165 research outputs found
OverSketch: Approximate Matrix Multiplication for the Cloud
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.Comment: Published in Proc. IEEE Big Data 2018. Updated version provides
details of distributed sketching and highlights other advantages of
OverSketc
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