Predictable Accelerator Design with Time-Sensitive Affine Types
April 09, 2020 ยท Declared Dead ยท ๐ ACM-SIGPLAN Symposium on Programming Language Design and Implementation
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Authors
Rachit Nigam, Sachille Atapattu, Samuel Thomas, Zhijing Li, Theodore Bauer, Yuwei Ye, Apurva Koti, Adrian Sampson, Zhiru Zhang
arXiv ID
2004.04852
Category
cs.PL: Programming Languages
Cross-listed
cs.AR
Citations
73
Venue
ACM-SIGPLAN Symposium on Programming Language Design and Implementation
Last Checked
2 months ago
Abstract
Field-programmable gate arrays (FPGAs) provide an opportunity to co-design applications with hardware accelerators, yet they remain difficult to program. High-level synthesis (HLS) tools promise to raise the level of abstraction by compiling C or C++ to accelerator designs. Repurposing legacy software languages, however, requires complex heuristics to map imperative code onto hardware structures. We find that the black-box heuristics in HLS can be unpredictable: changing parameters in the program that should improve performance can counterintuitively yield slower and larger designs. This paper proposes a type system that restricts HLS to programs that can predictably compile to hardware accelerators. The key idea is to model consumable hardware resources with a time-sensitive affine type system that prevents simultaneous uses of the same hardware structure. We implement the type system in Dahlia, a language that compiles to HLS C++, and show that it can reduce the size of HLS parameter spaces while accepting Pareto-optimal designs.
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