Apollo: Reusable Models for Fast, Dynamic Tuning of Input-Dependent Code

Article Details
Title:	Apollo: Reusable Models for Fast, Dynamic Tuning of Input-Dependent Code
Article URLs:	https://doi.org/10.1109/IPDPS.2017.38 http://doi.ieeecomputersociety.org/10.1109/IPDPS.2017.38
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Authors:	David Beckingsale	Lawrence Livermore National Laboratory, Center for Applied Scientific Computing
	Olga Pearce	Lawrence Livermore National Laboratory, Center for Applied Scientific Computing
	Ignacio Laguna	Lawrence Livermore National Laboratory, Center for Applied Scientific Computing
	Todd Gamblin	Lawrence Livermore National Laboratory, Center for Applied Scientific Computing
Sharing:	Unknown
Verification:	Authors have not verified information
Artifact Evaluation Badge:	none
Artifact URLs:	https://github.com/LLNL/Apollo
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DBLP Key:	conf/ipps/BeckingsalePLG17
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IEEE Intl. Parallel and Distributed Processing Symposium, IPDPS 2017