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Echo: Compiler-based GPU Memory Footprint Reduction for LSTM RNN Training., , and . ISCA, page 1089-1102. IEEE, (2020)DietCode: Automatic Optimization for Dynamic Tensor Programs., , , , , , , , , and . MLSys, mlsys.org, (2022)Automatic Horizontal Fusion for GPU Kernels., , , and . CGO, page 14-27. IEEE, (2022)IDEAL: image denoising accelerator., , , , , , , and . MICRO, page 82-95. ACM, (2017)EcoRNN: Fused LSTM RNN Implementation with Data Layout Optimization., , , , and . CoRR, (2018)Hidet: Task Mapping Programming Paradigm for Deep Learning Tensor Programs., , , , , and . CoRR, (2022)Grape: Practical and Efficient Graphed Execution for Dynamic Deep Neural Networks on GPUs., , , , , , and . MICRO, page 1364-1380. ACM, (2023)Hidet: Task-Mapping Programming Paradigm for Deep Learning Tensor Programs., , , , , and . ASPLOS (2), page 370-384. ACM, (2023)Automatic Horizontal Fusion for GPU Kernels., , , and . CoRR, (2020)Tempo: Accelerating Transformer-Based Model Training through Memory Footprint Reduction., , , and . NeurIPS, (2022)