Zero-carbon cloud is exploring a new approach to computing that leverages recent advances in information technology (cloud computing, data center automation, system-focused analytics, etc.), and the advance of renewable energy generation to create truly "green" computing. The goal is zero incremental carbon emissions. A key aspect of this approach is the use of "stranded power", that is uneconomic due to geographic and temporal mismatching, and delivery of volatile computing services. The RIVER system is a flexible NSF-funded testbed for exploring volatility, power, energy, variability, and reliability.
- Fan Yang and Andrew A. Chien, "Scaling Supercomputing with Stranded Power: Costs and Capabilities", submitted for publication. (also available as University of Chicago Technical Report 2016-04, January 2016, Techreport link)
- Kibaek Kim, Fan Yang, Victor Zavala, and Andrew A. Chien, "Data Centers as Dispatchable Loads to Harness Stranded Power", to appear in IEEE Transactions on Sustainable Energy, DOI 10.1109/TSTE.2016.2593607. (submitted version from March 2016 is available from Arxiv)
- Fan Yang and Andrew A. Chien, "ZCCloud: Exploring Wasted Green Power for High-Performance Computing", in the International Parallel and Distributed Processing Symposium (IPDPS), May 2016. (also University of Chicago Technical Report 2015-09, October 2015. Techreport Link)
- Mingzhe Hao, Gokul Soundararajan, Deepak Kenchammana-Hosekote, Andrew A. Chien, and Haryadi S. Gunawi, "The Tail at Store: A Revelation from Millions of Hours of Disk and SSD Deployments", in Proceedings of the USENIX Filesystems and Storage Technologies (FAST), February 2016, Santa Clara, CA.
- Andrew A. Chien, Rich Wolski, and Fan Yang, "Dispatchable Computational Loads to Tolerate Renewable Power Generation Variability", Energy Policy Research Conference, September 2015, Denver, Colorado. In Electricity Journal, October 2015.
- Andrew A. Chien, Rich Wolski, and Fan Yang, "Zero-carbon Cloud: A Volatile Resource for High Performance Computing", Proceedings of the IEEE Workshop on Sustainable High-Performance Computing, October 2015, Liverpool, England.
This work was supported by the National Science Foundation under Award CNS-1405959. We also gratefully acknowledge support from Keysight, HP, and Samsung.