Sameer Deshmukh, Qinxiang Ma, Rio Yokota, George Bosilca
{"title":"$O(N)$ distributed direct factorization of structured dense matrices using runtime systems","authors":"Sameer Deshmukh, Qinxiang Ma, Rio Yokota, George Bosilca","doi":"arxiv-2311.00921","DOIUrl":null,"url":null,"abstract":"Structured dense matrices result from boundary integral problems in\nelectrostatics and geostatistics, and also Schur complements in sparse\npreconditioners such as multi-frontal methods. Exploiting the structure of such\nmatrices can reduce the time for dense direct factorization from $O(N^3)$ to\n$O(N)$. The Hierarchically Semi-Separable (HSS) matrix is one such low rank\nmatrix format that can be factorized using a Cholesky-like algorithm called ULV\nfactorization. The HSS-ULV algorithm is highly parallel because it removes the\ndependency on trailing sub-matrices at each HSS level. However, a key merge\nstep that links two successive HSS levels remains a challenge for efficient\nparallelization. In this paper, we use an asynchronous runtime system PaRSEC\nwith the HSS-ULV algorithm. We compare our work with STRUMPACK and LORAPO, both\nstate-of-the-art implementations of dense direct low rank factorization, and\nachieve up to 2x better factorization time for matrices arising from a diverse\nset of applications on up to 128 nodes of Fugaku for similar or better accuracy\nfor all the problems that we survey.","PeriodicalId":501256,"journal":{"name":"arXiv - CS - Mathematical Software","volume":"13 2","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Mathematical Software","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2311.00921","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
Structured dense matrices result from boundary integral problems in
electrostatics and geostatistics, and also Schur complements in sparse
preconditioners such as multi-frontal methods. Exploiting the structure of such
matrices can reduce the time for dense direct factorization from $O(N^3)$ to
$O(N)$. The Hierarchically Semi-Separable (HSS) matrix is one such low rank
matrix format that can be factorized using a Cholesky-like algorithm called ULV
factorization. The HSS-ULV algorithm is highly parallel because it removes the
dependency on trailing sub-matrices at each HSS level. However, a key merge
step that links two successive HSS levels remains a challenge for efficient
parallelization. In this paper, we use an asynchronous runtime system PaRSEC
with the HSS-ULV algorithm. We compare our work with STRUMPACK and LORAPO, both
state-of-the-art implementations of dense direct low rank factorization, and
achieve up to 2x better factorization time for matrices arising from a diverse
set of applications on up to 128 nodes of Fugaku for similar or better accuracy
for all the problems that we survey.