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dc.contributor.authorKoo, Jaehyun
dc.date.accessioned2024-07-23T19:50:32Z
dc.date.available2024-07-23T19:50:32Z
dc.date.issued2024-06-17
dc.identifier.isbn979-8-4007-0416-1
dc.identifier.urihttps://hdl.handle.net/1721.1/155771
dc.descriptionSPAA ’24, June 17–21, 2024, Nantes, Franceen_US
dc.description.abstractWe present an O(1)-round fully-scalable deterministic massively parallel algorithm for computing the min-plus matrix multiplication of unit-Monge matrices. We use this to derive a O(łog n)-round fully-scalable massively parallel algorithm for solving the exact longest increasing subsequence (LIS) problem. For a fully-scalable MPC regime, this result substantially improves the previously known algorithm of O(łog^4 n)-round complexity, and matches the best algorithm for computing the (1+ε)-approximation of LIS.en_US
dc.publisherACM|SPAA '24: Proceedings of the 36th ACM Symposium on Parallelism in Algorithms and Architecturesen_US
dc.relation.isversionof10.1145/3626183.3659974en_US
dc.rightsCreative Commons Attributionen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.sourceAssociation for Computing Machineryen_US
dc.titleAn Optimal MPC Algorithm for Subunit-Monge Matrix Multiplication, with Applications to LISen_US
dc.typeArticleen_US
dc.identifier.citationKoo, Jaehyun. 2024. "An Optimal MPC Algorithm for Subunit-Monge Matrix Multiplication, with Applications to LIS."
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
dc.identifier.mitlicensePUBLISHER_CC
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2024-07-01T07:53:46Z
dc.language.rfc3066en
dc.rights.holderThe author(s)
dspace.date.submission2024-07-01T07:53:46Z
mit.licensePUBLISHER_CC
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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