Fair and Comprehensive Benchmarking of Machine Learning Processing Chips

Geoffrey W. Burr; SukHwan Lim; Boris Murmann; Rangharajan Venkatesan; Marian Verhelst

doi:10.1109/MDAT.2021.3063366

IEEE Design and Test

Review

31 May 2022

Fair and Comprehensive Benchmarking of Machine Learning Processing Chips

View publication

Abstract

This article provides an overview of benchmarking strategies at a different set of abstraction levels and related best practices in each, while working to also give an overall view of impact.

Conference paper

Incorporating excitation-induced dephasing into the Maxwell-Bloch numerical modeling of photon echoes

Geoffrey W. Burr, Todd L. Harris, et al.

Journal of Luminescence

Conference paper

Reducing circuit design complexity for neuromorphic machine learning systems based on Non-Volatile Memory arrays

Pritish Narayanan, Lucas L. Sanches, et al.

ISCAS 2017

Conference paper

Enhancing magnetic light emission with optical nanoantennas

Maria Sanz-Paz, Cyrine Ernandes, et al.

CLEO/Europe-EQEC 2019

Paper

Training fully connected networks with resistive memories: Impact of device failures

Louis P. Romero, Stefano Ambrogio, et al.

Faraday Discussions

View all publications

Abstract

Related

Incorporating excitation-induced dephasing into the Maxwell-Bloch numerical modeling of photon echoes

Reducing circuit design complexity for neuromorphic machine learning systems based on Non-Volatile Memory arrays

Enhancing magnetic light emission with optical nanoantennas

Training fully connected networks with resistive memories: Impact of device failures