Urlea, C. , Vanderbauwhede, W. and Nabi, S. W. (2020) Efficient FPGA Cost-Performance Space Exploration Using Type-driven Program Transformations. In: 2019 International Conference on Reconfigurable Computing and FPGAs (ReConFig 2019), Cancun, Mexico, 9-11 Dec 2019, ISBN 9781728119571 (doi: 10.1109/ReConFig48160.2019.8994801)
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Abstract
Many numerical simulation applications from the scientific, financial and machine-learning domains require large amounts of compute capacity. They can often be implemented with a streaming data-flow architecture. Field Programmable Gate Arrays (FPGA) are particularly power-efficient hardware architectures suitable for streaming data-flow applications. Although numerous programming languages and frameworks target FPGAs, expert knowledge is still required to optimise the throughput of such applications for each target FPGA device. The process of selecting which optimising transformations to apply, and where to apply them is dubbed Design Space Exploration (DSE). We contribute an elegant and efficient compiler based DSE strategy for FPGAs by merging information sourced from the compiled application's semantic structure, an accurate cost-performance model and a description of hardware resource limits for particular FPGAs. Our work leverages developments in functional programming and dependent type theory to bring performance portability to the realm of High-Level Synthesis (HLS) tools targeting FPGAs. We showcase our approach by presenting achievable speedups for three example applications. Results indicate considerable improvements in throughput of up to 58× in one example. These results are obtained by traversing a minute fraction of the total Design Space.
| Item Type: | Conference Proceedings |
|---|---|
| Status: | Published |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Urlea, Mr Cristian and Vanderbauwhede, Professor Wim and Nabi, Dr Syed Waqar |
| Authors: | Urlea, C., Vanderbauwhede, W., and Nabi, S. W. |
| College/School: | College of Science and Engineering > School of Computing Science |
| ISSN: | 2640-0472 |
| ISBN: | 9781728119571 |
| Copyright Holders: | Copyright © 2019 IEEE |
| Publisher Policy: | Reproduced in accordance with the copyright policy of the publisher |
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