Sierra Center of Excellence: Lessons Learned
- Vulcan Inc., Seattle, WA (United States)
- Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
- IBM Cambridge Research Center, Cambridge, MA (United States)
- IBM Research, Yorktown Heights, NY (United States)
The introduction of heterogeneous computing via GPUs from the Sierra architecture represented a significant shift in direction for computational science at Lawrence Livermore National Laboratory (LLNL), and therefore required significant preparation. Over the last five years, the Sierra Center of Excellence (CoE) has brought employees with specific expertise from IBM and NVIDIA together with LLNL in a concentrated effort to prepare applications, system software, and tools for the Sierra supercomputer. This article shares the process we applied for the CoE and documents lessons learned during the collaboration, with the hope that others will be able to learn from both our success and intermediate setbacks. We describe what we have found to work for the management of such a collaboration and best practices for algorithms and source code, system configuration and software stack, tools, and application performance.
- Research Organization:
- Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
- Sponsoring Organization:
- USDOE National Nuclear Security Administration (NNSA)
- Grant/Contract Number:
- AC52-07NA27344
- OSTI ID:
- 1631911
- Report Number(s):
- LLNL-JRNL-789080; 987415
- Journal Information:
- IBM Journal of Research and Development, Vol. 64, Issue 3/4; ISSN 0018-8646
- Publisher:
- IEEECopyright Statement
- Country of Publication:
- United States
- Language:
- English
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