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OverSketch: Approximate Matrix Multiplication for the Cloud
release_5ygtebaba5farpb37xxmqvlu5i
by
Vipul Gupta and Shusen Wang and Thomas Courtade and Kannan Ramchandran
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2019
Abstract
We propose OverSketch, an approximate algorithm for distributed matrix
multiplication in serverless computing. OverSketch leverages ideas from matrix
sketching and high-performance computing to enable cost-efficient
multiplication that is resilient to faults and straggling nodes pervasive in
low-cost serverless architectures. We establish statistical guarantees on the
accuracy of OverSketch and empirically validate our results by solving a
large-scale linear program using interior-point methods and demonstrate a 34%
reduction in compute time on AWS Lambda.
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1811.02653v2
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