Future High Performance Computing Capabilities: Summary Report of the Advanced Scientific Computing Advisory Committee (ASCAC) Subcommittee
- Columbia Univ., New York, NY (United States)
- Georgia Inst. of Technology, Atlanta, GA (United States)
- Intel Corporation, Santa Clara, CA (United States)
- Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
- Sandia National Laboratories (SNL), Albuquerque, NM, and Livermore, CA (United States)
- Univ. of Notre Dame, IN (United States)
- Information Sciences Inst., CA (United States)
- Tokyo Tech. (Japan)
- Google (United States)
The ASCAC Subcommittee on Future High Performance Computing (HPC) Capabilities has reviewed opportunities and challenges related to the most promising technologies that are currently planned for the post-exascale (2020's) and post-Moore (2030's and beyond) timeframes. We briefly summarize in this report the key findings and recommendations from this review, from the perspective of planning and research directions that need to be given priority to prepare for the very significant challenges that await us in the post-Moore computing era. An overarching concern that emerged from the subcommittee's deliberations is that DOE has lost considerable momentum in funding and sustaining a research pipeline in the applied math and computer science areas that should have been the "seed corn" for preparing for these future challenges, and it is therefore critical to correct this gap as soon as possible. While the subcommittee understands the paramount importance of DOE's commitment to deliver exascale capabilities, we believe that it is essential for DOE ASCR to fund research and development that looks beyond the Exascale Computing Project (ECP) horizon so as to ensure our nation's continued leadership in HPC and we were glad to learn about the ASCAC exascale transition subcommittee in this regard.
- Research Organization:
- USDOE Office of Science (SC) (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)
- OSTI ID:
- 1570693
- Country of Publication:
- United States
- Language:
- English
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