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Statements

Subject Item
n2:RIV%2F68407700%3A21340%2F12%3A00203142%21RIV13-MSM-21340___
rdf:type
skos:Concept n9:Vysledek
dcterms:description
We present new format for storing sparse matrices on GPU. We compare it with several other formats including CUSPARSE which is today probably the best choice for processing of sparse matrices on GPU in CUDA. Contrary to CUSPARSE which works with common CSR format, our new format requires conversion. However, multiplication of sparse-matrix and vector is significantly faster for many matrices. We demonstrate it on set of 1 600 matrices and we show for what types of matrices our format is profitable. We present new format for storing sparse matrices on GPU. We compare it with several other formats including CUSPARSE which is today probably the best choice for processing of sparse matrices on GPU in CUDA. Contrary to CUSPARSE which works with common CSR format, our new format requires conversion. However, multiplication of sparse-matrix and vector is significantly faster for many matrices. We demonstrate it on set of 1 600 matrices and we show for what types of matrices our format is profitable.
dcterms:title
Improved Row-grouped CSR Format for Storing of Sparse Matrices on GPU Improved Row-grouped CSR Format for Storing of Sparse Matrices on GPU
skos:prefLabel
Improved Row-grouped CSR Format for Storing of Sparse Matrices on GPU Improved Row-grouped CSR Format for Storing of Sparse Matrices on GPU
skos:notation
RIV/68407700:21340/12:00203142!RIV13-MSM-21340___
n9:predkladatel
n10:orjk%3A21340
n3:aktivita
n5:S n5:P n5:Z
n3:aktivity
P(LC06052), S, Z(MSM6840770010)
n3:dodaniDat
n23:2013
n3:domaciTvurceVysledku
n13:6345107 n13:7070195
n3:druhVysledku
n14:D
n3:duvernostUdaju
n20:S
n3:entitaPredkladatele
n16:predkladatel
n3:idSjednocenehoVysledku
140911
n3:idVysledku
RIV/68407700:21340/12:00203142
n3:jazykVysledku
n11:eng
n3:klicovaSlova
sparse matrices; SpMV; parallel computing; GPU; thread computing; CUDA; circuit simulations; optimizations problems
n3:klicoveSlovo
n4:parallel%20computing n4:thread%20computing n4:CUDA n4:GPU n4:circuit%20simulations n4:SpMV n4:optimizations%20problems n4:sparse%20matrices
n3:kontrolniKodProRIV
[90D46D9DAE17]
n3:mistoKonaniAkce
Podbanské
n3:mistoVydani
Bratislava
n3:nazevZdroje
Algoritmy 2012 Proceedings of Contributed Papers and Posters
n3:obor
n19:BA
n3:pocetDomacichTvurcuVysledku
2
n3:pocetTvurcuVysledku
2
n3:projekt
n21:LC06052
n3:rokUplatneniVysledku
n23:2012
n3:tvurceVysledku
Heller, Martin Oberhuber, Tomáš
n3:typAkce
n6:WRD
n3:zahajeniAkce
2012-09-09+02:00
n3:zamer
n18:MSM6840770010
s:numberOfPages
9
n17:hasPublisher
Slovenská technická univerzita v Bratislave. Stavebná fakulta
n15:isbn
978-80-227-3742-5
n22:organizacniJednotka
21340