This is to be consistent with StringSet and ultimately with the standard
library's associative container insert function.
This lead to updating SmallSet::insert to return pair<iterator, bool>,
and then to update SmallPtrSet::insert to return pair<iterator, bool>,
and then to update all the existing users of those functions...
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This fixes the autobuilders I broke with a recent patch. Thanks echristo
and dblaikie for beating me with a clue stick.
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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
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When the profile for a function cannot be applied, we use to emit an
error. This seems extreme. The compiler can continue, it's just that the
optimization opportunities won't include profile information.
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Summary:
When using a profile, we used to require the use -gmlt so that we could
get access to the line locations. This is used to match line numbers in
the input profile to the line numbers in the function's IR.
But this is actually not necessary. The driver can provide source
location tracking without the emission of debug information. In these
cases, the annotation 'llvm.dbg.cu' is missing from the IR, but the
actual line location annotations are still present.
This patch adds a new way of looking for the start of the current
function. Instead of looking through the compile units in llvm.dbg.cu,
we can walk up the scope for the first instruction in the function with
a debug loc. If that describes the function, we use it. Otherwise, we
keep looking until we find one.
If no such instruction is found, we then give up and produce an error.
Reviewers: echristo, dblaikie
Subscribers: llvm-commits
Differential Revision: http://reviews.llvm.org/D5887
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Summary:
This patch moves the profile reading logic out of the Sample Profile
transformation into a generic profile reader facility in
lib/ProfileData.
The intent is to use this new reader to implement a sample profile
reader/writer that can be used to convert sample profiles from external
sources into LLVM.
This first patch introduces no functional changes. It moves the profile
reading code from lib/Transforms/SampleProfile.cpp into
lib/ProfileData/SampleProfReader.cpp.
In subsequent patches I will:
- Add a bitcode format for sample profiles to allow for more efficient
encoding of the profile.
- Add a writer for both text and bitcode format profiles.
- Add a 'convert' command to llvm-profdata to be able to convert between
the two (and serve as entry point for other sample profile formats).
Reviewers: bogner, echristo
Subscribers: llvm-commits
Differential Revision: http://reviews.llvm.org/D5250
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Instead of moving out the data in a ErrorOr<std::unique_ptr<Foo>>, get
a reference to it.
Thanks to David Blaikie for the suggestion.
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This reverts commit r213474 (and r213475), which causes a miscompile on
a stage2 LTO build. I'll reply on the list in a moment.
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Summary: This patch introduces two new iterator ranges and updates existing code to use it. No functional change intended.
Test Plan: All tests (make check-all) still pass.
Reviewers: dblaikie
Reviewed By: dblaikie
Subscribers: llvm-commits
Differential Revision: http://reviews.llvm.org/D4481
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definition below all of the header #include lines, lib/Transforms/...
edition.
This one is tricky for two reasons. We again have a couple of passes
that define something else before the includes as well. I've sunk their
name macros with the DEBUG_TYPE.
Also, InstCombine contains headers that need DEBUG_TYPE, so now those
headers #define and #undef DEBUG_TYPE around their code, leaving them
well formed modular headers. Fixing these headers was a large motivation
for all of these changes, as "leaky" macros of this form are hard on the
modules implementation.
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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
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Summary:
The sample profiler pass emits several error messages. Instead of
just aborting the compiler with report_fatal_error, we can emit
better messages using DiagnosticInfo.
This adds a new sub-class of DiagnosticInfo to handle the sample
profiler.
Reviewers: chandlerc, qcolombet
CC: llvm-commits
Differential Revision: http://llvm-reviews.chandlerc.com/D3086
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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
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This compiles with no changes to clang/lld/lldb with MSVC and includes
overloads to various functions which are used by those projects and llvm
which have OwningPtr's as parameters. This should allow out of tree
projects some time to move. There are also no changes to libs/Target,
which should help out of tree targets have time to move, if necessary.
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business.
This header includes Function and BasicBlock and directly uses the
interfaces of both classes. It has to do with the IR, it even has that
in the name. =] Put it in the library it belongs to.
This is one step toward making LLVM's Support library survive a C++
modules bootstrap.
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can be used by both the new pass manager and the old.
This removes it from any of the virtual mess of the pass interfaces and
lets it derive cleanly from the DominatorTreeBase<> template. In turn,
tons of boilerplate interface can be nuked and it turns into a very
straightforward extension of the base DominatorTree interface.
The old analysis pass is now a simple wrapper. The names and style of
this split should match the split between CallGraph and
CallGraphWrapperPass. All of the users of DominatorTree have been
updated to match using many of the same tricks as with CallGraph. The
goal is that the common type remains the resulting DominatorTree rather
than the pass. This will make subsequent work toward the new pass
manager significantly easier.
Also in numerous places things became cleaner because I switched from
re-running the pass (!!! mid way through some other passes run!!!) to
directly recomputing the domtree.
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directory. These passes are already defined in the IR library, and it
doesn't make any sense to have the headers in Analysis.
Long term, I think there is going to be a much better way to divide
these matters. The dominators code should be fully separated into the
abstract graph algorithm and have that put in Support where it becomes
obvious that evn Clang's CFGBlock's can use it. Then the verifier can
manually construct dominance information from the Support-driven
interface while the Analysis library can provide a pass which both
caches, reconstructs, and supports a nice update API.
But those are very long term, and so I don't want to leave the really
confusing structure until that day arrives.
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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
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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.
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subsequent changes are easier to review. About to fix some layering
issues, and wanted to separate out the necessary churn.
Also comment and sink the include of "Windows.h" in three .inc files to
match the usage in Memory.inc.
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I'm adding new functionality in the sample profiler. This will
require more data to be kept around for each function, so I moved
the structure SampleProfile that we keep for each function into
a separate class.
There are no functional changes in this patch. It simply provides
a new home where to place all the new data that I need to propagate
weights through edges.
There are some other name and minor edits throughout.
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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.
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