Collective Knowledge Aggregator proof-of-concept
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Aggregated execution times of slambench across multiple platforms (crowd-benchmarking)
Grigori Fursin 1,2, Anton Lokhmotov 2
1 cTuning Foundation, France,   2 dividiti, UK
Demo of aggregating results of all executions of slambench across all platforms (different CPU, GPU, frequency, compiler, etc). It can help build a realistic training set for further machine learning based autotuning and run-time adaptation as described in our papers [1, 2, 3]. We can use it to find an optimal platform for a given data set (balancing execution time, energy/frequency, accuracy, price, cost, etc - particularly useful for cloud computing or mobile devices).
CK report at with ranking of all devices/kernel vs FPS, energy, accuracy, etc.

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Developed by dividiti,
cTuning foundation,
and the community
Implemented as a CK workflow
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