With their widespread availability, FPGA-based accelerators cards have become an alternative to GPUs and CPUs to accelerate computing in applications with certain requirements (like energy efficiency) or properties (like fixed-point computations). In this paper we show results and experiences from mapping an industrial application used for drug discovery on several types of accelerators. We especially highlight the effort versus benefit of FPGAs compared to CPUs and GPUs in terms of performance and energy efficiency. For this application, even with extensive use of FPGA-specific features, and performing different optimizations, results on GPUs are still better, both in terms of energy and performance.
@article{arxiv.2210.10386,
title = {Virtual Screening on FPGA: Performance and Energy versus Effort},
author = {Tom Vander Aa and Tom Haber and Thomas J. Ashby and Roel Wuyts and Wilfried Verachtert},
journal= {arXiv preprint arXiv:2210.10386},
year = {2022}
}
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To be published at H2RC 2022 - https://h2rc.cse.sc.edu/