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hal.structure.identifierLithe and fast algorithmic number theory [LFANT]
dc.contributor.authorJOHANSSON, Fredrik
dc.date.accessioned2024-04-04T03:01:08Z
dc.date.available2024-04-04T03:01:08Z
dc.date.conference2019-06-10
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/192874
dc.description.abstractEnWe present algorithms for real and complex dot product and matrix multiplication in arbitrary-precision floating-point and ball arithmetic. A low-overhead dot product is implemented on the level of GMP limb arrays; it is about twice as fast as previous code in MPFR and Arb at precision up to several hundred bits. Up to 128 bits, it is 3-4 times as fast, costing 20-30 cycles per term for floating-point evaluation and 40-50 cycles per term for balls. We handle large matrix multiplications even more efficiently via blocks of scaled integer matrices. The new methods are implemented in Arb and significantly speed up polynomial operations and linear algebra.
dc.language.isoen
dc.subject.enArbitrary-precision arithmetic
dc.subject.enBall arithmetic
dc.subject.enDot product
dc.subject.enMatrix multiplication
dc.title.enFaster arbitrary-precision dot product and matrix multiplication
dc.typeCommunication dans un congrès
dc.subject.halInformatique [cs]/Logiciel mathématique [cs.MS]
dc.subject.halInformatique [cs]/Analyse numérique [cs.NA]
dc.identifier.arxiv1901.04289
bordeaux.hal.laboratoriesInstitut de Mathématiques de Bordeaux (IMB) - UMR 5251*
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
bordeaux.conference.title26th IEEE Symposium on Computer Arithmetic (ARITH26)
bordeaux.countryJP
bordeaux.conference.cityKyoto
bordeaux.peerReviewedoui
hal.identifierhal-01980399
hal.version1
hal.invitednon
hal.proceedingsoui
hal.conference.end2019-06-12
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-01980399v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.au=JOHANSSON,%20Fredrik&rft.genre=unknown


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