An Automated Verification Framework for HalideIR-Based Compiler Transformations
Sponsor
Funding Agency: 10.13039/100000028-Semiconductor Research Corporation (Grant Number: 2932.001) and 10.13039/100002418-Intel Corporation
Published In
2023 Design, Automation & Test in Europe Conference & Exhibition
ISBN
979-8-3503-9624-9
Document Type
Citation
Publication Date
4-2023
Subjects
Deep learning (Machine learning), Compilers (Computer programs), Electronic systems -- Design and construction
Abstract
HalideIR is a popular intermediate representation for compilers in domains such as deep learning, image processing, and hardware design. In this paper, we present an automated verification framework for HalideIR-based compiler transformations. The framework conducts verification using symbolic execution in two steps. Given a compiler transformation, our automated verification framework first uses symbolic execution to enumerate the compiler transformation's paths, and then utilizes symbolic execution to verify if the output program for each transformation path is equivalent to its source. We have successfully applied this framework to verify 46 transformations from the three most-starred HalideIR-based compilers on GitHub and detected 4 transformation bugs undetected by manually crafted unit tests.
Keywords: Deep learning; Program processors; Image processing; Computer bugs; Hardware; Software development management
Rights
Copyright © 2023 by the Institute of Electrical and Electronics Engineers, Inc.
All rights reserved.
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https://doi.org/10.23919/DATE56975.2023.10137308
DOI
10.23919/DATE56975.2023.10137308
Persistent Identifier
https://archives.pdx.edu/ds/psu/42456
Citation Details
Y. Wang, F. Xie, Z. Yang, J. Casas, P. Cocchini and J. Yang, "An Automated Verification Framework for HalideIR-Based Compiler Transformations," 2023 Design, Automation & Test in Europe Conference & Exhibition (DATE), Antwerp, Belgium, 2023, pp. 1-6, doi: 10.23919/DATE56975.2023.10137308.