Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/33139| Title: | Exploiting Very-Wide Vector Processing for Scientific Applications | Authors: | Diavastos, Andreas Stylianou, Giannos Koutsou, Giannis |
Major Field of Science: | Engineering and Technology | Field Category: | Computer and Information Sciences | Issue Date: | 28-Oct-2015 | Source: | Computing in Science & Engineering, 2015, vol. 17, iss. 6, pp. 83-87 | Volume: | 17 | Issue: | 6 | Start page: | 83 | End page: | 87 | Journal: | Computing in Science and Engineering | Abstract: | Exploiting the recently introduced very-wide vector units of the Xeon Phi coprocessor can potentially increase the scalability for scientific applications. Using lattice QCD compute kernels, the authors find that the performance achieved using the Xeon Phi coprocessors wide vector units is similar to GPGPU performance after appropriate code refactoring, requiring moderate programming effort. | URI: | https://hdl.handle.net/20.500.14279/33139 | ISSN: | 15219615 | DOI: | 10.1109/MCSE.2015.124 | Type: | Article | Affiliation : | The Cyprus Institute University of Cyprus |
Publication Type: | Peer Reviewed |
| Appears in Collections: | Άρθρα/Articles |
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