Publications
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Conferences 2023
Aart J.C. Bik, Yinying Li, and Peiming Liu. Progress on the MLIR Sparsifier. 2023 LLVM Developers' Meeting (MLIR Workshop), October 10, 2023.
Aart J.C. Bik and Peiming Liu. Moving the MLIR Sparse Compiler Pipeline into Production. Second Workshop on Compiler Techniques for Sparse Tensor Algebra (CTSTA), Orlando, Florida, June 18, 2023 (during PLDI 2023).
Joo Hyung Lee, Wonpyo Park, Nicole Mitchell, Jonathan Pilault, Johan Obando-Ceron, Han-Byul Kim, Namhoon Lee, Elias Frantar, Yun Long, Amir Yazdanbakhsh, Shivani Agrawal, Suvinay Subramanian, Xin Wang, Sheng-Chun Kao, Xingyao Zhang, Trevor Gale, Aart J.C. Bik. Woohyun Han, Milen Ferev, Zhonglin Han, Hong-Seok Kim, Yann Dauphin, Gintare Karolina Dziugaite, Pablo Samuel Castro, and Utku Evci. JaxPruner: A Concise Library for Sparsity Research. Sparsity in Neural Networks Worshop. Kigali, Rwanda, May 5, 2023.
Aart J.C. Bik. Sparse Compilation (recording and slides). OpenXLA Dev Summit, April 27, 2023.
Journal Papers 2022
- Aart J.C. Bik, Penporn Koanantakool, Tatiana Shpeisman, Nicolas Vasilache, Bixia Zheng, and Fredrik Kjolstad. Compiler Support for Sparse Tensor Computations in MLIR. ACM Transactions on Architecture and Code Optimization, June, 2022 (appeared as as pre-print arXiv:2202.04305, February 7, 2022).
Conferences 2022
Nicolas Vasilache, Oleksandr Zinenko, Aart J.C. Bik, Mahesh Ravishankar, Thomas Raoux, Alexander Belyaev, Matthias Springer, Tobias Gysi, Diego Caballero, Stephan Herhut, Stella Laurenzo, and Albert Cohen. Structured Operations: Modular Design of Code Generators for Tensor Compilers. In: Mendis, C., Rauchwerger, L. (eds) Languages and Compilers for Parallel Computing. Lecture Notes in Computer Science, vol 13829. LCPC, May 2022.
Aart J.C. Bik. Sparse Compiler Progress. 2022 LLVM Developers' Meeting (MLIR Summit "Project Updates" Track), November 7-10, 2022.
White Papers 2022
- Nicolas Vasilache, Oleksandr Zinenko, Aart J.C. Bik, Mahesh Ravishankar, Thomas Raoux, Alexander Belyaev, Matthias Springer, Tobias Gysi, Diego Caballero, Stephan Herhut, Stella Laurenzo, and Albert Cohen. Composable and Modular Code Generation in MLIR: A Structured and Retargetable Approach to Tensor Compiler Construction. Distributed as pre-print arXiv:2202.03293, February 7, 2022.
Conferences 2021
Presentations 2021
Aart J.C. Bik. Sparse Tensor Types in MLIR (discussion). Presented at the MLIR Open Design Meeting, March 11, 2021 (recording).
Aart J.C. Bik. Compiler Support for Sparse Tensor Computations in MLIR. Presented at the MLIR Open Design Meeting, February 18, 2021 (slides and recording).
PhD Thesis 1996
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Last updated 2024-09-03 UTC.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-09-03 UTC."],[[["\u003cp\u003eThis webpage catalogs Aart J.C. Bik's work on sparse tensor computations, compiler support, and their applications in machine learning, primarily using the MLIR framework.\u003c/p\u003e\n"],["\u003cp\u003eThe work spans publications in conferences, journals, and workshops, including presentations at LLVM Developers' Meetings and MLIR Open Design Meetings.\u003c/p\u003e\n"],["\u003cp\u003eKey topics covered include the development of the MLIR Sparsifier, integration of sparse compiler pipelines into production, and research on sparsity in neural networks using tools like JaxPruner.\u003c/p\u003e\n"],["\u003cp\u003eA significant focus is on structured operations and modular design for code generators in tensor compilers, enabling efficient and retargetable compilation.\u003c/p\u003e\n"],["\u003cp\u003eThe research builds upon foundational work from Aart J.C. Bik's 1996 PhD thesis on compiler support for sparse matrix computations, demonstrating a long-term commitment to this field.\u003c/p\u003e\n"]]],["Aart J.C. Bik and collaborators presented on sparse tensor computations and the MLIR compiler pipeline at multiple conferences, including the LLVM Developers' Meeting, CTSTA, and Sparsity in Neural Networks Workshop. Key topics included \"Progress on the MLIR Sparsifier,\" \"Moving the MLIR Sparse Compiler Pipeline into Production,\" \"Sparse Compilation,\" and \"Compiler Support for Sparse Tensor Computations in MLIR.