This changes the on-disk hash to get the type to use for offsets from
the Info type, so that clients can be more flexible with the size of
table they support.
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@206643 91177308-0d34-0410-b5e6-96231b3b80d8
This changes the on-disk hash to get the size of a hash value from the
Info type, so that clients can be more flexible with the types of hash
they use.
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@206642 91177308-0d34-0410-b5e6-96231b3b80d8
This warning is disabled for the LLVM build,
but external users of the header can still
run into this.
Patch by Ke Bai
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This reverts commit r206622 and the MSVC fixup in r206626.
Apparently the remotely failing tests are still failing, despite my
attempt to fix the nondeterminism in r206621.
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This reverts commit r206556, effectively reapplying commit r206548 and
its fixups in r206549 and r206550.
In an intervening commit I've added target triples to the tests that
were failing remotely [1] (but passing locally). I'm hoping the mystery
is solved? I'll revert this again if the tests are still failing
remotely.
[1]: http://bb.pgr.jp/builders/ninja-x64-msvc-RA-centos6/builds/1816
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Doesn't make sense to restrict this to BumpPtrAllocator. While there
replace an explicit loop with std::equal. Some standard libraries know
how to compile this down to a ::memcmp call if possible.
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Reality is that we're never going to copy one of these. Supporting this
was becoming a nightmare because nothing even causes it to compile most
of the time. Lots of subtle errors built up that wouldn't have been
caught by any "normal" testing.
Also, make the move assignment actually work rather than the bogus swap
implementation that would just infloop if used. As part of that, factor
out the graph pointer updates into a helper to share between move
construction and move assignment.
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implementation of the SpecificBumpPtrAllocator -- we have to actually
move the subobject. =] Noticed when using this code more directly.
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LazyCallGraph. This is the start of the whole point of this different
abstraction, but it is just the initial bits. Here is a run-down of
what's going on here. I'm planning to incorporate some (or all) of this
into comments going forward, hopefully with better editing and wording.
=]
The crux of the problem with the traditional way of building SCCs is
that they are ephemeral. The new pass manager however really needs the
ability to associate analysis passes and results of analysis passes with
SCCs in order to expose these analysis passes to the SCC passes. Making
this work is kind-of the whole point of the new pass manager. =]
So, when we're building SCCs for the call graph, we actually want to
build persistent nodes that stick around and can be reasoned about
later. We'd also like the ability to walk the SCC graph in more complex
ways than just the traditional postorder traversal of the current CGSCC
walk. That means that in addition to being persistent, the SCCs need to
be connected into a useful graph structure.
However, we still want the SCCs to be formed lazily where possible.
These constraints are quite hard to satisfy with the SCC iterator. Also,
using that would bypass our ability to actually add data to the nodes of
the call graph to facilite implementing the Tarjan walk. So I've
re-implemented things in a more direct and embedded way. This
immediately makes it easy to get the persistence and connectivity
correct, and it also allows leveraging the existing nodes to simplify
the algorithm. I've worked somewhat to make this implementation more
closely follow the traditional paper's nomenclature and strategy,
although it is still a bit obtuse because it isn't recursive, using
an explicit stack and a tail call instead, and it is interruptable,
resuming each time we need another SCC.
The other tricky bit here, and what actually took almost all the time
and trials and errors I spent building this, is exactly *what* graph
structure to build for the SCCs. The naive thing to build is the call
graph in its newly acyclic form. I wrote about 4 versions of this which
did precisely this. Inevitably, when I experimented with them across
various use cases, they became incredibly awkward. It was all
implementable, but it felt like a complete wrong fit. Square peg, round
hole. There were two overriding aspects that pushed me in a different
direction:
1) We want to discover the SCC graph in a postorder fashion. That means
the root node will be the *last* node we find. Using the call-SCC DAG
as the graph structure of the SCCs results in an orphaned graph until
we discover a root.
2) We will eventually want to walk the SCC graph in parallel, exploring
distinct sub-graphs independently, and synchronizing at merge points.
This again is not helped by the call-SCC DAG structure.
