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AutoAccel: Automated Accelerator Generation and Optimization with Composable, Parallel and Pipeline Architecture., , , and . CoRR, (2018)Decoupled Model Schedule for Deep Learning Training., , , , , and . CoRR, (2023)TensorIR: An Abstraction for Automatic Tensorized Program Optimization., , , , , , , , , and 1 other author(s). CoRR, (2022)From JVM to FPGA: Bridging Abstraction Hierarchy via Optimized Deep Pipelining., , and . HotCloud, USENIX Association, (2018)MOCHA: Multinode Cost Optimization in Heterogeneous Clouds with Accelerators., , , , , , and . FPGA, page 273-279. ACM, (2021)TensorIR: An Abstraction for Automatic Tensorized Program Optimization., , , , , , , , , and 1 other author(s). ASPLOS (2), page 804-817. ACM, (2023)DietCode: Automatic Optimization for Dynamic Tensor Programs., , , , , , , , , and . MLSys, mlsys.org, (2022)Bring Your Own Codegen to Deep Learning Compiler., , , , , , , , and . CoRR, (2021)RAF: Holistic Compilation for Deep Learning Model Training., , , , , , , , , and 2 other author(s). CoRR, (2023)Efficient Memory Management for Large Language Model Serving with PagedAttention., , , , , , , , and . SOSP, page 611-626. ACM, (2023)