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SWIRL: High-performance many-core CPU code generation for deep neural networks., , , , and . Int. J. High Perform. Comput. Appl., (2019)Sparse computation data dependence simplification for efficient compiler-generated inspectors., , , , , , , , , and . PLDI, page 594-609. ACM, (2019)Compiler generation and autotuning of communication-avoiding operators for geometric multigrid., , , , , and . HiPC, page 452-461. IEEE Computer Society, (2013)Optimizing LOBPCG: Sparse Matrix Loop and Data Transformations in Action., , and . LCPC, volume 10136 of Lecture Notes in Computer Science, page 218-232. Springer, (2016)Sparse Matrix Code Dependence Analysis Simplification at Compile Time., , , , , , , and . CoRR, (2018)High-Performance Deep Learning via a Single Building Block., , , , , , , , and . CoRR, (2019)Context-Aware Parse Trees., , , , , , , , , and 1 other author(s). CoRR, (2020)MISIM: An End-to-End Neural Code Similarity System., , , , , , , , , and 2 other author(s). CoRR, (2020)Towards making autotuning mainstream., , , , , , , , and . Int. J. High Perform. Comput. Appl., 27 (4): 379-393 (2013)SWIRL++ : Evaluating Performance Models to Guide Code Transformation in Convolutional Neural Networks., , , and . LCPC, volume 11998 of Lecture Notes in Computer Science, page 108-126. Springer, (2019)