tqchen commented on a change in pull request #5892: URL: https://github.com/apache/incubator-tvm/pull/5892#discussion_r452577924
########## File path: apps/wasm-graphcompiler-tvm/README.md ########## @@ -0,0 +1,188 @@ +# WebAssembly GraphCompiler for Deep Learning Framework with TVM Runtime + +#### Experimental notice: This project is still *experimental* and only serves as a proof of concept for running deep learning frameworks (such like [MindSpore](https://github.com/mindspore-ai/mindspore)) on [WebAssembly runtime](https://github.com/bytecodealliance/wasmtime) with [TVM stack](https://tvm.apache.org/). + +- [WebAssembly GraphCompiler for Deep Learning Framework with TVM Runtime](#webassembly-graphcompiler-for-deep-learning-framework-with-tvm-runtime) + - [Motivation](#motivation) + - [Framework Landscape](#framework-landscape) + - [Project Status](#project-status) + - [PoC Guidelines](#poc-guidelines) + - [Pre-installation](#pre-installation) + - [Build ResNet50 model](#build-resnet50-model) + - [Build wasm-graphcompiler-tvm package](#build-wasm-graphcompiler-tvm-package) + - [Test](#test) + - [Future Work](#future-work) + - [More networks support](#more-networks-support) + - [Performance benchmark](#performance-benchmark) + - [Native TVM Rust runtime support](#native-tvm-rust-runtime-support) + - [Appendix](#appendix) + - [System packages install](#system-packages-install) + - [Contribution](#contribution) + +## Motivation + +<img src="https://github.com/dmlc/web-data/raw/master/tvm/tutorial/tvm_support_list.png"; alt="TVM hardware support" width="600"/> + +As demonstrated in TVM runtime [tutorials](https://tvm.apache.org/docs/tutorials/relay_quick_start.html), TVM already supports WASM as the optional hardware backend, so we can leverage the features of WebAssembly (portability, security) and TVM runtime (domain-specific, optimization) to build a flexible and auto-optimized graph compiler for all deep learning frameworks. + +## Framework Landscape + +The figures below demonstrate the whole landscape of running deep learning frameworks on WASM runtime with TVM compiler stack. + +* WASM graph compiler stack + ``` + _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ + | | | | | | + | Framework Model | ---> | ONNX Model | ---> | TVM Relay Python API | + |_ _ _ _ _ _ _ _ _ _| |_ _ _ _ _ _ _| |_ _ _ _ _ _ _ _ _ _ _ _| + || + \/ + _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ + | | | | + | WASM Graph Compiler | | TVM Compiler Stack | + | (TVM runtime) | |_ _ _ _ _ _ _ _ _ _ _| Review comment: I am not too sure about what is the purpose of Graph Compiler here, perhaps we can directly use TVM to generate the graph? ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: [email protected]
![https://github.com/dmlc/web-data/raw/master/tvm/tutorial/tvm_support_list.png"](https://github.com/dmlc/web-data/raw/master/tvm/tutorial/tvm_support_list.png"){kind=link}