NeuRI: Diversifying DNN Generation via Inductive Rule Inference

Author:

Liu Jiawei1,Peng Jinjun2,Wang Yuyao3,Zhang Lingming1

Affiliation:

1. University of Illinois, Urbana-Champaign, USA

2. Columbia University, New York, USA

3. Nanjing University, Nanjing, China

Funder

NSF (National Science Foundation)

Publisher

ACM

Reference58 articles.

1. 2022. ASPLOS2023 Artifact for "NNSmith: Generating Diverse and Valid Test Cases for Deep Learning Compilers". Zenodo. https://doi.org/10 .5281/zenodo.7222132 10.5281/zenodo.7222132 10.5281/zenodo.7222132 2022. ASPLOS2023 Artifact for "NNSmith: Generating Diverse and Valid Test Cases for Deep Learning Compilers". Zenodo. https://doi.org/10.5281/zenodo.7222132 10.5281/zenodo.7222132

2. 2022. Building the Future of TensorFlow — The TensorFlow Blog. https://blog.tensorflow.org/2022/10/building-the-future-of-tensorflow.html 2022. Building the Future of TensorFlow — The TensorFlow Blog. https://blog.tensorflow.org/2022/10/building-the-future-of-tensorflow.html

3. 2022. "Compute Sanitizer :: CUDA Toolkit Documentation". https://docs.nvidia.com/cuda/compute-sanitizer/index.html 2022. "Compute Sanitizer :: CUDA Toolkit Documentation". https://docs.nvidia.com/cuda/compute-sanitizer/index.html

4. 2022. GCOV. https://gcc.gnu.org/onlinedocs/gcc/Gcov.html 2022. GCOV. https://gcc.gnu.org/onlinedocs/gcc/Gcov.html

5. 2022. PyTorch 2.0 | PyTorch. https://pytorch.org/get-started/pytorch-2.0/ 2022. PyTorch 2.0 | PyTorch. https://pytorch.org/get-started/pytorch-2.0/

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