phosek added a comment. This was already on my list of build system features I'd like to implement and I'm glad someone else is already looking into it, thank you! I have two high level comments about your approach.
The first one is related to the use of Clang build as the training data. I think that Clang build is both unnecessarily heavyweight, but also not particularly representative of typical workloads (most Clang users don't use it to build Clang). Ideally, we would give vendors the flexibility to supply their own training data. I'd prefer reusing the existing perf-training <https://github.com/llvm/llvm-project/tree/main/clang/utils/perf-training> setup to do so. In fact, I'd imagine most vendors would likely use the same training data for both PGO and BOLT and that use case should be supported. The second one is related to applicability. I don't think this mechanism should be limited only to Clang. Ideally, it should be possible to instrument and optimize other tools in the toolchain distribution as well; LLD is likely going to be the most common one after Clang. Repository: rG LLVM Github Monorepo CHANGES SINCE LAST ACTION https://reviews.llvm.org/D132975/new/ https://reviews.llvm.org/D132975 _______________________________________________ cfe-commits mailing list cfe-commits@lists.llvm.org https://lists.llvm.org/cgi-bin/mailman/listinfo/cfe-commits
