Collective Knowledge repository with reproducible experimental results from collaborative program autotuning on Raspberry Pi (program reactions to most efficient compiler optimizations)
收藏Figshare2018-01-16 更新2026-04-29 收录
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https://figshare.com/articles/dataset/Collective_Knowledge_repository_with_reproducible_experimental_results_from_collaborative_program_autotuning_on_Raspberry_Pi_program_reactions_to_most_efficient_compiler_optimizations_/5789007
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资源简介:
Optimization results to demonstrate compiler autotuning, crowd-tuning and machine learning on RPi3 via customizable Collective Knowledge workflow framework with a portable package manager.These results in the Collective Knowledge format help prototype a common and reproducible optimization methodology to support Artifact evaluation and Pareto-efficient co-design competitions of the whole software and hardware stack for emerging workloads such as deep learning in terms of speed, accuracy, energy and costs:* http://cKnowledge.org/request* http://cTuning.org/aeInteractive CK report: http://cKnowledge.org/rpi-crowd-tuningArXiv report: https://arxiv.org/abs/1801.08024
创建时间:
2018-01-16



