Abstract
This paper reports on the development of an MPI/OpenCL implementation of LU, an application-level benchmark from the NAS Parallel Benchmark Suite. An account of the design decisions addressed during the development of this code is presented, demonstrating the importance of memory arrangement and work-item/work-group distribution strategies when applications are deployed on different device types. The resulting platform-agnostic, single source application is benchmarked on a number of different architectures, and is shown to be 1.3-1.5× slower than native FORTRAN 77 or CUDA implementations on a single node and 1.3-3.1× slower on multiple nodes. We also explore the potential performance gains of OpenCL's device fissioning capability, demonstrating up to a 3× speed-up over our original OpenCL implementation.
| Original language | English |
|---|---|
| Pages (from-to) | 1439-1450 |
| Number of pages | 12 |
| Journal | Journal of Parallel and Distributed Computing |
| Volume | 73 |
| Issue number | 11 |
| DOIs | |
| Publication status | Published - 2013 |
Bibliographical note
Funding Information:Access to the LLNL Open Computing Facility is made possible through collaboration with the UK Atomic Weapons Establishment under grants CDK0660 (The Production of Predictive Models for Future Computing Requirements) and CDK0724 (AWE Technical Outreach Programme). The HPC performance benchmarking research is also supported jointly by AWE and the TSB Knowledge Transfer Partnership grant no. KTP006740 .
Funding Information:
This work is sponsored in part by The Royal Society through their Industry Fellowship Scheme ( IF090020/AM ).
Keywords
- GPU computing
- High performance computing
- Many-core computing
- OpenCL
- Optimisation
ASJC Scopus subject areas
- Software
- Theoretical Computer Science
- Hardware and Architecture
- Computer Networks and Communications
- Artificial Intelligence