Getting Started With TVM¶

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Installing TVM¶

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Compiling and Optimizing a Model with TVMC¶

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Compiling and Optimizing a Model with the Python Interface (AutoTVM)¶

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Working with Operators Using Tensor Expression¶

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Optimizing Operators with Schedule Templates and AutoTVM¶

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Optimizing Operators with Auto-scheduling¶

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Cross Compilation and RPC¶

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Quick Start Tutorial for Compiling Deep Learning Models¶

Tensor Expression and Schedules¶

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Schedule Primitives in TVM¶

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Intrinsics and Math Functions¶

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Scan and Recurrent Kernel¶

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External Tensor Functions¶

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Use Tensorize to Leverage Hardware Intrinsics¶

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Compute and Reduce with Tuple Inputs¶

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Use Tensor Expression Debug Display (TEDD) for Visualization¶

Optimize Tensor Operators¶

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How to optimize GEMM on CPU¶

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How to optimize convolution on GPU¶

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How to optimize convolution using TensorCores¶

AutoTVM : Template-based Auto Tuning¶

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Tuning High Performance Convolution on NVIDIA GPUs¶

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Auto-tuning a Convolutional Network for NVIDIA GPU¶

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Auto-tuning a Convolutional Network for x86 CPU¶

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Auto-tuning a Convolutional Network for ARM CPU¶

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Auto-tuning a Convolutional Network for Mobile GPU¶

AutoScheduler : Template-free Auto Scheduling¶

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Auto-scheduling a Convolution Layer for GPU¶

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Auto-scheduling a Neural Network for x86 CPU¶

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Auto-scheduling a Neural Network for NVIDIA GPU¶

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Auto-scheduling a Neural Network for ARM CPU¶

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Auto-scheduling a Neural Network for mali GPU¶

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Auto-scheduling Sparse Matrix Multiplication on CPU with Custom Sketch Rule¶

Developer Tutorials¶

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Writing a Customized Pass¶

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How to Use TVM Pass Infra¶

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How to Use TVM Pass Instrument¶

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Bring Your Own Datatypes to TVM¶

TOPI: TVM Operator Inventory¶

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Introduction to TOPI¶

microTVM¶

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Autotuning with micro TVM¶

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microTVM Reference Virtual Machines¶

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microTVM with TFLite Models¶

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