\" Additionally, they introduced \"JaxPruner,\" a library for sparsity research, and presented a structured approach to tensor compiler construction.\n"],null,["# Publications\n\n**Conferences 2023**\n\n- Aart J.C. Bik, Yinying Li, and Peiming Liu. Progress on the MLIR Sparsifier. [2023 LLVM Developers' Meeting](https://llvm.swoogo.com/2023devmtg/) (MLIR Workshop), October 10, 2023.\n\n- Aart J.C. Bik and Peiming Liu. Moving the MLIR Sparse Compiler Pipeline into Production. [Second Workshop on Compiler Techniques for Sparse Tensor Algebra (CTSTA)](https://pldi23.sigplan.org/home/ctsta-2023), Orlando, Florida, June 18, 2023 (during PLDI 2023).\n\n- Joo Hyung Lee, Wonpyo Park, Nicole Mitchell, Jonathan Pilault, Johan Obando-Ceron, Han-Byul Kim, Namhoon Lee, Elias Frantar, Yun Long, Amir Yazdanbakhsh, Shivani Agrawal, Suvinay Subramanian, Xin Wang, Sheng-Chun Kao, Xingyao Zhang, Trevor Gale, Aart J.C. Bik. Woohyun Han, Milen Ferev, Zhonglin Han, Hong-Seok Kim, Yann Dauphin, Gintare Karolina Dziugaite, Pablo Samuel Castro, and Utku Evci. [JaxPruner: A Concise Library for Sparsity Research](https://arxiv.org/pdf/2304.14082.pdf). Sparsity in Neural Networks Worshop. Kigali, Rwanda, May 5, 2023.\n\n- Aart J.C. Bik. Sparse Compilation ([recording](https://www.youtube.com/watch?t=4939&v=5i7xrBUCD38&feature=youtu.be) and [slides](https://docs.google.com/presentation/d/12A3xs-rG18zvD1nNsuZOdAlld_qjA_Pn9yx4j6elji4/edit?pli=1&resourcekey=0-w9--wU8abVZ1n6CPUjkK-g#slide=id.g24129ef52b5_0_0)). OpenXLA Dev Summit, April 27, 2023.\n\n**Journal Papers 2022**\n\n- Aart J.C. Bik, Penporn Koanantakool, Tatiana Shpeisman, Nicolas Vasilache, Bixia Zheng, and Fredrik Kjolstad. [Compiler Support for Sparse Tensor Computations in MLIR](https://dl.acm.org/doi/10.1145/3544559). ACM Transactions on Architecture and Code Optimization, June, 2022 (appeared as as pre-print arXiv:2202.04305, February 7, 2022).\n\n**Conferences 2022**\n\n- Nicolas Vasilache, Oleksandr Zinenko, Aart J.C. Bik, Mahesh Ravishankar, Thomas Raoux, Alexander Belyaev, Matthias Springer, Tobias Gysi, Diego Caballero, Stephan Herhut, Stella Laurenzo, and Albert Cohen. [Structured Operations: Modular Design of Code Generators for Tensor Compilers](https://storage.googleapis.com/pub-tools-public-publication-data/pdf/241ee71b059d9f2295385a46be37311d29e3fc1c.pdf). In: Mendis, C., Rauchwerger, L. (eds) Languages and Compilers for Parallel Computing. Lecture Notes in Computer Science, vol 13829. LCPC, May 2022.\n\n- Aart J.C. Bik. Sparse Compiler Progress. [2022 LLVM Developers' Meeting](https://llvm.org/devmtg/2022-11/) (MLIR Summit \"Project Updates\" Track), November 7-10, 2022.\n\n**White Papers 2022**\n\n- Nicolas Vasilache, Oleksandr Zinenko, Aart J.C. Bik, Mahesh Ravishankar, Thomas Raoux, Alexander Belyaev, Matthias Springer, Tobias Gysi, Diego Caballero, Stephan Herhut, Stella Laurenzo, and Albert Cohen. Composable and Modular Code Generation in MLIR: A Structured and Retargetable Approach to Tensor Compiler Construction. Distributed as pre-print [arXiv:2202.03293](https://arxiv.org/abs/2202.03293), February 7, 2022.\n\n**Conferences 2021**\n\n- Aart J.C. Bik. [Compiler Support for Sparse Tensor Computations in MLIR](https://www.youtube.com/watch?v=x-nHc3hBxHM). [2021 LLVM Developers' Meeting](https://llvm.org/devmtg/2021-11/), November 16-19, 2021.\n\n**Presentations 2021**\n\n- Aart J.C. Bik. Sparse Tensor Types in MLIR (discussion). Presented at the MLIR Open Design Meeting, March 11, 2021 ([recording](https://drive.google.com/file/d/1D9D5x-1O4oDrNxVg_Vg7CyJQDjSw28z5/view)).\n\n- Aart J.C. Bik. Compiler Support for Sparse Tensor Computations in MLIR. Presented at the MLIR Open Design Meeting, February 18, 2021 ([slides and recording](https://drive.google.com/drive/u/0/folders/1xeiay1h5HvYRe5qYv_J2EC-hchW5VzZy)).\n\n**PhD Thesis 1996**\n\n- A.J.C. Bik. [Compiler Support for Sparse Matrix Computations](https://www.aartbik.com/MISC/bik-96.pdf). ISBN 90-9009442-3, NUGI 855, Leiden University, 1996. This PhD thesis received the C.J. Kok Award (outstanding thesis award) from the Leiden University."]]