Energy Efficiency Scaling for 2 Decades (EES2) Roadmap for Computing
In response to the looming crisis in global energy consumption required for advanced computing applications, the United States Department of Energy (DOE) Advanced Materials and Manufacturing Technology Office (AMMTO) is leading a multi-organizational effort to define a roadmap for energy efficiency scaling for two decades (EES2) with the aim to reduce energy use in all aspects of computation by more than a factor of 1000 in two decades. By July of 2024, over 60 organizations representing industry, academia, and the national laboratories have pledged to work in various aspects of research and development to enable energy efficiency in computing including in the development of the EES2 roadmap, with an initial public release in 2024 as the first phase of an ongoing commitment to energy-efficient and sustainable computation.
Authors
- James C. Booth (ORCID: https://orcid.org/0000-0002-0256-653X)
- Elliot Taylor
- Sudha Misra (ORCID: https://orcid.org/0000-0002-5218-2753)
- Florian Musso
- Tao Wei (ORCID: https://orcid.org/0000-0001-8693-0695)
- Prashant Nagapurkar (ORCID: https://orcid.org/0000-0002-8540-6717)
- Moinuddin Ahmed (ORCID: https://orcid.org/0000-0003-2916-5821)
- Kentaro Shimizu (ORCID: https://orcid.org/0000-0003-0631-9365)
- N. Li
- Amirkoushyar Ziabari (ORCID: https://orcid.org/0000-0003-4776-457X)
- Shyam Shankar (ORCID: https://orcid.org/0000-0002-1311-9508)
- Sean E. Shaheen (ORCID: https://orcid.org/0000-0002-7179-9230)
- Colin Green (ORCID: https://orcid.org/0000-0003-3459-6298)
- T. Kaarsberg
- Y. Zhang
- J. L. Luo (ORCID: https://orcid.org/0000-0002-0051-7726)
- A.J. Bhavnagarwala
- Emre Salman (ORCID: https://orcid.org/0000-0001-6538-6803)
- I‐Cheng Lu (ORCID: https://orcid.org/0000-0001-6643-1071)
- A. K. Petford‐Long (ORCID: https://orcid.org/0000-0002-3154-8090)
- Dhireesha Kudithipudi (ORCID: https://orcid.org/0000-0003-4462-5224)
- Daniel B. Gopman (ORCID: https://orcid.org/0000-0003-4172-8113)
- Rashmi Aggarwal (ORCID: https://orcid.org/0000-0002-8706-6680)
- Jayasimha Atulasimha (ORCID: https://orcid.org/0000-0002-5681-0884)
- Joshua B. Ballard (ORCID: https://orcid.org/0009-0006-5207-1005)
- Tom McDonald (ORCID: https://orcid.org/0000-0002-9606-6420)
- Paul Sharps (ORCID: https://orcid.org/0000-0002-9400-5392)
- B. Hirano
- Yong Chen (ORCID: https://orcid.org/0000-0001-8824-7187)
- R. W. L. Jones (ORCID: https://orcid.org/0000-0002-6427-3513)
- Wei Huang (ORCID: https://orcid.org/0000-0001-6340-422X)
- P. Fischer (ORCID: https://orcid.org/0009-0007-7797-2851)
- A. Paramonov
- T. Shah
- S. Pawłowski
- Nancy Johnson
- C. Gotama
- J. Baniecki
Institutions
- Micron (United States) (US)
- Argonne National Laboratory (US)
- Oak Ridge National Laboratory (US)
- National Institute of Standards and Technology (US)
- Intel (United States) (US)
- Duke University (US)
- Virginia Commonwealth University (US)
- University of Colorado Boulder (US)
- Energetics (United States) (US)
- Zyvex (United States) (US)
- Infineon Technologies (United States) (US)
- The University of Texas at San Antonio (US)
- Stony Brook University (US)
Publication Details
- Published
- 2024-09-23
- DOI
- https://doi.org/10.1109/hpec62836.2024.10938468
- Citations
- 3
- Primary Topic
- Parallel Computing and Optimization Techniques
- Type
- article
- Field-Weighted Citation Impact
- 1.47