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

Yang, Fan; Chien, Andrew A.

doi:10.1109/TPDS.2017.2782677

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

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Abstract

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:

^[1];

^[2]

The Univ. of Chicago, Chicago, IL (United States)
The Univ. of Chicago, Chicago, IL (United States); Argonne National Lab. (ANL), Lemont, IL (United States)

Publication Date:: Tue Dec 12 00:00:00 EST 2017

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)

OSTI Identifier:: 1464632

Grant/Contract Number:: AC02-06CH11357

Resource 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

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

Citation Formats


                    Yang, Fan, and Chien, Andrew A. Large-Scale and Extreme-Scale Computing with Stranded Green Power: Opportunities and Costs.  United States: N. p., 2017. 
Web.  doi:10.1109/TPDS.2017.2782677.

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                    Yang, Fan, & Chien, Andrew A. Large-Scale and Extreme-Scale Computing with Stranded Green Power: Opportunities and Costs.  United States.  https://doi.org/10.1109/TPDS.2017.2782677

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                    Yang, Fan, and Chien, Andrew A. Tue .  
"Large-Scale and Extreme-Scale Computing with Stranded Green Power: Opportunities and Costs".  United States.  https://doi.org/10.1109/TPDS.2017.2782677.  https://www.osti.gov/servlets/purl/1464632.

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@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         = {Tue Dec 12 00:00:00 EST 2017},

  month        = {Tue Dec 12 00:00:00 EST 2017}

}

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