History log of /external/llvm/lib/Transforms/Scalar/SampleProfile.cpp
Revision Date Author Comments (<<< Hide modified files) (Show modified files >>>)
cd81d94322a39503e4a3e87b6ee03d4fcb3465fb 21-Jul-2014 Stephen Hines <srhines@google.com> Update LLVM for rebase to r212749.

Includes a cherry-pick of:
r212948 - fixes a small issue with atomic calls

Change-Id: Ib97bd980b59f18142a69506400911a6009d9df18
dce4a407a24b04eebc6a376f8e62b41aaa7b071f 29-May-2014 Stephen Hines <srhines@google.com> Update LLVM for 3.5 rebase (r209712).

Change-Id: I149556c940fb7dc92d075273c87ff584f400941f
36b56886974eae4f9c5ebc96befd3e7bfe5de338 24-Apr-2014 Stephen Hines <srhines@google.com> Update to LLVM 3.5a.

Change-Id: Ifadecab779f128e62e430c2b4f6ddd84953ed617
4223b9601058369536caa1d15c9c19bc7c5a3706 13-Nov-2013 Alexey Samsonov <samsonov@google.com> Fix -Wdelete-non-virtual-dtor warnings by making SampleProfile methods non-virtual

git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@194568 91177308-0d34-0410-b5e6-96231b3b80d8
563b29f8db68275407ffcd2a9a5f0ba77ee5e899 13-Nov-2013 Diego Novillo <dnovillo@google.com> SampleProfileLoader pass. Initial setup.

This adds a new scalar pass that reads a file with samples generated
by 'perf' during runtime. The samples read from the profile are
incorporated and emmited as IR metadata reflecting that profile.

The profile file is assumed to have been generated by an external
profile source. The profile information is converted into IR metadata,
which is later used by the analysis routines to estimate block
frequencies, edge weights and other related data.

External profile information files have no fixed format, each profiler
is free to define its own. This includes both the on-disk representation
of the profile and the kind of profile information stored in the file.
A common kind of profile is based on sampling (e.g., perf), which
essentially counts how many times each line of the program has been
executed during the run.

The SampleProfileLoader pass is organized as a scalar transformation.
On startup, it reads the file given in -sample-profile-file to
determine what kind of profile it contains. This file is assumed to
contain profile information for the whole application. The profile
data in the file is read and incorporated into the internal state of
the corresponding profiler.

To facilitate testing, I've organized the profilers to support two file
formats: text and native. The native format is whatever on-disk
representation the profiler wants to support, I think this will mostly
be bitcode files, but it could be anything the profiler wants to
support. To do this, every profiler must implement the
SampleProfile::loadNative() function.

The text format is mostly meant for debugging. Records are separated by
newlines, but each profiler is free to interpret records as it sees fit.
Profilers must implement the SampleProfile::loadText() function.

Finally, the pass will call SampleProfile::emitAnnotations() for each
function in the current translation unit. This function needs to
translate the loaded profile into IR metadata, which the analyzer will
later be able to use.

This patch implements the first steps towards the above design. I've
implemented a sample-based flat profiler. The format of the profile is
fairly simplistic. Each sampled function contains a list of relative
line locations (from the start of the function) together with a count
representing how many samples were collected at that line during
execution. I generate this profile using perf and a separate converter

Currently, I have only implemented a text format for these profiles. I
am interested in initial feedback to the whole approach before I send
the other parts of the implementation for review.

This patch implements:

- The SampleProfileLoader pass.
- The base ExternalProfile class with the core interface.
- A SampleProfile sub-class using the above interface. The profiler
generates branch weight metadata on every branch instructions that
matches the profiles.
- A text loader class to assist the implementation of
- Basic unit tests for the pass.

Additionally, the patch uses profile information to compute branch
weights based on instruction samples.

This patch converts instruction samples into branch weights. It
does a fairly simplistic conversion:

Given a multi-way branch instruction, it calculates the weight of
each branch based on the maximum sample count gathered from each
target basic block.

Note that this assignment of branch weights is somewhat lossy and can be
misleading. If a basic block has more than one incoming branch, all the
incoming branches will get the same weight. In reality, it may be that
only one of them is the most heavily taken branch.

I will adjust this assignment in subsequent patches.

git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@194566 91177308-0d34-0410-b5e6-96231b3b80d8