超级计算的极限扩展：成本和能力
Extreme Scaling of Supercomputing with Stranded Power: Costs and Capabilities
摘要：
功耗（供应、热量、成本）和相关的碳排放（环境影响）是将超级计算扩展到Exascale及更高级别的关键挑战。我们建议利用搁浅的电力，对电网没有价值的可再生能源，用于扩展超级计算机，零碳云（ZCCloud），并表明搁浅的电力可以有效地用于扩展计算[1]。我们建立在这些结果与搁浅的权力，表征时间，地理和间隔属性的新分析。我们模拟生产超级计算工作负载，并对数据中心总拥有成本（TCO）进行建模，评估基于搁浅功率的超级计算的成本和功能。结果表明，ZCCloud方法在当今高成本地区具有成本效益。ZCCloud方法将TCO降低了21- 45%，并将成本效益提高了34%。我们研究了很多场景。随着更高的电力价格，更便宜的计算硬件和更高的系统功率密度，效益分别上升到55%，97%和116%。最后，我们研究了未来的极端规模系统，结果表明，超过万亿级，超过100兆瓦的预计功率需求使ZCCloud的成本降低了45%，对于固定预算，可实现的峰值PFLOPS增加了80%。
英文摘要：
Power consumption (supply, heat, cost) and associated carbon emissions (environmental impact) are increasingly critical challenges in scaling supercomputing to Exascale and beyond. We proposes to exploit stranded power, renewable energy that has no value to the power grid, for scaling supercomputers, Zero-Carbon Cloud (ZCCloud), and showing that stranded power can be employed effectively to expand computing [1]. We build on those results with a new analysis of stranded power, characterizing temporal, geographic, and interval properties. We simulate production supercomputing workloads and model datacenter total-cost-of-ownership (TCO), assessing the costs and capabilities of stranded-power based supercomputing. Results show that the ZCCloud approach is cost-effective today in regions with high cost power. The ZCCloud approach reduces TCO by 21-45%, and improves cost-effectiveness up to 34%. We study many scenarios. With higher power price, cheaper computing hardware and higher system power density, benefits rise to 55%, 97% and 116% respectively. Finally, we study future extreme-scale systems, showing that beyond terascale, projected power requirements in excess of 100MW make ZCCloud up to 45% lower cost, for a fixed budget, increase peak PFLOPS achievable by 80%.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
