{"title":"Partial and weighted matrix multiplication","authors":"Péter Vrana","doi":"arxiv-2408.15728","DOIUrl":null,"url":null,"abstract":"In a paper published in 1981, Sch\\\"onhage showed that large total matrix\nmultiplications can be reduced to powers of partial matrix multiplication\ntensors, which correspond to the bilinear computation task of multiplying\nmatrices with some of the entries fixed to be zero. It was left as an open\nproblem to generalize the method to the case when the multiplication is also\npartial in the sense that only a subset of the entries need to be computed. We\nprove a variant of a more general case: reducing large weighted matrix\nmultiplications to tensor powers of a partial matrix multiplication in the\nsense that every entry of the result is a partial version of the inner product\nof the corresponding row and column of the factors that would appear in the\nusual matrix product. The implication is that support rank upper bounds on\npartial matrix multiplication tensors in this general sense give upper bounds\non the support rank exponent of matrix multiplication.","PeriodicalId":501024,"journal":{"name":"arXiv - CS - Computational Complexity","volume":"67 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Computational Complexity","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2408.15728","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In a paper published in 1981, Sch\"onhage showed that large total matrix
multiplications can be reduced to powers of partial matrix multiplication
tensors, which correspond to the bilinear computation task of multiplying
matrices with some of the entries fixed to be zero. It was left as an open
problem to generalize the method to the case when the multiplication is also
partial in the sense that only a subset of the entries need to be computed. We
prove a variant of a more general case: reducing large weighted matrix
multiplications to tensor powers of a partial matrix multiplication in the
sense that every entry of the result is a partial version of the inner product
of the corresponding row and column of the factors that would appear in the
usual matrix product. The implication is that support rank upper bounds on
partial matrix multiplication tensors in this general sense give upper bounds
on the support rank exponent of matrix multiplication.