When computing a range for a SCEVUnknown, today we use computeKnownBits for unsigned ranges, and computeNumSignBots for signed ranges. This means we miss opportunities to improve range results.
One common missed pattern is that we have a signed range of a value which CKB can determine is positive, but CNSB doesn't convey that information. The current range includes the negative part, and is thus double the size.
Per the removed comment, the original concern which delayed using both (after some code merging years back) was a compile time concern. CTMark results (provided by Nikita, thanks!) showed a geomean impact of about 0.1%. This doesn't seem large enough to avoid higher quality results.
Differential Revision: https://reviews.llvm.org/D96534
Many tests use opt's -analyze feature, which does not translate well to
NPM and has better alternatives. The alternative here is to explicitly
add a pass that calls ScalarEvolution::print().
The legacy pass manager RUNs aren't changing, but they are now pinned to
the legacy pass manager. For each legacy pass manager RUN, I added a
corresponding NPM RUN using the 'print<scalar-evolution>' pass. For
compatibility with update_analyze_test_checks.py and existing test
CHECKs, 'print<scalar-evolution>' now prints what -analyze prints per
function.
This was generated by the following Python script and failures were
manually fixed up:
import sys
for i in sys.argv:
with open(i, 'r') as f:
s = f.read()
with open(i, 'w') as f:
for l in s.splitlines():
if "RUN:" in l and ' -analyze ' in l and '\\' not in l:
f.write(l.replace(' -analyze ', ' -analyze -enable-new-pm=0 '))
f.write('\n')
f.write(l.replace(' -analyze ', ' -disable-output ').replace(' -scalar-evolution ', ' "-passes=print<scalar-evolution>" ').replace(" | ", " 2>&1 | "))
f.write('\n')
else:
f.write(l)
There are a couple failures still in ScalarEvolution under NPM, but
those are due to other unrelated naming conflicts.
Reviewed By: asbirlea
Differential Revision: https://reviews.llvm.org/D83798
Max backedge taken count is always expected to be a constant; and this is
usually true by construction -- it is a SCEV expression with constant inputs.
However, if the max backedge expression ends up being computed to be a udiv with
a constant zero denominator[0], SCEV does not fold the result to a constant
since there is no constant it can fold it to (SCEV has no representation for
"infinity" or "undef").
However, in computeMaxBECountForLT we already know the denominator is positive,
and thus at least 1; and we can use this fact to avoid dividing by zero.
[0]: We can end up with a constant zero denominator if the signed range of the
stride is more precise than the unsigned range.
llvm-svn: 316615
Philip Reames