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Passes using local ArenaAllocator were hiding their memory
usage from the allocation counting, making it difficult to
track down where memory was used. Using ScopedArenaAllocator
reveals the memory usage.
This changes the HGraph constructor which requires a lot of
changes in tests. Refactor these tests to limit the amount
of work needed the next time we change that constructor.
Test: m test-art-host-gtest
Test: testrunner.py --host
Test: Build with kArenaAllocatorCountAllocations = true.
Bug: 64312607
Change-Id: I34939e4086b500d6e827ff3ef2211d1a421ac91a
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Replace most uses of the runtime's Primitive in compiler
with a new class DataType. This prepares for introducing
new types, such as Uint8, that the runtime does not need
to know about.
Test: m test-art-host-gtest
Test: testrunner.py --host
Bug: 23964345
Change-Id: Iec2ad82454eec678fffcd8279a9746b90feb9b0c
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Test: market scan.
Change-Id: I58b23b8d254883f30619ea3602d34bf93618d432
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Fix the issue when after loop header's predecessors reordering in
SimplifyLoops phi inputs are not reordered correspondingly.
Test: loop_optimization_test.cc, test-art-host, test-art-target.
Change-Id: I8a251a0a953d751f9bb67da58181e47d225d90e6
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Rationale:
Break-out CL of ART Vectorizer: number 3.
The purpose is making the original CL smaller
and easier to review.
Bug: 34083438
Test: test-art-host
Change-Id: I7cece807ee4f5fcaeae41f1deed33ac263447b77
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Add abstraction for uint16_t type index.
Test: m test-art-host
Change-Id: I47708741c7c579cbbe59ab723c1e31c5fe71f83a
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Rationale:
Ownership of graph's linear order and iterators was
a bit unclear now that other phases are using it.
New approach allows phases to compute their own
order, while ssa_liveness is sole owner for graph
(since it is not mutated afterwards).
Also shortens lifetime of loop's arena.
Test: test-art-host
Change-Id: Ib7137d1203a1e0a12db49868f4117d48a4277f30
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loop_optimization_test uses memory from HLoopOptimization's
allocator, which is scoped by the Run method.
Fix is to pass custom allocator.
test: m test-art-host-gtest
Change-Id: I359330e22202519f400a26da5403eeb00f0b2db4
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Rationale:
We are planning to add more and more loop related optimizations
and this framework provides the basis to do so. For starters,
the framework optimizes dead induction, induction that can be
replaced with a simpler closed-form, and eliminates dead loops
completely (either pre-existing or as a result of induction
removal).
Speedup on e.g. Benchpress Loop is 73x (17.5us. -> 0.24us.)
[with the potential for more exploiting outer loop too]
Test: 618-checker-induction et al.
Change-Id: If80a809acf943539bf6726b0030dcabd50c9babc
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