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Publications of Torsten Hoefler
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Maciej Besta, Marc Fischer, Tal Ben-Nun, Johannes De Fine Licht, Torsten Hoefler:
| | | Substream-Centric Maximum Matchings on FPGA
(Feb. 2019, In Proceedings of the 27th ACM/SIGDA International Symposium on Field-Programmable Gate Arrays )
AbstractDeveloping high-performance and energy-efficient algorithms
for maximum matchings is becoming increasingly important
in social network analysis, computational sciences, scheduling,
and others. In this work, we propose the first maximum
matching algorithm designed for FPGAs; it is energy-efficient
and has provable guarantees on accuracy, performance, and
storage utilization. To achieve this, we forego popular graph
processing paradigms, such as vertex-centric programming,
that are tuned for CPUs and often entail large communication
costs. Instead, we propose a substream-centric approach, in
which the input stream of data is divided into substreams
processed independently to enable more parallelism while
lowering communication costs. We base our work on the
theory of streaming graph algorithms and analyze 15 models
and 28 algorithms. We use this analysis to provide theoretical
underpinning that matches well the physical constraints of
FPGA platforms. Our algorithm delivers high performance
(more than 4× speedup over tuned parallel CPU variants),
low memory, high accuracy, and effective usage of FPGA
resources. The substream-centric approach could easily be
extended to other algorithms to offer low-power and high-performance
graph processing on FPGAs.
Documents | | | BibTeX | @inproceedings{,
author={Maciej Besta and Marc Fischer and Tal Ben-Nun and Johannes De Fine Licht and Torsten Hoefler},
title={{Substream-Centric Maximum Matchings on FPGA}},
year={2019},
month={Feb.},
note={In Proceedings of the 27th ACM/SIGDA International Symposium on Field-Programmable Gate Arrays},
source={http://www.unixer.de/~htor/publications/},
} |
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