Collective Knowledge Aggregator proof-of-concept
Crowd results Raw CK browser Graphs Reports Datasets Models Home

This page is outdated! New version is available here.


Distinct solutions after online classification (auto/crowd-tune GCC compiler flags (minimize execution time))

Scenario UID8289e0cf24346aa7 (experiment.tune.compiler.flags.gcc.e)
Data UID98dfd62a3ca917cb
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 8289e0cf24346aa7:98dfd62a3ca917cb
CompilerGCC 5.4.0
CPUIntel(R) Core(TM) i7-4910MQ CPU @ 2.90GHz
Objectivemin
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 d01dc0796d84f68a 1.43 0.76 -O3 -fno-reorder-blocks-and-partition -funroll-all-loops -O3 2 0 5 33 milepost-codelet-mibench-automotive-susan-e-src-susan-codelet-10-1 default 2901, 2901, 2901, 2901, 2901, 2901, 2901, 2901 8 VMware, Inc. None (VMware Virtual Platform) Ubuntu 16.04.1 LTS



[ Participated users, platforms, OS, CPU, GPU, GPGPU, NN, NPU ] [ How to participate ] [ Motivation (PPT) (PDF) ] [ Papers 1 , 2 , 3] [ Android app ] [ Collective training set ] [ Unified AI ]
View entry in raw format

Developed by Grigori Fursin           
Implemented as a CK workflow 		                         
   
                      Hosted at