MLIR Related Publications

Publications

• MLIR: Scaling Compiler Infrastructure for Domain Specific Computation - Chris Lattner, Mehdi Amini, Uday Bondhugula, Albert Cohen, Andy Davis, Jacques Pienaar, River Riddle, Tatiana Shpeisman, Nicolas Vasilache, Oleksandr Zinenko - In proceedings of 2021 IEEE/ACM International Symposium on Code Generation and Optimization (CGO) - pp. 2-14 - A preprint is available on arXiv, see FAQ for citation how-to.

About MLIR and MLIR Components

• Compiler Support for Sparse Tensor Computations in MLIR - Aart J.C. Bik, Penporn Koanantakool, Tatiana Shpeisman, Nicolas Vasilache, Bixia Zheng, Fredrik Kjolstad. ACM Transactions on Architecture and Code Optimization, June, 2022. Appeared as preprint on arXiv, February 9, 2022.
• Composable and Modular Code Generation in MLIR: A Structured and Retargetable Approach to Tensor Compiler Construction - Nicolas Vasilache, Oleksandr Zinenko, Aart J.C. Bik, Mahesh Ravishankar, Thomas Raoux, Alexander Belyaev, Matthias Springer, Tobias Gysi, Diego Caballero, Stephan Herhut, Stella Laurenzo, Albert Cohen. Pre-print on arXiv. February 7, 2022.
• The Deep Learning Compiler: A Comprehensive Survey - Li, Mingzhen, Yi Liu, Xiaoyan Liu, Qingxiao Sun, Xin You, Hailong Yang, Zhongzhi Luan, Lin Gan, Guangwen Yang, and Depei Qian. “The deep learning compiler: A comprehensive survey.” IEEE Transactions on Parallel and Distributed Systems 32, no. 3 (2020): 708-727.

Using MLIR

• A MLIR Dialect for Quantum Assembly Languages
• Compiling ONNX Neural Network Models Using MLIR
• SyFER-MLIR: Integrating Fully Homomorphic Encryption Into the MLIR Compiler Framework
• Domain-Specific Multi-Level IR Rewriting for GPU
• High Performance Code Generation in MLIR: An Early Case Study with GEMM - Uday Bondhugula
• TinyIREE: An ML Execution Environment for Embedded Systems from Compilation to Deployment
• Polygeist: Raising C to Polyhedral MLIR
• High-Performance GPU-to-CPU Transpilation and Optimization via High-Level Parallel Constructs