[clang] [llvm] [CMake][PGO] Build Sema.cpp to generate profdata for PGO builds (PR #77347)

[Tom Stellard via cfe-commits]

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@@ -26,9 +30,23 @@ if(LLVM_BUILD_INSTRUMENTED)
     message(STATUS "To enable merging PGO data LLVM_PROFDATA has to point to llvm-profdata")
   else()
     add_custom_target(generate-profdata
-      COMMAND "${Python3_EXECUTABLE}" ${CMAKE_CURRENT_SOURCE_DIR}/perf-helper.py merge ${LLVM_PROFDATA} ${CMAKE_CURRENT_BINARY_DIR}/clang.profdata ${CMAKE_CURRENT_BINARY_DIR}
+      COMMAND "${Python3_EXECUTABLE}" ${CMAKE_CURRENT_SOURCE_DIR}/perf-helper.py merge ${LLVM_PROFDATA} ${CMAKE_CURRENT_BINARY_DIR}/clang.profdata ${CMAKE_CURRENT_BINARY_DIR} ${CMAKE_BINARY_DIR}/profiles/
       COMMENT "Merging profdata"
       DEPENDS generate-profraw)
+    if (CLANG_PGO_TRAINING_DATA_SOURCE_DIR)
+      llvm_ExternalProject_Add(generate-profraw-external ${CLANG_PGO_TRAINING_DATA_SOURCE_DIR}
+              USE_TOOLCHAIN EXLUDE_FROM_ALL NO_INSTALL DEPENDS generate-profraw)
+      add_dependencies(generate-profdata generate-profraw-external)
+    else()
+      # Default to compiling a file from clang. This also builds all the
+      # dependencies needed to build this file, like TableGen.
+      set(generate_profraw_clang_sema tools/clang/lib/Sema/CMakeFiles/obj.clangSema.dir/Sema.cpp.o)
+      llvm_ExternalProject_Add(generate-profraw-clang ${CMAKE_CURRENT_SOURCE_DIR}/../../../llvm
+              USE_TOOLCHAIN EXLUDE_FROM_ALL NO_INSTALL DEPENDS generate-profraw
+              EXTRA_TARGETS generate_profraw_clang_sema
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tstellar wrote:

> If you're not concerned about the efficacy of the PGO build, I'm not sure why the existing single hello_world is a bad default. It isn't great but it is stable and something. If you want something that gives better performance then you must care about the efficacy, and I think you need to be somewhat concerned about the stability of those results, otherwise what's the point?

I'm concerned about the efficacy if it is 0%, but not really concerned if it bounces around between say 10 and 25 % based on updates to the file we are using to train.

I tested with the existing default (hello_world) and I didn't see any performance improvements from that.  We also did some manual builds (not using the 2-stage PGO cache) and could not get any performance gains for using a hello world source.  How certain are we that hello_world is enough to get performance improvements from PGO?  Has anyone tested this recently?  I will re-run my tests just to double check.

https://github.com/llvm/llvm-project/pull/77347