Interprocedural Block Placement algorithm, challenges and opportunities


I have written a code layout feedback directed optimization pass, which currently works for basic block reordering and function reordering. It very effectively improves the speedup (we could improve Python by 30%). The profiling method is window based context sensitive which is based on reference affinity (

The pass works in the IR level. Therefore, it may lose some information during the machine code optimization passes and perform imprecisely for BB reordering.

Eventually, I would like to see the improve for an interprocedural basic block reordering pass. However, with the current system there are several challenges ahead. The most important is that the CFG is not preserved during several passes including code-gen-prepare, cfg-simplify, remove-unreachable-blocks, tail-merge, and tail-duplication. So in order to keep track of the mapping between MBBs and BBs, one needs to insert code in every function that modifies the structure of BBs and MBBs.

The current block placement pass (MachineBasicBlockPlacement) works at the machine code level and with the new profiling structure (SampleProfileLoader), is effective as far as context-free profiling info is considered sufficient. However, the implementation of SampleProfileLoader itself encourages context sensitive info, which cannot efficiently be provided with the current profiling structure (<func,lineNo>).

Is there any way to incorporate information into the emitted MBBs so that we can get IR basic block level info instead of lineNo info?


Dear Rahman,

First, if you can, try to use the mapping between BasicBlocks and MachineBasicBlocks after all LLVM IR optimizations have been done (if you are not doing that already).

Second, there are several ideas you might want to try:

1. The llvm.pcmarker() intrinsic seems close to what you need. That said, it looks like the optimizers are free to move them around any way they like, but perhaps most optimizations will leave them within the basic block in which they were originally inserted.

2. A volatile load or an llvm.prefetch instruction might be a workable hack. Alternatively, you could insert an inline assembly call which the optimizer is unlikely to move. The key here is to provide a unique argument to the each instruction you insert so that you can map it back to its original basic block.

3. You could insert an llvm.var.annotation or llvm.annotation intrinsic into each basic block and modify the code generator to recognize your annotation.

I'm not sure which of these would be the best option. I would try llvm.pcmarker first to see if that works and then move on to the other options as needed.


John Criswell

Thanks John.