Just-in-time (JIT) compilation can take advantage of information only known once an application starts running in order to produce very-high-performance code. LLVM is well known for supporting JIT compilation, and moreover, Clang, LLVM's best-in-class C++ frontend, enables the highly-optimized compilation of C++ code. Clang, however, uses purely an ahead-of-time compilation model, and so we leave on the table performance which might come from dynamic specialization. In this talk, I'll describe ClangJIT, an enhancement to Clang, and an extension to the C++ language, which brings JIT-compilation capabilities to the C++ ecosystem. Critically, ClangJIT enables the dynamic, incremental creation of new template instantiations. This can provide important performance benefits, and in addition, can decrease overall application compile times. I'll describe how Clang was enhanced to support this feature - what I needed to do to turn Clang into an incremental C++ compilation library - and how LLVM's JIT infrastructure was leveraged. ClangJIT supports Clang's CUDA mode, and how that works will be described. Some application use cases will be highlighted and I'll discuss some future directions.
