wasConservativelyAllocatable() is only called to assert that a conservatively
allocatable node wasn't forced to spill.
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Remember if the node ever was in this state instead of checking just the
final state.
Reviewed by Arnaud de Grandmaison.
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The NodeMetadata are maintained in an incremental way. When an edge between
2 nodes has its cost updated, in the course of graph reduction for example,
the NodeMetadata need first to have the old edge cost removed, then the new
edge cost added. Only once the NodeMetadata have been fully updated, it
becomes safe to consider promoting the nodes to the
ConservativelyAllocatable or OptimallyReducible sets. Previously, this
promotion was occuring right after the removing the old cost, and this was
breaking the assumption that a ConservativelyAllocatable should not be
spilled.
This patch also adds asserts to:
- enforces the invariant that a node's reduction can not be downgraded,
- only not provably allocatable or optimally reducible nodes can be spilled.
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sets as keys into a cache of interference matrice values in the Interference
constraint adder.
Creating interference matrices was one of the large remaining time-sinks in
PBQP. Caching them reduces the total compile time (when using PBQP) on the
nightly test suite by ~10%.
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No functional change. This just brings things more in-line with coding
standards, and makes ValuePool's functionality clearer (it's not tied to pooling
costs, and we may want to use it to hold other things in the future).
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It is just too easy to use a virtual register intead of a NodeId without a
compiler warning. This does not fix the fundamental problem, i.e. both
have the same underlying types, but increases the likelyhood to detect it.
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implementation.
This is good for a ~6% reduction in total compile time on the nightly test suite
when running with -regalloc=pbqp.
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This patch removes the PBQPBuilder class and its subclasses and replaces them
with a composable constraints class: PBQPRAConstraint. This allows constraints
that are only required for optimisation (e.g. coalescing, soft pairing) to be
mixed and matched.
This patch also introduces support for target writers to supply custom
constraints for their targets by overriding a TargetSubtargetInfo method:
std::unique_ptr<PBQPRAConstraints> getCustomPBQPConstraints() const;
This patch should have no effect on allocations.
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in the future to attach useful information about the PBQP graph (e.g. the
associated MachineFunction, pointers to regalloc passes) to the graph itself,
making that information accessible to the solver. This should also allow the
PBQPBuilder interface to be simplified.
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Leveraging both intrusive shared_ptr-ing (std::enable_shared_from_this)
and shared_ptr<T>-owning-U (to allow external users to hold
std::shared_ptr<CostT> while keeping the underlying PoolEntry alive).
The intrusiveness could be removed if we had a weak_set that implicitly
removed items from the set when their underlying data went away.
This /might/ fix an existing memory leak reported by LeakSanitizer in
r217504.
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Add header guards to files that were missing guards. Remove #endif comments
as they don't seem common in LLVM (we can easily add them back if we decide
they're useful)
Changes made by clang-tidy with minor tweaks.
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* Use assignment instead of swap (since the original value is being
destroyed anyway)
* Rename "updateAdjEdgeId" to "setAdjEdgeId"
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The edge data structure (EdgeEntry) now holds the indices of its entries in the
adjacency lists of the nodes it connects. This trades a little ugliness for
faster insertion/removal, which is now O(1) with a cheap constant factor. All
of this is implementation detail within the PBQP graph, the external API remains
unchanged.
Individual register allocations are likely to change, since the adjacency lists
will now be ordered differently (or rather, will now be unordered). This
shouldn't affect the average quality of allocations however.
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The previous PBQP solver was very robust but consumed a lot of memory,
performed a lot of redundant computation, and contained some unnecessarily tight
coupling that prevented experimentation with novel solution techniques. This new
solver is an attempt to address these shortcomings.
Important/interesting changes:
1) The domain-independent PBQP solver class, HeuristicSolverImpl, is gone.
It is replaced by a register allocation specific solver, PBQP::RegAlloc::Solver
(see RegAllocSolver.h).
