EPIC: An Energy-Efficient, High-Performance GPGPU Computing Research Infrastructure

December 12, 2019 Β· Declared Dead Β· πŸ› arXiv.org

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Authors Magnus SjΓ€lander, Magnus Jahre, Gunnar Tufte, Nico Reissmann arXiv ID 1912.05848 Category cs.DC: Distributed Computing Citations 108 Venue arXiv.org Last Checked 4 months ago
Abstract
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.
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