SILOptimizer: support for Dictionary literals generated in the data section. #24205
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@swift-ci test |
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Code size: -O
Performance: -Osize
Code size: -Osize
How to read the dataThe tables contain differences in performance which are larger than 8% and differences in code size which are larger than 1%.If you see any unexpected regressions, you should consider fixing the Noise: Sometimes the performance results (not code size!) contain false Hardware Overview |
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Nice! |
slavapestov
reviewed
Apr 23, 2019
| unsigned TupleIdx = TEA->getFieldNo(); | ||
| assert(TupleIdx < NumTailTupleElements); | ||
| for (Operand *Use : TEA->getUses()) { | ||
| if (!handleTailAddr(TailIdx * NumTailTupleElements + TupleIdx, Use->getUser(), 0,TailStores)) |
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This line looks too long :)
| llvm::DenseMap<VarDecl *, StoreInst *> MemberStores; | ||
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| // A store for each element of the tail allocated array. In case of a tuple, there is a store | ||
| // for each tuple element. For example, a 3 element0 array of 2-element tuples |
…ection. Actually: generate the array of (key, value) tuples in the data section, which is then passed to Dictionary.init(dictionaryLiteral:) We already do this for simple arrays, e.g. arrays with trivial element types. The only change needed for dictionary literals is to support tuple types in the ObjectOutliner. The effect of this optimization is a significant reduction in code size for dictionary literals - and an increase in data size. But in most cases there is a considerable net win for code+data size in total.
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@swift-ci smoke test and merge |
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@swift-ci smoke test and merge |
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Actually: generate the array of (key, value) tuples in the data section, which is then passed to Dictionary.init(dictionaryLiteral:)
We already do this for simple arrays, e.g. arrays with trivial element types.
The only change needed for dictionary literals is to support tuple types in the ObjectOutliner.
The effect of this optimization is a significant reduction in code size for dictionary literals - and an increase in data size.
But in most cases there is a considerable net win for code+data size in total.