TY - GEN

T1 - Bohrium

T2 - 28th IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2014

AU - Kristensen, Mads R.B.

AU - Lund, Simon A.F.

AU - Blum, Troels

AU - Skovhede, Kenneth

AU - Vinter, Brian

PY - 2014/11/27

Y1 - 2014/11/27

N2 - 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.

AB - 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.

KW - GPU

KW - Heterogeneous Computing

KW - High-Productivity

KW - Parallel Programming Environment

UR - http://www.scopus.com/inward/record.url?scp=84918776846&partnerID=8YFLogxK

U2 - 10.1109/IPDPSW.2014.44

DO - 10.1109/IPDPSW.2014.44

M3 - Article in proceedings

AN - SCOPUS:84918776846

T3 - Proceedings of the International Parallel and Distributed Processing Symposium, IPDPS

SP - 312

EP - 321

BT - Proceedings - IEEE 28th International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2014

PB - IEEE Computer Society Press

Y2 - 19 May 2014 through 23 May 2014

ER -