加速能源游戏求解现代建筑

A. Formisano, R. Gentilini, Flavio Vella
{"title":"加速能源游戏求解现代建筑","authors":"A. Formisano, R. Gentilini, Flavio Vella","doi":"10.1145/3149704.3149771","DOIUrl":null,"url":null,"abstract":"Quantitative games, where quantitative objectives are defined on weighted game arenas, provide natural tools for designing faithful models of embedded controllers. Instances of these games are the so called Energy Games. Starting from a sequential baseline implementation, we investigate the use of massively data computation capabilities supported by modern GPUs to solve the initial credit problem for Energy Games. We present different parallel implementations on multi-core CPU and GPU systems. Our solution outperforms the baseline implementation by up to 36x speedup and obtains a faster convergence time on real-world graphs.","PeriodicalId":292798,"journal":{"name":"Proceedings of the Seventh Workshop on Irregular Applications: Architectures and Algorithms","volume":"66 3","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Accelerating Energy Games Solvers on Modern Architectures\",\"authors\":\"A. Formisano, R. Gentilini, Flavio Vella\",\"doi\":\"10.1145/3149704.3149771\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Quantitative games, where quantitative objectives are defined on weighted game arenas, provide natural tools for designing faithful models of embedded controllers. Instances of these games are the so called Energy Games. Starting from a sequential baseline implementation, we investigate the use of massively data computation capabilities supported by modern GPUs to solve the initial credit problem for Energy Games. We present different parallel implementations on multi-core CPU and GPU systems. Our solution outperforms the baseline implementation by up to 36x speedup and obtains a faster convergence time on real-world graphs.\",\"PeriodicalId\":292798,\"journal\":{\"name\":\"Proceedings of the Seventh Workshop on Irregular Applications: Architectures and Algorithms\",\"volume\":\"66 3\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-10-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Seventh Workshop on Irregular Applications: Architectures and Algorithms\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3149704.3149771\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Seventh Workshop on Irregular Applications: Architectures and Algorithms","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3149704.3149771","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

摘要

定量博弈,其中定量目标是在加权博弈领域中定义的,为设计嵌入式控制器的忠实模型提供了自然的工具。这些游戏的例子就是所谓的“能量游戏”。从连续基线实现开始,我们研究了现代gpu支持的大规模数据计算能力的使用,以解决Energy Games的初始信用问题。我们提出了在多核CPU和GPU系统上的不同并行实现。我们的解决方案比基线实现的速度提高了36倍,并且在实际图形上获得了更快的收敛时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Accelerating Energy Games Solvers on Modern Architectures
Quantitative games, where quantitative objectives are defined on weighted game arenas, provide natural tools for designing faithful models of embedded controllers. Instances of these games are the so called Energy Games. Starting from a sequential baseline implementation, we investigate the use of massively data computation capabilities supported by modern GPUs to solve the initial credit problem for Energy Games. We present different parallel implementations on multi-core CPU and GPU systems. Our solution outperforms the baseline implementation by up to 36x speedup and obtains a faster convergence time on real-world graphs.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Enabling Work-Efficiency for High Performance Vertex-Centric Graph Analytics on GPUs Parallel Depth-First Search for Directed Acyclic Graphs Quantum Computing and Irregular Applications An Efficient Data Layout Transformation Algorithm for Locality-Aware Parallel Sparse FFT A Case for Migrating Execution for Irregular Applications
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1