Previous blog posts overviewed the MLIR dialect hierarchy for kernel code generation (CodeGen) and zoomed in on the Linalg and Vector dialects among them. Now I will switch to discuss the runtime side a bit, in order to provide a holistic view of MLIR-based machine learning (ML) compilers. This one touches the foundation and basics, including the target landscape, runtime requirements and designs to meet thereof.
Vulkan is designed to be both a graphics and compute API. However, there is no formal definition of the compute subset from the Khronos group, the industry consortium behind Vulkan. The unified specification of Vulkan does not help here either as it contains everything, both graphics and compute. Unlike the complicated graphics subset, the compute subset is actually quite straightforward and clean. So in this blog post I try to explain what Vulkan compute is, from my point of view.
