This was stored in LiveIntervals, but not actually used for anything
related to LiveIntervals. It was only used in one check for if a load
instruction is rematerializable. I also don't think this was entirely
correct, since it was implicitly assuming constant loads are also
dereferenceable.
Remove this and rely only on the invariant+dereferenceable flags in
the memory operand. Set the flag based on the AA query upfront. This
should have the same net benefit, but has the possible disadvantage of
making this AA query nonlazy.
Preserve the behavior of assuming pointsToConstantMemory implying
dereferenceable for now, but maybe this should be changed.
This reverts commit 7f230feeeac8a67b335f52bd2e900a05c6098f20.
Breaks CodeGenCUDA/link-device-bitcode.cu in check-clang,
and many LLVM tests, see comments on https://reviews.llvm.org/D121169
Add the calculation of a score, which will be used during ML training. The
score qualifies the quality of a regalloc policy, and is independent of
what we train (currently, just eviction), or the regalloc algo itself.
We can then use scores to guide training (which happens offline), by
formulating a reward based on score variation - the goal being lowering
scores (currently, that reward is percentage reduction relative to
Greedy's heuristic)
Currently, we compute the score by factoring different instruction
counts (loads, stores, etc) with the machine basic block frequency,
regardless of the instructions' provenance - i.e. they could be due to
the regalloc policy or be introduced previously. This is different from
RAGreedy::reportStats, which accummulates the effects of the allocator
alone. We explored this alternative but found (at least currently) that
the more naive alternative introduced here produces better policies. We
do intend to consolidate the two, however, as we are actively
investigating improvements to our reward function, and will likely want
to re-explore scoring just the effects of the allocator.
In either case, we want to decouple score calculation from allocation
algorighm, as we currently evaluate it after a few more passes after
allocation (also, because score calculation should be reusable
regardless of allocation algorithm).
We intentionally accummulate counts independently because it facilitates
per-block reporting, which we found useful for debugging - for instance,
we can easily report the counts indepdently, and then cross-reference
with perf counter measurements.
Differential Revision: https://reviews.llvm.org/D115195
