Search Results for author: David Patterson

Found 8 papers, 4 papers with code

Carbon Emissions and Large Neural Network Training

no code implementations21 Apr 2021 David Patterson, Joseph Gonzalez, Quoc Le, Chen Liang, Lluis-Miquel Munguia, Daniel Rothchild, David So, Maud Texier, Jeff Dean

To help reduce the carbon footprint of ML, we believe energy usage and CO2e should be a key metric in evaluating models, and we are collaborating with MLPerf developers to include energy usage during training and inference in this industry standard benchmark.

Neural Architecture Search

Benchmarking TinyML Systems: Challenges and Direction

1 code implementation10 Mar 2020 Colby R. Banbury, Vijay Janapa Reddi, Max Lam, William Fu, Amin Fazel, Jeremy Holleman, Xinyuan Huang, Robert Hurtado, David Kanter, Anton Lokhmotov, David Patterson, Danilo Pau, Jae-sun Seo, Jeff Sieracki, Urmish Thakker, Marian Verhelst, Poonam Yadav

In this position paper, we present the current landscape of TinyML and discuss the challenges and direction towards developing a fair and useful hardware benchmark for TinyML workloads.

Automated, context-free assignment of asymmetric rotor microwave spectra

1 code implementation15 Dec 2018 Lia Yeh, Lincoln Satterthwaite, David Patterson

The RAARR algorithm can automatically assign experimental spectra under a broad range of conditions, including spectra comprised of multiple mixture components, in about 100 seconds or less.

Chemical Physics

A Berkeley View of Systems Challenges for AI

no code implementations15 Dec 2017 Ion Stoica, Dawn Song, Raluca Ada Popa, David Patterson, Michael W. Mahoney, Randy Katz, Anthony D. Joseph, Michael Jordan, Joseph M. Hellerstein, Joseph E. Gonzalez, Ken Goldberg, Ali Ghodsi, David Culler, Pieter Abbeel

With the increasing commoditization of computer vision, speech recognition and machine translation systems and the widespread deployment of learning-based back-end technologies such as digital advertising and intelligent infrastructures, AI (Artificial Intelligence) has moved from research labs to production.

Machine Translation Speech Recognition

The GAP Benchmark Suite

6 code implementations14 Aug 2015 Scott Beamer, Krste Asanović, David Patterson

Algorithm designers can use the input graphs and the baseline implementations to demonstrate their contribution.

Distributed, Parallel, and Cluster Computing Data Structures and Algorithms

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