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20241212160804.0 |
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241212s2012 hu o 0|| Angol d |
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|a 9781467326322
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|a 2724105
|2 mtmt
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|a PPKE Publikáció Repozitórium
|b hun
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|a Angol
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|a Reguly István Zoltán
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| 245 |
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|a Efficient sparse matrix-vector multiplication on cache-based GPUs
|h [elektronikus dokumentum] /
|c Reguly István Zoltán
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| 260 |
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|a IEEE Communications Society
|b Piscataway (NJ)
|c 2012
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|a 12
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|a 1-12
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|a Innovative Parallel Computing (InPar), 2012
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|a Sparse matrix-vector multiplication is an integral part of many scientific algorithms. Several studies have shown that it is a bandwidth-limited operation on current hardware. On cache-based architectures the main factors that influence performance are spatial locality in accessing the matrix, and temporal locality in re-using the elements of the vector. © 2012 IEEE.
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| 650 |
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|a Műszaki és technológiai tudományok
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| 700 |
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|a Giles M
|e aut
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|u https://publikacio.ppke.hu/id/eprint/1901/1/Efficient_sparse_matrix-vector_multiplication_on_cache-based_GPUs.pdf
|z Dokumentum-elérés
|