The structure which, quite surprisingly, ended up being completely
natural to use is the *inverse* of the call-SCC DAG. We add the leaf
SCCs to the graph as "roots", and have edges to the caller SCCs. Once
I switched to building this structure, everything just fell into place
elegantly.
Aside from general cleanups (there are FIXMEs and too few comments
overall) that are still needed, the other missing piece of this is
support for iterating across levels of the SCC graph. These will become
useful for implementing #2, but they aren't an immediate priority.
Once SCCs are in good shape, I'll be working on adding mutation support
for incremental updates and adding the pass manager that this analysis
enables.
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Previously module verification was always enabled, with no way to turn it off.
As of this commit, module verification is on by default in Debug builds, and off
by default in release builds. The default behaviour can be overridden by calling
setVerifyModules(bool) on the JIT instance (this works for both the old JIT, and
MCJIT).
<rdar://problem/16150008>
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Rewrite the shared implementation of BlockFrequencyInfo and
MachineBlockFrequencyInfo entirely.
The old implementation had a fundamental flaw: precision losses from
nested loops (or very wide branches) compounded past loop exits (and
convergence points).
The @nested_loops testcase at the end of
test/Analysis/BlockFrequencyAnalysis/basic.ll is motivating. This
function has three nested loops, with branch weights in the loop headers
of 1:4000 (exit:continue). The old analysis gives non-sensical results:
Printing analysis 'Block Frequency Analysis' for function 'nested_loops':
---- Block Freqs ----
entry = 1.0
for.cond1.preheader = 1.00103
for.cond4.preheader = 5.5222
for.body6 = 18095.19995
for.inc8 = 4.52264
for.inc11 = 0.00109
for.end13 = 0.0
The new analysis gives correct results:
Printing analysis 'Block Frequency Analysis' for function 'nested_loops':
block-frequency-info: nested_loops
- entry: float = 1.0, int = 8
- for.cond1.preheader: float = 4001.0, int = 32007
- for.cond4.preheader: float = 16008001.0, int = 128064007
- for.body6: float = 64048012001.0, int = 512384096007
- for.inc8: float = 16008001.0, int = 128064007
- for.inc11: float = 4001.0, int = 32007
- for.end13: float = 1.0, int = 8
Most importantly, the frequency leaving each loop matches the frequency
entering it.
The new algorithm leverages BlockMass and PositiveFloat to maintain
precision, separates "probability mass distribution" from "loop
scaling", and uses dithering to eliminate probability mass loss. I have
unit tests for these types out of tree, but it was decided in the review
to make the classes private to BlockFrequencyInfoImpl, and try to shrink
them (or remove them entirely) in follow-up commits.
The new algorithm should generally have a complexity advantage over the
old. The previous algorithm was quadratic in the worst case. The new
algorithm is still worst-case quadratic in the presence of irreducible
control flow, but it's linear without it.
The key difference between the old algorithm and the new is that control
flow within a loop is evaluated separately from control flow outside,
limiting propagation of precision problems and allowing loop scale to be
calculated independently of mass distribution. Loops are visited
bottom-up, their loop scales are calculated, and they are replaced by
pseudo-nodes. Mass is then distributed through the function, which is
now a DAG. Finally, loops are revisited top-down to multiply through
the loop scales and the masses distributed to pseudo nodes.
There are some remaining flaws.
- Irreducible control flow isn't modelled correctly. LoopInfo and
MachineLoopInfo ignore irreducible edges, so this algorithm will
fail to scale accordingly. There's a note in the class
documentation about how to get closer. See also the comments in
test/Analysis/BlockFrequencyInfo/irreducible.ll.
- Loop scale is limited to 4096 per loop (2^12) to avoid exhausting
the 64-bit integer precision used downstream.
- The "bias" calculation proposed on llvmdev is *not* incorporated
here. This will be added in a follow-up commit, once comments from
this review have been handled.
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@206548 91177308-0d34-0410-b5e6-96231b3b80d8
Summary:
This prevents the discriminator generation pass from triggering if
the DWARF version being used in the module is prior to 4.
Reviewers: echristo, dblaikie
CC: llvm-commits
Differential Revision: http://reviews.llvm.org/D3413
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Still only 32-bit ARM using it at this stage, but the promotion allows
direct testing via opt and is a reasonably self-contained patch on the
way to switching ARM64.
