{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,6]],"date-time":"2026-02-06T06:40:00Z","timestamp":1770360000076,"version":"3.49.0"},"reference-count":28,"publisher":"Association for Computing Machinery (ACM)","issue":"2","license":[{"start":{"date-parts":[[2015,2,4]],"date-time":"2015-02-04T00:00:00Z","timestamp":1423008000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Italian ISCRA project \u201cPARPREC: Scalable Preconditioners for Large Scale Problems\u201d at the CINECA Centre for High Performance Computing"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Math. Softw."],"published-print":{"date-parts":[[2015,2,4]]},"abstract":"<jats:p>The Factorized Sparse Approximate Inverse (FSAI) is an efficient technique for preconditioning parallel solvers of symmetric positive definite sparse linear systems. The key factor controlling FSAI efficiency is the identification of an appropriate nonzero pattern. Currently, several strategies have been proposed for building such a nonzero pattern, using both static and dynamic techniques. This article describes a fresh software package, called FSAIPACK, which we developed for shared memory parallel machines. It collects all available algorithms for computing FSAI preconditioners. FSAIPACK allows for combining different techniques according to any specified strategy, hence enabling the user to thoroughly exploit the potential of each preconditioner, in solving any peculiar problem. FSAIPACK is freely available as a compiled library at http:\/\/www.dmsa.unipd.it\/~janna\/software.html, together with an open-source command language interpreter. By writing a command ASCII file, one can easily perform and test any given strategy for building an FSAI preconditioner. Numerical experiments are discussed in order to highlight the FSAIPACK features and evaluate its computational performance.<\/jats:p>","DOI":"10.1145\/2629475","type":"journal-article","created":{"date-parts":[[2015,2,10]],"date-time":"2015-02-10T13:19:47Z","timestamp":1423574387000},"page":"1-26","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":43,"title":["FSAIPACK"],"prefix":"10.1145","volume":"41","author":[{"given":"Carlo","family":"Janna","sequence":"first","affiliation":[{"name":"DICEA, University of Padova, Italy and M3E S.r.l., Padova, Italy"}]},{"given":"Massimiliano","family":"Ferronato","sequence":"additional","affiliation":[{"name":"DICEA, University of Padova, Italy and M3E S.r.l., Padova, Italy"}]},{"given":"Flavio","family":"Sartoretto","sequence":"additional","affiliation":[{"name":"DAIS, Universit\u00e0 Ca' Foscari Venezia, Italy"}]},{"given":"Giuseppe","family":"Gambolati","sequence":"additional","affiliation":[{"name":"DICEA, University of Padova, Italy and M3E S.r.l., Padova, Italy"}]}],"member":"320","published-online":{"date-parts":[[2015,2,4]]},"reference":[{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1137\/S1064827594271421"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0168-9274(98)00118-4"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11075-012-9605-7"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1137\/S1064827594270415"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1137\/S106482759833913X"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1177\/109434200101500106"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/2049662.2049663"},{"key":"e_1_2_1_9_1","volume-title":"Preconditioning for sparse linear systems at the dawn of the 21st century: History, current developments, and future perspectives. ISRN Appl. Math","author":"Ferronato M.","year":"2012"},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1002\/nag.1012"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1002\/nme.3309"},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1137\/S1064827594276552"},{"key":"e_1_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0168-9274(98)00117-2"},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1023\/A:1023988426844"},{"key":"e_1_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1002\/nme.2664"},{"key":"e_1_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1137\/090779760"},{"key":"e_1_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1137\/100810368"},{"key":"e_1_2_1_19_1","first-page":"897","article-title":"A preconditioned conjugate gradient method for solving discrete analogs of differential problems","volume":"26","author":"Kaporin I. E.","year":"1990","journal-title":"Diff. Equat."},{"key":"e_1_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1002\/nla.1680010208"},{"key":"e_1_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1137\/0614004"},{"key":"e_1_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1002\/(SICI)1099-1506(199910\/11)6:7<515::AID-NLA176>3.0.CO;2-0"},{"key":"e_1_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.camwa.2011.04.071"},{"key":"e_1_2_1_24_1","volume-title":"http:\/\/www.openmp.org. (Last accessed on","author":"MP","year":"2013"},{"key":"e_1_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1002\/nla.1680010405"},{"key":"e_1_2_1_26_1","volume-title":"Iterative Methods for Sparse Linear Systems","author":"Saad Y.","edition":"2"},{"key":"e_1_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1002\/nla.279"},{"key":"e_1_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1007\/BF02165096"},{"key":"e_1_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1137\/S1064827502400832"},{"key":"e_1_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.finel.2010.11.005"}],"container-title":["ACM Transactions on Mathematical Software"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/2629475","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/2629475","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T07:01:17Z","timestamp":1750230077000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/2629475"}},"subtitle":["A Software Package for High-Performance Factored Sparse Approximate Inverse Preconditioning"],"short-title":[],"issued":{"date-parts":[[2015,2,4]]},"references-count":28,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2015,2,4]]}},"alternative-id":["10.1145\/2629475"],"URL":"https:\/\/doi.org\/10.1145\/2629475","relation":{},"ISSN":["0098-3500","1557-7295"],"issn-type":[{"value":"0098-3500","type":"print"},{"value":"1557-7295","type":"electronic"}],"subject":[],"published":{"date-parts":[[2015,2,4]]},"assertion":[{"value":"2013-07-01","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2014-05-01","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2015-02-04","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}