SILOptimizer: move String concatination optimization from SILCombine/ConstantFolding to StringOptimization.

[eeckstein]

This simplifies some code and it's not required to try this optimization on every run of SILCombine and ConstantPropagation.

[eeckstein]

@swift-ci test

[eeckstein]

@swift-ci benchmark

[swift-ci]

Performance: -O

Regression	OLD	NEW	DELTA	RATIO
Data.append.Sequence.64kB.Count	25	29	+16.0%	0.86x (?)
Improvement	OLD	NEW	DELTA	RATIO
CharIteration_korean_unicodeScalars	3120	2800	-10.3%	1.11x (?)
CharIndexing_ascii_unicodeScalars	3840	3520	-8.3%	1.09x
CharIteration_japanese_unicodeScalars	4040	3720	-7.9%	1.09x (?)
CharIteration_punctuatedJapanese_unicodeScalars	560	520	-7.1%	1.08x (?)
CharIteration_chinese_unicodeScalars	2400	2240	-6.7%	1.07x (?)

Code size: -O

Performance: -Osize

Regression	OLD	NEW	DELTA	RATIO
FlattenListLoop	1204	1530	+27.1%	0.79x (?)
Improvement	OLD	NEW	DELTA	RATIO
DataCreateMedium	6200	4000	-35.5%	1.55x
CharIteration_russian_unicodeScalars_Backwards	4120	3520	-14.6%	1.17x
CharIteration_japanese_unicodeScalars_Backwards	6400	5480	-14.4%	1.17x
CharIteration_korean_unicodeScalars_Backwards	5040	4320	-14.3%	1.17x
CharIteration_chinese_unicodeScalars_Backwards	3680	3160	-14.1%	1.16x (?)
CharIteration_punctuatedJapanese_unicodeScalars_Backwards	960	840	-12.5%	1.14x
CharIndexing_punctuatedJapanese_unicodeScalars_Backwards	1640	1440	-12.2%	1.14x (?)
FlattenListFlatMap	4081	3604	-11.7%	1.13x (?)
CharIndexing_japanese_unicodeScalars_Backwards	10440	9400	-10.0%	1.11x (?)
CharIteration_punctuated_unicodeScalars_Backwards	840	760	-9.5%	1.11x
CharIndexing_chinese_unicodeScalars_Backwards	6520	5920	-9.2%	1.10x (?)
DataAccessBytesMedium	59	54	-8.5%	1.09x (?)
CharIndexing_ascii_unicodeScalars_Backwards	7120	6560	-7.9%	1.09x (?)
CharIndexing_tweet_unicodeScalars_Backwards	14000	12920	-7.7%	1.08x (?)
CharIndexing_russian_unicodeScalars_Backwards	7480	6920	-7.5%	1.08x (?)
CharIndexing_punctuated_unicodeScalars_Backwards	1800	1680	-6.7%	1.07x (?)

Code size: -Osize

Performance: -Onone

Code size: -swiftlibs

How to read the data

The 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
regressions before you merge the PR.

Noise: Sometimes the performance results (not code size!) contain false
alarms. Unexpected regressions which are marked with '(?)' are probably noise.
If you see regressions which you cannot explain you can try to run the
benchmarks again. If regressions still show up, please consult with the
performance team (@eeckstein).

Hardware Overview

  Model Name: Mac mini
  Model Identifier: Macmini8,1
  Processor Name: 6-Core Intel Core i7
  Processor Speed: 3.2 GHz
  Number of Processors: 1
  Total Number of Cores: 6
  L2 Cache (per Core): 256 KB
  L3 Cache: 12 MB
  Memory: 64 GB