At this point, other targets should be able to make use of it without
too much difficulty if they want. (See ARM64 commit coming soon for an
example).
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to a more normal move operation on the graph itself. The definition
already got removed, but I missed the declaration.
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This will become necessary to build up the SCC iterators and SCC
definitions. Moving it now so that subsequent diffs are incremental.
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this code ages ago and lost track of it. Seems worth doing though --
this thing can get called from places that would benefit from knowing
that std::distance is O(1). Also add a very fledgeling unittest for
Users and make sure various aspects of this seem to work reasonably.
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graph. This simplifies the custom move constructor operation to one of
walking the graph and updating the 'up' pointers to point to the new
location of the graph. Switch the nodes from a reference to a pointer
for the 'up' edge to facilitate this.
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This introduces clang's Basic/OnDiskHashTable.h into llvm as
Support/OnDiskHashTable.h. I've taken the opportunity to add doxygen
comments and run the file through clang-format, but other than the
namespace changing from clang:: to llvm:: the API is identical.
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This is so that EF_MIPS_NAN2008 is set if we are using IEEE 754-2008
NaN encoding (-mnan=2008). This patch also adds support for parsing
'.nan legacy' and '.nan 2008' assembly directives. The handling of
these directives should match GAS' behaviour i.e., the last directive
in use sets the ELF header bit (EF_MIPS_NAN2008).
Differential Revision: http://reviews.llvm.org/D3346
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It doesn't work. I'm still cleaning up all the places where I blindly
followed this pattern. There are more to come in this code too.
As a benefit, this lets the default copy and move operations Just Work.
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a default argument. The allocator interface we're modeling doesn't
distinguish between array and non-array allocation.
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because there is another (size_t, size_t) overload of Allocator, and the
only distinguishing factor is that one is a tempalte and the other
isn't. There was only one usage of this and that one was easily
converted to carry the alignment constraint in the type itself.
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Implement DebugInfoVerifier, which steals verification relying on
DebugInfoFinder from Verifier.
- Adds LegacyDebugInfoVerifierPassPass, a ModulePass which wraps
DebugInfoVerifier. Uses -verify-di command-line flag.
- Change verifyModule() to invoke DebugInfoVerifier as well as
Verifier.
- Add a call to createDebugInfoVerifierPass() wherever there was a
call to createVerifierPass().
This implementation as a module pass should sidestep efficiency issues,
allowing us to turn debug info verification back on.
<rdar://problem/15500563>
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ARM64 suffered multiple -verify-machineinstr failures (principally over the
xsp/xzr issue) because FastISel was completely ignoring which subset of the
general-purpose registers each instruction required.
More fixes are coming in ARM64 specific FastISel, but this should cover the
generic problems.
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by removing the MallocSlabAllocator entirely and just using
MallocAllocator directly. This makes all off these allocators expose and
utilize the same core interface.
The only ugly part of this is that it exposes the fact that the JIT
allocator has no real handling of alignment, any more than the malloc
allocator does. =/ It would be nice to fix both of these to support
alignments, and then to leverage that in the BumpPtrAllocator to do less
over allocation in order to manually align pointers. But, that's another
patch for another day. This patch has no functional impact, it just
removes the somewhat meaningless wrapper around MallocAllocator.
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allocation libraries, may allow more efficient allocation and
deallocation. It at least makes the interface implementable by the JIT
memory manager.
However, this highlights problematic overloading between the void* and
the T* deallocation functions. I'm looking into a better way to do this,
but as it happens, it comes up rarely in the codebase.
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overloads. This doesn't matter *that* much yet, but it will in
a subsequent patch. I had tested the original pattern, but not my
attempt to pacify MSVC. This at least appears to work. Still fixing the
rest of the fallout in the final patch that uses these overloads, but it
will follow shortly.
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'sizeof(T)' for T == void and produces a hard error. I cannot fathom why
this is OK. Oh well. switch to an explicit test for being the
(potentially qualified) void type, which is the only specific case I was
worried about. Hopefully this survives the libstdc++ build bots which
have limited type traits implementations...
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