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Keynote at HPSC 2013 at NTU, Taiwan: Systematizing tuning of computer systems using crowdsourcing and statistics

Grigori Fursin
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Abstract

Continuing innovation in science and technology is vital for our society and requires ever increasing computational resources. However, delivering such resources has become intolerably complex, ad-hoc, costly and error prone due to an enormous number of available design and optimization choices combined with the complex interactions between all software and hardware components. Auto-tuning, run-time adaptation and machine learning based approaches have been demonstrating good promise to address above challenges for more than a decade but are still far from the widespread production use due to unbearably long exploration and training times, lack of a common experimental methodology, and lack of public repositories for unified data collection, analysis and mining.
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Dates and versions

hal-00819000 , version 1 (29-10-2013)

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  • HAL Id : hal-00819000 , version 1

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Grigori Fursin. Keynote at HPSC 2013 at NTU, Taiwan: Systematizing tuning of computer systems using crowdsourcing and statistics. HPSC - Conference on Advanced Topics and Auto Tuning in High Performance and Scientific Computing - 2013, Mar 2013, Taipei, Taiwan. ⟨hal-00819000⟩
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