Zobrazeno 1 - 10
of 440
pro vyhledávání: '"Basic linear algebra"'
Autor:
Jan Fostier
Publikováno v:
BMC Bioinformatics, Vol 21, Iss S2, Pp 1-13 (2020)
Abstract Background The identification of all matches of a large set of position weight matrices (PWMs) in long DNA sequences requires significant computational resources for which a number of efficient yet complex algorithms have been proposed. Resu
Externí odkaz:
https://doaj.org/article/75eedc7fcddc4ad88dd5a15791b7f380
Akademický článek
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Autor:
Sandra Catalan, Jose R. Herrero, Enrique S. Quintana-Orti, Rafael Rodriguez-Sanchez, Robert Van De Geijn
Publikováno v:
IEEE Access, Vol 7, Pp 17617-17633 (2019)
We propose two novel techniques for overcoming load-imbalance encountered when implementing so-called look-ahead mechanisms in relevant dense matrix factorizations for the solution of linear systems. Both techniques target the scenario where two thre
Externí odkaz:
https://doaj.org/article/1dd22ac4d05f47ea861ef9706b628a77
Autor:
Jakub Kurzak, Mark Gates, Nicholas J. Higham, Azzam Haidar, Jack Dongarra, Stanimire Tomov, Timothy B. Costa, Ahmad Abdelfattah, Mawussi Zounon, Sven Hammarling, Piotr Luszczek
Publikováno v:
ACM Transactions on Mathematical Software. 47:1-23
This article describes a standard API for a set of Batched Basic Linear Algebra Subprograms (Batched BLAS or BBLAS). The focus is on many independent BLAS operations on small matrices that are grouped together and processed by a single routine, calle
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::efae8edd639842bca9e3644bab42a334
https://doi.org/10.1145/3431921
https://doi.org/10.1145/3431921
Publikováno v:
The Journal of Supercomputing. 78:1741-1758
In the past few decades, general matrix multiplication (GEMM), as the basic component of the Basic Linear Algebra Subprograms (BLAS) library, has played a vital role in various fields such as machine learning, image processing, and fluid dynamics. Be
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9b39237c5d9eeb1834edc740857d73be
https://doi.org/10.1007/s11227-021-03936-9
https://doi.org/10.1007/s11227-021-03936-9
Publikováno v:
IEEE Transactions on Very Large Scale Integration (VLSI) Systems. 29:730-738
Deep neural networks (DNNs) have gained tremendous popularity in recent years due to their ability to achieve superhuman accuracy in a wide variety of machine learning tasks. However, the compute and memory requirements of DNNs have grown rapidly, cr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0397deca7d08ef6518a7c7d871ebf12b
https://doi.org/10.1109/tvlsi.2021.3063543
https://doi.org/10.1109/tvlsi.2021.3063543
Autor:
Hanif Muhammad, Zimmermann Karl-Heinz
Publikováno v:
Open Computer Science, Vol 2, Iss 4, Pp 367-388 (2012)
Externí odkaz:
https://doaj.org/article/4e6d275b4caa46dcb603379833a40913