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Title: Large-Scale and Extreme-Scale Computing with Stranded Green Power: Opportunities and Costs

Power consumption and associated carbon emissions are increasingly critical challenges for large-scale computing. Recent research proposes exploiting stranded power-uneconomic renewable power-for green supercomputing in a system called Zero-Carbon Cloud (ZCCloud). These efforts studied production supercomputing workloads on stranded-power based computing resources, demonstrating their achievable productivity. We explore economic viability of stranded-power based supercomputing, using three datacenter total-cost-of-ownership (TOO) models to study cost-effectiveness. These studies show that ZCCloud's approach can be cost-effective in the USA today, and is even more attractive in regions with higher power prices (e.g., Japan, Germany), achieving cost advantages as large as 50 percent. Environmental and power-grid benefits are a further advantage. We also explore the sensitivity of these results to changes in hardware TOO; cheaper hardware or longer lifetimes magnify the attractiveness of stranded-power based approaches, yielding advantages as large as 91 percent. These results are robust across different TCO models. Lastly, we study extreme-scale supercomputers ( >100 MW), finding stranded-power can increase peak capability per cost by as much as 80 percent.
Authors:
ORCiD logo [1] ; ORCiD logo [2]
  1. The Univ. of Chicago, Chicago, IL (United States)
  2. The Univ. of Chicago, Chicago, IL (United States); Argonne National Lab. (ANL), Lemont, IL (United States)
Publication Date:
Grant/Contract Number:
AC02-06CH11357
Type:
Accepted Manuscript
Journal Name:
IEEE Transactions on Parallel and Distributed Systems
Additional Journal Information:
Journal Volume: 29; Journal Issue: 5; Journal ID: ISSN 1045-9219
Publisher:
IEEE
Research Org:
Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Org:
National Science Foundation (NSF); USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21)
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; 32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; supercomputing; cost; extreme scale; power grid; stranded power
OSTI Identifier:
1464632

Yang, Fan, and Chien, Andrew A. Large-Scale and Extreme-Scale Computing with Stranded Green Power: Opportunities and Costs. United States: N. p., Web. doi:10.1109/TPDS.2017.2782677.
Yang, Fan, & Chien, Andrew A. Large-Scale and Extreme-Scale Computing with Stranded Green Power: Opportunities and Costs. United States. doi:10.1109/TPDS.2017.2782677.
Yang, Fan, and Chien, Andrew A. 2017. "Large-Scale and Extreme-Scale Computing with Stranded Green Power: Opportunities and Costs". United States. doi:10.1109/TPDS.2017.2782677. https://www.osti.gov/servlets/purl/1464632.
@article{osti_1464632,
title = {Large-Scale and Extreme-Scale Computing with Stranded Green Power: Opportunities and Costs},
author = {Yang, Fan and Chien, Andrew A.},
abstractNote = {Power consumption and associated carbon emissions are increasingly critical challenges for large-scale computing. Recent research proposes exploiting stranded power-uneconomic renewable power-for green supercomputing in a system called Zero-Carbon Cloud (ZCCloud). These efforts studied production supercomputing workloads on stranded-power based computing resources, demonstrating their achievable productivity. We explore economic viability of stranded-power based supercomputing, using three datacenter total-cost-of-ownership (TOO) models to study cost-effectiveness. These studies show that ZCCloud's approach can be cost-effective in the USA today, and is even more attractive in regions with higher power prices (e.g., Japan, Germany), achieving cost advantages as large as 50 percent. Environmental and power-grid benefits are a further advantage. We also explore the sensitivity of these results to changes in hardware TOO; cheaper hardware or longer lifetimes magnify the attractiveness of stranded-power based approaches, yielding advantages as large as 91 percent. These results are robust across different TCO models. Lastly, we study extreme-scale supercomputers ( >100 MW), finding stranded-power can increase peak capability per cost by as much as 80 percent.},
doi = {10.1109/TPDS.2017.2782677},
journal = {IEEE Transactions on Parallel and Distributed Systems},
number = 5,
volume = 29,
place = {United States},
year = {2017},
month = {12}
}