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EECS Publication

High Performance Realtime Convex Solver for Embedded Systems

Ichitaro Yamazaki and Saeid Nooshabadi (Senior Member, IEEE) and Stanimire Tomov and Jack Dongarra

Abstract- Convex optimization solvers for embedded systems find widespread use. This letter presents a novel technique to reduce the run-time of decomposition of KKT matrix for the convex optimization solver for an embedded system, by two orders of magnitude. We use the property that although the KKT matrix changes, some of its block sub-matrices are fixed during the solution iterations and the associated solving instances. Index Terms-Realtime embedded convex optimization solver, KKT

Published  2016-10-25 04:00:00  as  ut-eecs-16-745 (ID:605)


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