dc.creator | Soler, Janet | |
dc.creator | Ortiz, Javier | |
dc.creator | Wolfmann, Aaron Gustavo | |
dc.date.accessioned | 2022-09-07T14:01:33Z | |
dc.date.accessioned | 2022-10-14T18:27:29Z | |
dc.date.available | 2022-09-07T14:01:33Z | |
dc.date.available | 2022-10-14T18:27:29Z | |
dc.date.created | 2022-09-07T14:01:33Z | |
dc.date.issued | 2013 | |
dc.identifier | http://hdl.handle.net/11086/28443 | |
dc.identifier.uri | https://repositorioslatinoamericanos.uchile.cl/handle/2250/4272386 | |
dc.description.abstract | The number of cores in multicore computers has an irreversible tendency to increase. Also, computers with multiple sockets to insert multicore chips are based on a complex hardware design and are becoming more common. To parallelize the algorithms that run on this type of computers in order to obtain a higher performance rate, is a goal that can only be achieved by taking into account hardware architecture. As hardware evolves, so must software. This leads to old parallelization strategies quickly become obsolete. This paper presents a series of alternatives for parallelization the LU factorization algorithm and its results intended to running on a multicore system. Simple strategies lead to poor results. This study presents complex strategies that merge double levels of parallelism with asynchronous scheduling whose results reach up to the State-of-the-art in the field and even go further. | |
dc.language | eng | |
dc.rights | https://creativecommons.org/licenses/by-nc-sa/4.0/ | |
dc.rights | Attribution-NonCommercial-ShareAlike 4.0 International | |
dc.subject | Hardware architecture | |
dc.subject | Software | |
dc.subject | Multicore system | |
dc.title | Strategies to optimize the LU factorization algorithm on multicore computers | |
dc.type | conferenceObject | |