{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,20]],"date-time":"2025-02-20T05:17:27Z","timestamp":1740028647752,"version":"3.37.3"},"reference-count":0,"publisher":"IOS Press","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2014]]},"abstract":"<jats:p>In this paper we evaluate two solvers for the algebraic Riccati equation &amp;ndash;a crucial operation in control theory&amp;ndash; based on the Newton iterative scheme for the matrix sign function. When the target architecture is a multicore server with a moderate number of cores, our Riccati solvers exploit the task-parallelism that exist in the computational kernels that compose the Newton iteration. On the other hand, for hybrid platforms that include a graphics processor (GPU), we further exploit the data-parallelism of the major kernels and off-load these computations to the graphics device. Our experimental results on a platform equipped with state-of-the-art technology from AMD, Intel and NVIDIA reveals significant acceleration factors from the GPU.<\/jats:p>","DOI":"10.3233\/978-1-61499-381-0-367","type":"book-chapter","created":{"date-parts":[[2025,2,19]],"date-time":"2025-02-19T15:30:51Z","timestamp":1739979051000},"source":"Crossref","is-referenced-by-count":0,"title":["Exploiting Data- and Task-Parallelism in the Solution of Riccati Equations on Multicore Servers and GPUs"],"prefix":"10.3233","author":[{"family":"Benner P.","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Ezzatti P.","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Quintana-Ort&iacute; E.S.","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Rem&oacute;n A.","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Advances in Parallel Computing","Parallel Computing: Accelerating Computational Science and Engineering (CSE)"],"original-title":[],"deposited":{"date-parts":[[2025,2,19]],"date-time":"2025-02-19T15:45:11Z","timestamp":1739979911000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.medra.org\/servlet\/aliasResolver?alias=iospressISSNISBN&issn=0927-5452&volume=25&spage=367"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/978-1-61499-381-0-367","relation":{},"ISSN":["0927-5452"],"issn-type":[{"value":"0927-5452","type":"print"}],"subject":[],"published":{"date-parts":[[2014]]}}}