Summary:
Detect when the working set size of a profiled application is huge,
by comparing the number of counts required to reach the hot percentile
in the profile summary to a large threshold*.
When the working set size is determined to be huge, disable peeling
to avoid bloating the working set further.
*Note that the selected threshold (15K) is significantly larger than the
largest working set value in SPEC cpu2006 (which is gcc at around 11K).
Reviewers: davidxl
Subscribers: mehdi_amini, mzolotukhin, eraman, llvm-commits
Differential Revision: https://reviews.llvm.org/D36288
llvm-svn: 310005
Summary:
Peeling should not occur during the full unrolling invocation early
in the pipeline, but rather later with partial and runtime loop
unrolling. The later loop unrolling invocation will also eventually
utilize profile summary and branch frequency information, which
we would like to use to control peeling. And for ThinLTO we want
to delay peeling until the backend (post thin link) phase, just as
we do for most types of unrolling.
Ensure peeling doesn't occur during the full unrolling invocation
by adding a parameter to the shared implementation function, similar
to the way partial and runtime loop unrolling are disabled.
Performance results for ThinLTO suggest this has a neutral to positive
effect on some internal benchmarks.
Reviewers: chandlerc, davidxl
Subscribers: mzolotukhin, llvm-commits, mehdi_amini
Differential Revision: https://reviews.llvm.org/D36258
llvm-svn: 309966
This enables peeling of loops with low dynamic iteration count by default,
when profile information is available.
Differential Revision: https://reviews.llvm.org/D27734
llvm-svn: 295796
Summary:
Regardless how the loop body weight is distributed, we should preserve
total loop body weight. i.e. we should have same weight reaching the body of the loop
or its duplicates in peeled and unpeeled case.
Reviewers: mkuper, davidxl, anemet
Subscribers: llvm-commits
Differential Revision: https://reviews.llvm.org/D28179
llvm-svn: 290833
This implements PGO-driven loop peeling.
The basic idea is that when the average dynamic trip-count of a loop is known,
based on PGO, to be low, we can expect a performance win by peeling off the
first several iterations of that loop.
Unlike unrolling based on a known trip count, or a trip count multiple, this
doesn't save us the conditional check and branch on each iteration. However,
it does allow us to simplify the straight-line code we get (constant-folding,
etc.). This is important given that we know that we will usually only hit this
code, and not the actual loop.
This is currently disabled by default.
Differential Revision: https://reviews.llvm.org/D25963
llvm-svn: 288274
Teresa Johnson