Quantum;
zettascale;
deep learning;
clouds;
HPC myths;
D O I:
10.1177/10943420231166608
中图分类号:
TP3 [计算技术、计算机技术];
学科分类号:
0812 ;
摘要:
In this thought-provoking article, we discuss certain myths and legends that are folklore among members of the high-performance computing community. We gathered these myths from conversations at conferences and meetings, product advertisements, papers, and other communications such as tweets, blogs, and news articles within and beyond our community. We believe they represent the zeitgeist of the current era of massive change, driven by the end of many scaling laws such as Dennard scaling and Moore's law. While some laws end, new directions are emerging, such as algorithmic scaling or novel architecture research. Nevertheless, these myths are rarely based on scientific facts, but rather on some evidence or argumentation. In fact, we believe that this is the very reason for the existence of many myths and why they cannot be answered clearly. While it feels like there should be clear answers for each, some may remain endless philosophical debates, such as whether Beethoven was better than Mozart. We would like to see our collection of myths as a discussion of possible new directions for research and industry investment.
机构:
Univ Penn, Dept Med, Div Translat Med & Human Genet, Philadelphia, PA 19104 USAUniv Penn, Dept Med, Div Translat Med & Human Genet, Philadelphia, PA 19104 USA
Verma, Anurag
Huffman, Jennifer
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机构:
VA Boston Healthcare Syst, Boston, MA USAUniv Penn, Dept Med, Div Translat Med & Human Genet, Philadelphia, PA 19104 USA
Huffman, Jennifer
Torkamani, Ali
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机构:
Scripps Res Inst, Dept Integrat Struct & Comp Biol, La Jolla, CA USAUniv Penn, Dept Med, Div Translat Med & Human Genet, Philadelphia, PA 19104 USA
Torkamani, Ali
Madduri, Ravi
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机构:
Argonne Natl Lab, Data Sci & Learning Div, Lemont, IL USAUniv Penn, Dept Med, Div Translat Med & Human Genet, Philadelphia, PA 19104 USA