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  8. TASO: The Tensor Algebra SuperOptimizer for Deep Learning

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    How does Taso perform in deep learning?TASO outperforms the graph optimizers in existing deep learning frameworks by up to 3x. TASO directly optimizes any pre-trained DNN models in ONNX, TensorFlow, and PyTorch graph formats. TASO also provides a Python interface for optimizing arbitrary DNN architectures.
    How can Taso optimize a DNN model?TASO can directly optimize any pre-trained DNN models in ONNX, TensorFlow, and PyTorch graph formats. TASO also provides a Python interface for optimizing arbitrary DNN architectures. TASO supports exporting the optimized computation graphs to ONNX, which can be directly used as inputs by most existing deep learning frameworks.
    Does Taso support exporting optimized computation graphs to ONNX?TASO supports exporting the optimized computation graphs to ONNX, which can be directly used as inputs by most existing deep learning frameworks. For example, the following figures shows how TASO automatically performs a series of non-trivial transformations and improves the inference performance of a ResNet module by 1.3x on a V100 GPU.
    Who are the authors of Taso?Zhihao Jia, Oded Padon, James Thomas, Todd Warszawski, Matei Zaharia, and Alex Aiken. TASO: Optimizing Deep Learning Computation with Automated Generation of Graph Substitutions. In Proceedings of the Symposium on Operating Systems Principles (SOSP), Ontario, Canada, October 2019.
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