The optimal reduction rules and the backpropagation algorithm have been extracted
into stand-alone functions (see ReductionRules.h), which can be used to build
domain specific PBQP solvers. This provides many more opportunities for
domain-specific knowledge to inform the PBQP solvers' decisions. In theory this
should allow us to generate better solutions. In practice, we can at least test
out ideas now.
As a side benefit, I believe the new solver is more readable than the old one.
2) The solver type is now a template parameter of the PBQP graph.
This allows the graph to notify the solver of any modifications made (e.g. by
domain independent rules) without the overhead of a virtual call. It also allows
the solver to supply policy information to the graph (see below).
3) Significantly reduced memory overhead.
Memory management policy is now an explicit property of the PBQP graph (via
the CostAllocator typedef on the graph's solver template argument). Because PBQP
graphs for register allocation tend to contain many redundant instances of
single values (E.g. the value representing an interference constraint between
GPRs), the new RASolver class uses a uniquing scheme. This massively reduces
memory consumption for large register allocation problems. For example, looking
at the largest interference graph in each of the SPEC2006 benchmarks (the
largest graph will always set the memory consumption high-water mark for PBQP),
the average memory reduction for the PBQP costs was 400x. That's times, not
percent. The highest was 1400x. Yikes. So - this is fixed.
"PBQP: No longer feasting upon every last byte of your RAM".
Minor details:
- Fully C++11'd. Never copy-construct another vector/matrix!
- Cute tricks with cost metadata: Metadata that is derived solely from cost
matrices/vectors is attached directly to the cost instances themselves. That way
if you unique the costs you never have to recompute the metadata. 400x less
memory means 400x less cost metadata (re)computation.
Special thanks to Arnaud de Grandmaison, who has been the source of much
encouragement, and of many very useful test cases.
This new solver forms the basis for future work, of which there's plenty to do.
I will be adding TODO notes shortly.
- Lang.
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The new graph structure replaces the node and edge linked lists with vectors.
Free lists (well, free vectors) are used for fast insertion/deletion.
The ultimate aim is to make PBQP graphs cheap to clone. The motivation is that
the PBQP solver destructively consumes input graphs while computing a solution,
forcing the graph to be fully reconstructed for each round of PBQP. This
imposes a high cost on large functions, which often require several rounds of
solving/spilling to find a final register allocation. If we can cheaply clone
the PBQP graph and incrementally update it between rounds then hopefully we can
reduce this cost. Further, once we begin pooling matrix/vector values (future
work), we can cache some PBQP solver metadata and share it between cloned
graphs, allowing the PBQP solver to re-use some of the computation done in
earlier rounds.
For now this is just a data structure update. The allocator and solver still
use the graph the same way as before, fully reconstructing it between each
round. I expect no material change from this update, although it may change
the iteration order of the nodes, causing ties in the solver to break in
different directions, and this could perturb the generated allocations
(hopefully in a completely benign way).
Thanks very much to Arnaud Allard de Grandmaison for encouraging me to get back
to work on this, and for a lot of discussion and many useful PBQP test cases.
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AKA: Recompile *ALL* the source code!
This one went much better. No manual edits here. I spot-checked for
silliness and grep-checked for really broken edits and everything seemed
good. It all still compiles. Yell if you see something that looks goofy.
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Sooooo many of these had incorrect or strange main module includes.
I have manually inspected all of these, and fixed the main module
include to be the nearest plausible thing I could find. If you own or
care about any of these source files, I encourage you to take some time
and check that these edits were sensible. I can't have broken anything
(I strictly added headers, and reordered them, never removed), but they
may not be the headers you'd really like to identify as containing the
API being implemented.
Many forward declarations and missing includes were added to a header
files to allow them to parse cleanly when included first. The main
module rule does in fact have its merits. =]
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The colorability heuristic should count these as denied registers.
No test case - this exposed a bug on an out-of-tree target.
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