Collective Knowledge Aggregator proof-of-concept
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Distinct solutions after online classification (auto/crowd-tune LLVM compiler flags (minimize execution time))

Scenario UID2aaed4c520956635 (experiment.tune.compiler.flags.llvm.e)
Data UIDb288c4ef0b46cf60
Discuss (optimizations to improve compilers,
semantic/data set/hardware features
to improve predictions
, etc):
GitHub wiki, Google group
Download:[ All solutions in JSON ], [ Solutions' classification in JSON ]
Reproduce all (with reactions):ck replay 2aaed4c520956635:b288c4ef0b46cf60
CompilerLLVM 3.6
Improvement key IK1Main kernel execution time speedup [min]
Improvement key IK2Code size improvement

Improvements (<4% variation) Distinct workload for highest improvement
# Solution UID IK1 IK2 New distinct optimization choices Ref Best species Worst species Touched Iters Program CMD Dataset Dataset file CPU freq (MHz) Cores Platform OS Replay
S1 3db64fa786d12b01 1.35 1.00 -O3 -fmerge-all-constants -fno-elide-constructors -fomit-frame-pointer -fvisibility-inlines-hidden -msoft-float -fshort-wchar -ffp-contract=off -O3 1 0 2 1 milepost-codelet-mibench-consumer-tiffmedian-src-tiffmedian-codelet-3-1 default 456, 456 1 SAMSUNG GT-P7500 Android 4.2.2

[ Participated users, platforms, OS, CPU, GPU, GPGPU, NN ] [ How to participate ] [ Motivation (PPT) (PDF) ] [ Papers 1 , 2 , 3] [ Android app ] [ Collective training set ] [ Unified AI ]
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Developed by dividiti,
cTuning foundation,
and the community
Implemented as a CK workflow
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