http://www.cnr.it/ontology/cnr/individuo/prodotto/ID292505
Multi-Kepler GPU vs. multi-Intel MIC for spin systems simulations (Articolo in rivista)
- Type
- Label
- Multi-Kepler GPU vs. multi-Intel MIC for spin systems simulations (Articolo in rivista) (literal)
- Anno
- 2014-01-01T00:00:00+01:00 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
- 10.1016/j.cpc.2014.05.026 (literal)
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- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- Bernaschi M.; Bisson M.; Salvadore F. (literal)
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- http://www.scopus.com/inward/record.url?eid=2-s2.0-84904757424&partnerID=q2rCbXpz (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
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- Istituto Applicazioni Calcolo, CNR, Viale Manzoni, 30, 00185 Rome, Italy; CINECA, via dei Tizii, 6, 00185 Rome, Italy (literal)
- Titolo
- Multi-Kepler GPU vs. multi-Intel MIC for spin systems simulations (literal)
- Abstract
- We present and compare the performances of two many-core architectures: the Nvidia Kepler and the Intel MIC both in a single system and in cluster configuration for the simulation of spin systems. As a benchmark we consider the time required to update a single spin of the 3D Heisenberg spin glass model by using the Over-relaxation algorithm. We present data also for a traditional high-end multi-core architecture: the Intel Sandy Bridge. The results show that although on the two Intel architectures it is possible to use basically the same code, the performances of a Intel MIC change dramatically depending on (apparently) minor details. Another issue is that to obtain a reasonable scalability with the Intel Phi coprocessor (Phi is the coprocessor that implements the MIC architecture) in a cluster configuration it is necessary to use the so-called offload mode which reduces the performances of the single system. As to the GPU, the Kepler architecture offers a clear advantage with respect to the previous Fermi architecture maintaining exactly the same source code. Scalability of the multi-GPU implementation remains very good by using the CPU as a communication co-processor of the GPU. All source codes are provided for inspection and for double-checking the results. © 2014 Elsevier B.V. All rights reserved. (literal)
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