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PENCIL: A Platform-Neutral Compute Intermediate Language for Accelerator Programming, , , , , , , , , and 1 other author(s). Proceedings of the 24th International Conference on Parallel Architectures and Compilation Techniques, page 138--149. (2015)A Transferable Approach for Partitioning Machine Learning Models on Multi-Chip-Modules., , , , , , , , and . MLSys, mlsys.org, (2022)Efficient Code Generation for Hardware Accelerators by Refining Partially Specified Implementations. (Génération de code efficace pour accélérateurs matériels par raffinement d'implémentations partiellement spécifiées).. École Normale Supérieure, Paris, France, (2019)Weaving Synchronous Reactions into the Fabric of SSA-form Compilers., , , and . ACM Trans. Archit. Code Optim., 19 (2): 22:1-22:25 (2022)A Transferable Approach for Partitioning Machine Learning Models on Multi-Chip-Modules., , , , , , , , and . CoRR, (2021)TelaMalloc: Efficient On-Chip Memory Allocation for Production Machine Learning Accelerators., , , and . ASPLOS (1), page 123-137. ACM, (2023)On the Representation of Partially Specified Implementations and its Application to the Optimization of Linear Algebra Kernels on GPU., , , and . CoRR, (2019)