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Title: HeteroGen: transpiling C to heterogeneous HLS code with automated test generation and program repair
Despite the trend of incorporating heterogeneity and specialization in hardware, the development of heterogeneous applications is limited to a handful of engineers with deep hardware expertise. We propose HeteroGen that takes C/C++ code as input and automatically generates an HLS version with test behavior preservation and better performance. Key to the success of HeteroGen is adapting the idea of search-based program repair to the heterogeneous computing domain, while addressing two technical challenges. First, the turn-around time of HLS compilation and simulation is much longer than the usual C/C++ compilation and execution time; therefore, HeteroGen applies pattern-oriented program edits guided by common fix patterns and their dependences. Second, behavior and performance checking requires testing, but test cases are often unavailable. Thus, HeteroGen auto-generates test inputs suitable for checking C to HLS-C conversion errors, while providing high branch coverage for the original C code. An evaluation of HeteroGen shows that it produces an HLS-compatible version for nine out of ten real-world heterogeneous applications fully automatically, applying up to 438 lines of edits to produce an HLS version 1.63x faster than the original version.  more » « less
Award ID(s):
2106404 1763172 1723773
NSF-PAR ID:
10342993
Author(s) / Creator(s):
; ; ;
Date Published:
Journal Name:
ASPLOS 2022: Proceedings of the 27th ACM International Conference on Architectural Support for Programming Languages and Operating Systems
Page Range / eLocation ID:
1017 to 1029
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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