出版物

TVM 是作为机器学习编译器框架在 CPU、GPU 和机器学习加速器领域的同行评审研究的一部分而开发的。

本文档包含了对描述使用 TVM 或基于 TVM 构建的研究、成果和设计的出版物的引用。

2018

• TVM: An Automated End-to-End Optimizing Compiler for Deep Learning, [Slides]

• Learning to Optimize Tensor Programs, [Slides]

2020

• Ansor: Generating High-Performance Tensor Programs for Deep Learning, [Slides] [Tutorial]

2021

• Nimble: Efficiently Compiling Dynamic Neural Networks for Model Inference, [Slides]

• Cortex: A Compiler for Recursive Deep Learning Models, [Slides]

• UNIT: Unifying Tensorized Instruction Compilation, [Slides]

• Lorien: Efficient Deep Learning Workloads Delivery, [Slides]

• Bring Your Own Codegen to Deep Learning Compiler, [Slides] [Tutorial]

2022

• DietCode: Automatic optimization for dynamic tensor program, [Slides]

• Bolt: Bridging the Gap between Auto-tuners and Hardware-native Performance, [Slides]

• The CoRa Tensor Compiler: Compilation for Ragged Tensors with Minimal Padding, [Slides]