Results from a second longitudinal survey of academic research computing and data center usage: expenditures, utilization patterns, and approaches to return on investment
被引:3
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作者:
论文数: 引用数:
h-index:
机构:
Geva, Sharon Broude
[1
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Chalker, Alan
论文数: 0引用数: 0
h-index: 0
机构:
Ohio Supercomp Ctr, Columbus, OH USAUniv Michigan, Ann Arbor, MI 48109 USA
Chalker, Alan
[2
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Hillegas, Curtis W.
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机构:
Princeton Univ, Princeton, NJ 08544 USAUniv Michigan, Ann Arbor, MI 48109 USA
Hillegas, Curtis W.
[3
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Petravick, Donald
论文数: 0引用数: 0
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机构:
Univ Illinois, Chicago, IL USAUniv Michigan, Ann Arbor, MI 48109 USA
Petravick, Donald
[4
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Sill, Alan
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Texas Tech Univ, Lubbock, TX 79409 USAUniv Michigan, Ann Arbor, MI 48109 USA
Sill, Alan
[5
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Stewart, Craig A.
论文数: 0引用数: 0
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机构:
Indiana Univ, Bloomington, IN USA
Univ Illinois, Champaign, IL USAUniv Michigan, Ann Arbor, MI 48109 USA
cloud computing;
HPC;
research computing;
data-centric computing;
return on investment;
D O I:
10.1145/3437359.3465589
中图分类号:
TP31 [计算机软件];
学科分类号:
081202 ;
0835 ;
摘要:
Availability of cloud-based resource delivery modes is transforming many areas of computing. Academic research computing and data (RCD) support largely remains based on on-premises delivery and has adopted commercial clouds more slowly than the private sector for a variety of stated reasons including factors related to cost efficiency, return on investment, institutional requirements, high costs for bulk commercial cloud computing usage, and funding patterns. Other factors involved in selection of computing resource delivery modes include capabilities and applications that are available only in or best adapted to specific computing environments. It is important for the higher education and research communities to be able to learn from each other as institutions and individuals to make optimum use of appropriate modes of delivery for RCD resources. This paper reports an overview of results from the second annual community-wide survey conducted by the Coalition for Advanced Scientific Computation on patterns of funding, usage, and return on investment for academic research computing and data resources. The results show that on-premises delivery continues to remain the preferred mode for RCD resources for most responding institutions as found in the first survey, but that commercial cloud usage is beginning to be reported for production use by a small number of respondents to the survey. Reasons for these preferences are further explored in the survey and initial high-level results are reported here.