Abstract
The reconfigurable computing paradigm that uses field programmable gate arrays (FPGAs) has received renewed interest in the high-performance computing field due to FPGAs' unique combination of performance and energy efficiency. However, difficulties in programming and optimizing FPGAs have prevented them from being widely accepted as general-purpose computing devices. In accelerator-based heterogeneous computing, portability across diverse heterogeneous devices is also an important issue, but the unique architectural features in FPGAs make this difficult to achieve. To address these issues, a directive-based, high-level FPGA programming and optimization framework was previously developed. In this work, developed optimizations were combined holistically using the directive-based approach to show that each individual benchmark requires a unique set of optimizations to maximize performance. The relationships between FPGA resource usages and runtime performance were also explored.
Original language | English |
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Title of host publication | Proceedings - 2020 IEEE 34th International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2020 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 460-470 |
Number of pages | 11 |
ISBN (Electronic) | 9781728174457 |
DOIs | |
State | Published - May 2020 |
Event | 34th IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2020 - New Orleans, United States Duration: May 18 2020 → May 22 2020 |
Publication series
Name | Proceedings - 2020 IEEE 34th International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2020 |
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Conference
Conference | 34th IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2020 |
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Country/Territory | United States |
City | New Orleans |
Period | 05/18/20 → 05/22/20 |
Bibliographical note
Publisher Copyright:© 2020 IEEE.
Funding
This research was supported in part by the Exascale Computing Project (17-SC-20-SC), a collaborative effort of the US Department of Energy (DOE) Office of Science (OS) and the National Nuclear Security Administration. This material is based upon work supported by the DOE OS Advanced Scientific Computing Research under contract number DE-AC05-00OR22725.The US government retains— and the publisher, by accepting the article for publication, acknowledges that the US government retains—a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).
Funders | Funder number |
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US Department of Energy | |
U.S. Department of Energy | |
Office of Science | |
National Nuclear Security Administration | |
Advanced Scientific Computing Research | DE-AC05-00OR22725 |
Keywords
- Compiler optimization
- Directive-based programming
- FPGA
- OpenACC
- OpenARC