English

Application-Level Validation of Accelerator Designs Using a Formal Software/Hardware Interface

Hardware Architecture 2023-08-23 v2 Programming Languages

Abstract

Ideally, accelerator development should be as easy as software development. Several recent design languages/tools are working toward this goal, but actually testing early designs on real applications end-to-end remains prohibitively difficult due to the costs of building specialized compiler and simulator support. We propose a new first-in-class, mostly automated methodology termed "3LA" to enable end-to-end testing of prototype accelerator designs on unmodified source applications. A key contribution of 3LA is the use of a formal software/hardware interface that specifies an accelerator's operations and their semantics. Specifically, we leverage the Instruction-Level Abstraction (ILA) formal specification for accelerators that has been successfully used thus far for accelerator implementation verification. We show how the ILA for accelerators serves as a software/hardware interface, similar to the Instruction Set Architecture (ISA) for processors, that can be used for automated development of compilers and instruction-level simulators. Another key contribution of this work is to show how ILA-based accelerator semantics enables extending recent work on equality saturation to auto-generate basic compiler support for prototype accelerators in a technique we term "flexible matching." By combining flexible matching with simulators auto-generated from ILA specifications, our approach enables end-to-end evaluation with modest engineering effort. We detail several case studies of 3LA, which uncovered an unknown flaw in a recently published accelerator and facilitated its fix.

Keywords

Cite

@article{arxiv.2203.00218,
  title  = {Application-Level Validation of Accelerator Designs Using a Formal Software/Hardware Interface},
  author = {Bo-Yuan Huang and Steven Lyubomirsky and Yi Li and Mike He and Gus Henry Smith and Thierry Tambe and Akash Gaonkar and Vishal Canumalla and Andrew Cheung and Gu-Yeon Wei and Aarti Gupta and Zachary Tatlock and Sharad Malik},
  journal= {arXiv preprint arXiv:2203.00218},
  year   = {2023}
}
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