KubeCon + CloudNativeCon + Open Source Summit + AI_dev China 2024

In recent years WASM has been one of the hottest topics in the world of computing due to its portability, small size, fast loading, and compatibility. And given these advantages, WebAssembly is an ideal technology based on sandbox schemes for modern applications including ML/AI. But beyond the browser, currently WebAssembly only can leverage CPU to accelerate ML/AI mostly. Here we offer a flexible way to make running ML/AI on WebAssembly over a variety of AI Accelerators by empowering WASM with a transparent backend interposer. With this, your native ML/AI WebAssembly workloads can seamlessly enjoy the underlying AI accelerators such as CPU, GPU, FPGA and so on, with best performance. During this presentation we also would like to show our latest implementation with demos to help users get direct insight of running ML/AI with WebAssembly on AI accelerators.

近年来，由于其可移植性、体积小、加载速度快和兼容性等优势，WASM已成为计算领域最热门的话题之一。鉴于这些优势，WebAssembly是基于沙箱方案的现代应用程序，包括ML/AI的理想技术。但除了浏览器之外，目前WebAssembly只能利用CPU来加速大部分ML/AI。在这里，我们提供了一种灵活的方式，通过为WASM赋予一个透明的后端插入器，使其能够在各种AI加速器上运行ML/AI。借助这一技术，您的本地ML/AI WebAssembly工作负载可以无缝地享受CPU、GPU、FPGA等底层AI加速器的最佳性能。在本次演示中，我们还将展示我们最新的实现，并通过演示帮助用户直观了解在AI加速器上运行ML/AI的WebAssembly。