EPIC: An Energy-Efficient, High-Performance GPGPU Computing Research Infrastructure
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arXiv
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| Hauptverfasser: | , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2019
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| _version_ | 1866910512996941824 |
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| author | Själander, Magnus Jahre, Magnus Tufte, Gunnar Reissmann, Nico |
| author_facet | Själander, Magnus Jahre, Magnus Tufte, Gunnar Reissmann, Nico |
| contents | The pursuit of many research questions requires massive computational resources. State-of-the-art research in physical processes using simulations, the training of neural networks for deep learning, or the analysis of big data are all dependent on the availability of sufficient and performant computational resources. For such research, access to a high-performance computing infrastructure is indispensable. Many scientific workloads from such research domains are inherently parallel and can benefit from the data-parallel architecture of general purpose graphics processing units (GPGPUs). However, GPGPU resources are scarce at Norway's national infrastructure. EPIC is a GPGPU enabled computing research infrastructure at NTNU. It enables NTNU's researchers to perform experiments that otherwise would be impossible, as time-to-solution would simply take too long. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_1912_05848 |
| institution | arXiv |
| publishDate | 2019 |
| record_format | arxiv |
| spellingShingle | EPIC: An Energy-Efficient, High-Performance GPGPU Computing Research Infrastructure Själander, Magnus Jahre, Magnus Tufte, Gunnar Reissmann, Nico Distributed, Parallel, and Cluster Computing The pursuit of many research questions requires massive computational resources. State-of-the-art research in physical processes using simulations, the training of neural networks for deep learning, or the analysis of big data are all dependent on the availability of sufficient and performant computational resources. For such research, access to a high-performance computing infrastructure is indispensable. Many scientific workloads from such research domains are inherently parallel and can benefit from the data-parallel architecture of general purpose graphics processing units (GPGPUs). However, GPGPU resources are scarce at Norway's national infrastructure. EPIC is a GPGPU enabled computing research infrastructure at NTNU. It enables NTNU's researchers to perform experiments that otherwise would be impossible, as time-to-solution would simply take too long. |
| title | EPIC: An Energy-Efficient, High-Performance GPGPU Computing Research Infrastructure |
| topic | Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/1912.05848 |