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CLEAR: A Holistic Figure-of-Merit for Post- and Predicting Electronic and Photonic-based Compute-system Evolution.
Sun, Shuai; Narayana, Vikram K; Miscuglio, Mario; Kimerling, Lionel C; El-Ghazawi, Tarek; Sorger, Volker J.
Afiliação
  • Sun S; Department of Electrical and Computer Engineering, George Washington University, 800 22nd Science & Engineering Hall, Washington, DC, 20052, USA.
  • Narayana VK; Department of Electrical and Computer Engineering, George Washington University, 800 22nd Science & Engineering Hall, Washington, DC, 20052, USA.
  • Miscuglio M; Department of Electrical and Computer Engineering, George Washington University, 800 22nd Science & Engineering Hall, Washington, DC, 20052, USA.
  • Kimerling LC; Department of Materials Science and Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue Cambridge, Cambridge, MA, 02139, USA.
  • El-Ghazawi T; Department of Electrical and Computer Engineering, George Washington University, 800 22nd Science & Engineering Hall, Washington, DC, 20052, USA.
  • Sorger VJ; Department of Electrical and Computer Engineering, George Washington University, 800 22nd Science & Engineering Hall, Washington, DC, 20052, USA. sorger@gwu.edu.
Sci Rep ; 10(1): 6482, 2020 04 16.
Article em En | MEDLINE | ID: mdl-32300139
Continuing demands for increased computing efficiency and communication bandwidth have pushed the current semiconductor technology to its limit. This led to novel technologies with the potential to outperform conventional electronic solutions such as photonic pre-processors or accelerators, electronic-photonic hybrid circuits, and neural networks. However, the efforts made to describe and predict the performance evolution of compute-performance fall short to accurately predict and thereby explain the actually observed development pace with time; that is all proposed metrics eventually deviate from their development trajectory after several years from when they were originally proposed. This discrepancy demands a figure-of-merit that includes a holistic set of driving forces of the compute-system evolution. Here we introduce the Capability-to-Latency-Energy-Amount-Resistance (CLEAR) metric encompassing synchronizing speed, energy efficiency, physical machine size scaling, and economic cost. We show that CLEAR is the only metric to accurately describe the historical compute-system development. We find that even across different technology options CLEAR matches the observed (post-diction) constant rate-of-growth, and also fits proposed future compute-system (prediction). Therefore, we propose CLEAR to serve as a guide to quantitatively predict required compute-system demands at a given time in the future.

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Estados Unidos