Dfesnippets: An open-source library for dataflow acceleration on FPGAs
File(s)arc17pg.pdf (247.85 KB)
Accepted version
Author(s)
Type
Conference Paper
Abstract
Highly-tuned FPGA implementations can achieve significant performance and power efficiency gains over general purpose hardware. However the limited development productivity has prevented mainstream adoption of FPGAs in many areas such as High Performance Computing. High level standard development libraries are increasingly adopted in improving productivity. We propose an approach for performance critical applications including standard library modules, benchmarking facilities and application benchmarks to support a variety of usecases. We implement the proposed approach as an open-source library for a commercially available FPGA system and highlight applications and productivity gains.
Date Issued
2017-03-31
Date Acceptance
2017-03-01
ISBN
9783319562575
ISSN
0302-9743
Publisher
Springer
Start Page
299
End Page
310
Journal / Book Title
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume
10216
Copyright Statement
© Springer International Publishing AG 2017. The final publication is available at Springer via https://link.springer.com/chapter/10.1007%2F978-3-319-56258-2_26
Sponsor
Engineering & Physical Science Research Council (E
Commission of the European Communities
Engineering & Physical Science Research Council (E
Grant Number
PO 1553380
671653
516075101 (EP/N031768/1)
Source
13th International Symposium, ARC 2017
Subjects
08 Information And Computing Sciences
Artificial Intelligence & Image Processing
Publication Status
Published
Start Date
2017-04-03
Finish Date
2017-04-07
Coverage Spatial
Delft, The Netherlands