary prototypes. The evaluation includes three well-known benchmark applications, Black Sholes, Shallow Water, and N-body, implemented in C++, Python, and C# respectively.

OriginalsprogEngelsk
TitelProceedings - IEEE 28th International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2014
Antal sider10
ForlagIEEE Computer Society Press
Publikationsdato27 nov. 2014
Sider312-321
Artikelnummer6969406
ISBN (Elektronisk)9780769552088
DOI
StatusUdgivet - 27 nov. 2014
Begivenhed28th IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2014 - Phoenix, USA
Varighed: 19 maj 201423 maj 2014

Konference

Konference28th IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2014
LandUSA
ByPhoenix
Periode19/05/201423/05/2014
SponsorIEEE Computer Society Technical Committee on Parallel Processing
NavnProceedings of the International Parallel and Distributed Processing Symposium, IPDPS
ISSN1530-2075

ID: 229371955