Machine Learning with Wasm (wasi-nn) - Andrew Brown & Mingqiu Sun, Intel

WebAssembly provides an ideal portable form of deployment for machine learning models. Although a whole machine learning framework could be potentially compiled into Wasm, special hardware acceleration is often needed in order to be performant, which is difficult to do within Wasm with the limited support of parallelism. WASI-NN is a Web Assembly System Interface (WASI) module that allows for near-native performance on a variety of devices such as CPU with AVX512, GPU, TPU, and FPGA. In this talk, we will present the WASI-NN interface design and a reference implementation in Wasmtime. We will provide a step-by-step guide and a demo on how to build all relevant components, and write an image classification application with sample code in Rust and AssemblyScript. We will also demonstrate the performance advantages of WASI-NN over alternative approaches.

#wasm #webassembly #machine-learning #rust