MLPerf Power: Benchmarking the Energy Efficiency of Machine Learning Systems from Microwatts to Megawatts for Sustainable AI

Rapid adoption of machine learning (ML) technologies has led to a surge in power consumption across diverse systems, from tiny IoT devices to massive datacenter clusters. Benchmarking the energy efficiency of these systems is crucial for optimization, but presents novel challenges due to the variety...

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Bibliographic Details

Main Authors:	Tschand, Arya, Rajan, Arun Tejusve Raghunath, Idgunji, Sachin, Ghosh, Anirban, Holleman, Jeremy, Kiraly, Csaba, Ambalkar, Pawan, Borkar, Ritika, Chukka, Ramesh, Cockrell, Trevor, Curtis, Oliver, Fursin, Grigori, Hodak, Miro, Kassa, Hiwot, Lokhmotov, Anton, Miskovic, Dejan, Pan, Yuechao, Manmathan, Manu Prasad, Raymond, Liz, John, Tom St, Suresh, Arjun, Taubitz, Rowan, Zhan, Sean, Wasson, Scott, Kanter, David, Reddi, Vijay Janapa
Format:	Journal Article
Language:	English
Published:	15-10-2024
Subjects:	Computer Science - Distributed, Parallel, and Cluster Computing Computer Science - Hardware Architecture Computer Science - Learning
Online Access:	Get full text
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