High-level programming languages often rely on interpretation or compilation schemes that are ill-suited for hardware accelerators like GPUs: These devices typically require statically compiled, straight-line code in order to reach acceptable performance. The high-level Julia programming language takes a different approach, by combining careful language design with an LLVM-based JIT compiler to generate high-quality machine code.
In this talk, I will show how we’ve used that capability to build a GPU back-end for the Julia language, and explain the underlying techniques that make it happen, including a high-level Julia wrapper for the LLVM libraries, and interfaces to share functionality with the existing Julia code generator. I will also demonstrate some of the powerful abstractions that we have built on top of this infrastructure.
