Commit Graph

7 Commits

Author SHA1 Message Date
Diego Novillo
e75c2b3e54 Add profile writing capabilities for sampling profiles.
Summary:
This patch finishes up support for handling sampling profiles in both
text and binary formats. The new binary format uses uleb128 encoding to
represent numeric values. This makes profiles files about 25% smaller.

The profile writer class can write profiles in the existing text and the
new binary format. In subsequent patches, I will add the capability to
read (and perhaps write) profiles in the gcov format used by GCC.

Additionally, I will be adding support in llvm-profdata to manipulate
sampling profiles.

There was a bit of refactoring needed to separate some code that was in
the reader files, but is actually common to both the reader and writer.

The new test checks that reading the same profile encoded as text or
raw, produces the same results.

Reviewers: bogner, dexonsmith

Subscribers: llvm-commits

Differential Revision: http://reviews.llvm.org/D6000

git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@220915 91177308-0d34-0410-b5e6-96231b3b80d8
2014-10-30 18:00:06 +00:00
Diego Novillo
c605296342 Tolerate unmangled names in sample profiles.
Summary:
The compiler does not always generate linkage names. If a function
has been inlined and its body elided, its linkage name may not be
generated.

When the binary executes, the profiler will use its unmangled name
when attributing samples. This results in unmangled names in the
input profile.

We are currently failing hard when this happens. However, in this case
all that happens is that we fail to attribute samples to the inlined
function. While this means fewer optimization opportunities, it should
not cause a compilation failure.

This patch accepts all valid function names, regardless of whether
they were mangled or not.

Reviewers: chandlerc

CC: llvm-commits

Differential Revision: http://llvm-reviews.chandlerc.com/D3087

git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@204142 91177308-0d34-0410-b5e6-96231b3b80d8
2014-03-18 12:03:12 +00:00
Diego Novillo
87393cfd6b Use discriminator information in sample profiles.
Summary:
When the sample profiles include discriminator information,
use the discriminator values to distinguish instruction weights
in different basic blocks.

This modifies the BodySamples mapping to map <line, discriminator> pairs
to weights. Instructions on the same line but different blocks, will
use different discriminator values. This, in turn, means that the blocks
may have different weights.

Other changes in this patch:

- Add tests for positive values of line offset, discriminator and samples.
- Change data types from uint32_t to unsigned and int and do additional
  validation.

Reviewers: chandlerc

CC: llvm-commits

Differential Revision: http://llvm-reviews.chandlerc.com/D2857

git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@203508 91177308-0d34-0410-b5e6-96231b3b80d8
2014-03-10 22:41:28 +00:00
Diego Novillo
4b2b2da9c7 Extend and simplify the sample profile input file.
1- Use the line_iterator class to read profile files.

2- Allow comments in profile file. Lines starting with '#'
   are completely ignored while reading the profile.

3- Add parsing support for discriminators and indirect call samples.

   Our external profiler can emit more profile information that we are
   currently not handling. This patch does not add new functionality to
   support this information, but it allows profile files to provide it.

   I will add actual support later on (for at least one of these
   features, I need support for DWARF discriminators in Clang).

   A sample line may contain the following additional information:

   Discriminator. This is used if the sampled program was compiled with
   DWARF discriminator support
   (http://wiki.dwarfstd.org/index.php?title=Path_Discriminators). This
   is currently only emitted by GCC and we just ignore it.

   Potential call targets and samples. If present, this line contains a
   call instruction. This models both direct and indirect calls. Each
   called target is listed together with the number of samples. For
   example,

                    130: 7  foo:3  bar:2  baz:7

   The above means that at relative line offset 130 there is a call
   instruction that calls one of foo(), bar() and baz(). With baz()
   being the relatively more frequent call target.

   Differential Revision: http://llvm-reviews.chandlerc.com/D2355

4- Simplify format of profile input file.

   This implements earlier suggestions to simplify the format of the
   sample profile file. The symbol table is not necessary and function
   profiles do not need to know the number of samples in advance.

   Differential Revision: http://llvm-reviews.chandlerc.com/D2419

git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@198973 91177308-0d34-0410-b5e6-96231b3b80d8
2014-01-10 23:23:51 +00:00
Diego Novillo
0de8cecb84 Propagation of profile samples through the CFG.
This adds a propagation heuristic to convert instruction samples
into branch weights. It implements a similar heuristic to the one
implemented by Dehao Chen on GCC.

The propagation proceeds in 3 phases:

1- Assignment of block weights. All the basic blocks in the function
   are initial assigned the same weight as their most frequently
   executed instruction.

2- Creation of equivalence classes. Since samples may be missing from
   blocks, we can fill in the gaps by setting the weights of all the
   blocks in the same equivalence class to the same weight. To compute
   the concept of equivalence, we use dominance and loop information.
   Two blocks B1 and B2 are in the same equivalence class if B1
   dominates B2, B2 post-dominates B1 and both are in the same loop.

3- Propagation of block weights into edges. This uses a simple
   propagation heuristic. The following rules are applied to every
   block B in the CFG:

   - If B has a single predecessor/successor, then the weight
     of that edge is the weight of the block.

   - If all the edges are known except one, and the weight of the
     block is already known, the weight of the unknown edge will
     be the weight of the block minus the sum of all the known
     edges. If the sum of all the known edges is larger than B's weight,
     we set the unknown edge weight to zero.

   - If there is a self-referential edge, and the weight of the block is
     known, the weight for that edge is set to the weight of the block
     minus the weight of the other incoming edges to that block (if
     known).

Since this propagation is not guaranteed to finalize for every CFG, we
only allow it to proceed for a limited number of iterations (controlled
by -sample-profile-max-propagate-iterations). It currently uses the same
GCC default of 100.

Before propagation starts, the pass builds (for each block) a list of
unique predecessors and successors. This is necessary to handle
identical edges in multiway branches. Since we visit all blocks and all
edges of the CFG, it is cleaner to build these lists once at the start
of the pass.

Finally, the patch fixes the computation of relative line locations.
The profiler emits lines relative to the function header. To discover
it, we traverse the compilation unit looking for the subprogram
corresponding to the function. The line number of that subprogram is the
line where the function begins. That becomes line zero for all the
relative locations.

git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@198972 91177308-0d34-0410-b5e6-96231b3b80d8
2014-01-10 23:23:46 +00:00
Diego Novillo
e40c77d191 Add tests for profile sample file parsing.
The profile file parser needed some tests for its parsing actions.
This adds tests for each of the error messages emitted by the parser.

git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@196106 91177308-0d34-0410-b5e6-96231b3b80d8
2013-12-02 15:12:50 +00:00
Diego Novillo
563b29f8db 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
tool.

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
  SampleProfile::loadText().
- 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
2013-11-13 12:22:21 +00:00