High-level synthesis using the Julia language
File(s)2022_LATTE_JuliaHLS.pdf (414.32 KB)
Accepted version
Author(s)
Biggs, Benjamin
McInerney, Ian
Kerrigan, Eric C
Constantinides, George A
Type
Conference Paper
Abstract
The growing proliferation of FPGAs and High-level Synthesis (HLS) tools has
led to a large interest in designing hardware accelerators for complex
operations and algorithms. However, existing HLS toolflows typically require a
significant amount of user knowledge or training to be effective in both
industrial and research applications. In this paper, we propose using the Julia
language as the basis for an HLS tool. The Julia HLS tool aims to decrease the
barrier to entry for hardware acceleration by taking advantage of the
readability of the Julia language and by allowing the use of the existing large
library of standard mathematical functions written in Julia. We present a
prototype Julia HLS tool, written in Julia, that transforms Julia code to VHDL.
We highlight how features of Julia and its compiler simplified the creation of
this tool, and we discuss potential directions for future work.
led to a large interest in designing hardware accelerators for complex
operations and algorithms. However, existing HLS toolflows typically require a
significant amount of user knowledge or training to be effective in both
industrial and research applications. In this paper, we propose using the Julia
language as the basis for an HLS tool. The Julia HLS tool aims to decrease the
barrier to entry for hardware acceleration by taking advantage of the
readability of the Julia language and by allowing the use of the existing large
library of standard mathematical functions written in Julia. We present a
prototype Julia HLS tool, written in Julia, that transforms Julia code to VHDL.
We highlight how features of Julia and its compiler simplified the creation of
this tool, and we discuss potential directions for future work.
Date Issued
2022-03-01
Date Acceptance
2022-02-09
Citation
2022
Copyright Statement
© 2022 Copyright held by the owner/author(s)
Identifier
http://arxiv.org/abs/2201.11522v1
Source
2nd Workshop on Languages, Tools, and Techniques for Accelerator Design (LATTE’22)
Subjects
cs.AR
cs.SE
cs.SE
Publication Status
Published
Start Date
2022-03-01
Coverage Spatial
Lausanne, Switzerland