Speed-up Solving Linear Systems on Parallel Architectures via Aggregation of Clans (Dmitry Zaitsev, LVEE-2019) — различия между версиями
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;{{SpeakerInfo}}: {{Speaker|Дмитрий Зайцев}} <blockquote> Varying minimal clan size brings in certain imbalance when solving a linear (Diophantine) system on parallel architectures via composition of its clans using open source software PaAd. The problem is partially mended by dynamic scheduling of jobs. The present paper studies a task of preliminary balancing the clan size via their aggregation represented as a special case of graph partitioning. Due to complexity of the optimization criteria, taking into consideration both the number of equations and the number of variables on two stages of solution — solving a system for each clan and solving a composition system — simplified variants of the task are considered and solved using heuristic techniques: a fast bin packing with the first fit on a sorted array algorithm and a multi-objective graph partitioning with software package METIS. Obtained benchmarks show that aggregation of clans brings in an additional 3 times speed-up. </blockquote> {{VideoSection}} {{vimeoembed|366010418|800|450}} {{youtubelink|lBoWwVJu6h8}} {{SlidesSection}} [[File:Speed-up Solving Linear Systems on Parallel Architectures via Aggregation of Clans (Dmitry Zaitsev, LVEE-2019).pdf|left|page=-|300px]] {{----}} == Thesis == {{----}} [[File:{{#setmainimage:Speed-up Solving Linear Systems on Parallel Architectures via Aggregation of Clans (Dmitry Zaitsev, LVEE-2019)!.jpg}}|center|640px]] {{LinksSection}} * [ Talks page] <!-- <blockquote>[©]</blockquote> --> {{vklink|1435}} {{fblink|2423735191212821}} <references/> [[Категория:LVEE-2019]] [[Категория:Алгоритмы]] {{stats|disqus_comments=12|refresh_time=2020-01-09T16:05:022021-08-31T16:37:41.939067614556|vimeo_plays=26|youtube_comments=0|youtube_plays=11}}23}} |
Текущая версия на 12:19, 4 сентября 2021
- Докладчик
- Дмитрий Зайцев
Varying minimal clan size brings in certain imbalance when solving a linear (Diophantine) system on parallel architectures via composition of its clans using open source software PaAd. The problem is partially mended by dynamic scheduling of jobs. The present paper studies a task of preliminary balancing the clan size via their aggregation represented as a special case of graph partitioning. Due to complexity of the optimization criteria, taking into consideration both the number of equations and the number of variables on two stages of solution — solving a system for each clan and solving a composition system — simplified variants of the task are considered and solved using heuristic techniques: a fast bin packing with the first fit on a sorted array algorithm and a multi-objective graph partitioning with software package METIS. Obtained benchmarks show that aggregation of clans brings in an additional 3 times speed-up.
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