NeuroMeter: An Integrated Power, Area, and Timing Modeling Framework for Machine Learning Accelerators Industry Track Paper

2021 IEEE International Symposium on High-Performance Computer Architecture (HPCA)(2021)

Cited 18|Views63
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Abstract
As Machine Learning (ML) becomes pervasive in the era of artificial intelligence, ML specific tools and frameworks are required for architectural research. This paper introduces NeuroMeter, an integrated power, area, and timing modeling framework for ML accelerators. NeuroMeter models the detailed architecture of ML accelerators and generates a fast and accurate estimation on power, area, and chip...
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Key words
Analytical models,Runtime,Accelerator architectures,Tools,Energy efficiency,Timing,Task analysis
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