{"title":"混合系统级MPSoC设计空间探索的交错方法","authors":"R. Piscitelli, A. Pimentel","doi":"10.1109/SAMOS.2012.6404152","DOIUrl":null,"url":null,"abstract":"System-level design space exploration (DSE), which is performed early in the design process, is of eminent importance to the design of complex multi-processor embedded system architectures. During system-level DSE, system parameters like, e.g., the number and type of processors, the type and size of memories, or the mapping of application tasks to architectural resources, are considered. Simulation-based DSE, in which different design instances are evaluated using system-level simulations, typically are computationally costly. Even using high-level simulations and efficient exploration algorithms, the simulation time to evaluate design points forms a real bottleneck in such DSE. Therefore, the vast design space that needs to be searched requires effective design space pruning techniques. This paper presents and studies different strategies for interleaving fast but less accurate analytical performance estimations with slower but more accurate simulations during DSE. By interleaving these analytical estimations with simulations, our hybrid approach significantly reduces the number of simulations that are needed during the process of DSE. Experimental results have demonstrated that such hybrid DSE is a promising technique that can yield solutions of similar quality as compared to simulation-based DSE but only at a fraction of the execution time.","PeriodicalId":130275,"journal":{"name":"2012 International Conference on Embedded Computer Systems (SAMOS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Interleaving methods for hybrid system-level MPSoC design space exploration\",\"authors\":\"R. Piscitelli, A. Pimentel\",\"doi\":\"10.1109/SAMOS.2012.6404152\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"System-level design space exploration (DSE), which is performed early in the design process, is of eminent importance to the design of complex multi-processor embedded system architectures. During system-level DSE, system parameters like, e.g., the number and type of processors, the type and size of memories, or the mapping of application tasks to architectural resources, are considered. Simulation-based DSE, in which different design instances are evaluated using system-level simulations, typically are computationally costly. Even using high-level simulations and efficient exploration algorithms, the simulation time to evaluate design points forms a real bottleneck in such DSE. Therefore, the vast design space that needs to be searched requires effective design space pruning techniques. This paper presents and studies different strategies for interleaving fast but less accurate analytical performance estimations with slower but more accurate simulations during DSE. By interleaving these analytical estimations with simulations, our hybrid approach significantly reduces the number of simulations that are needed during the process of DSE. Experimental results have demonstrated that such hybrid DSE is a promising technique that can yield solutions of similar quality as compared to simulation-based DSE but only at a fraction of the execution time.\",\"PeriodicalId\":130275,\"journal\":{\"name\":\"2012 International Conference on Embedded Computer Systems (SAMOS)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-07-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 International Conference on Embedded Computer Systems (SAMOS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SAMOS.2012.6404152\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 International Conference on Embedded Computer Systems (SAMOS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SAMOS.2012.6404152","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
摘要
系统级设计空间探索(system -level design space exploration, DSE)在设计过程的早期进行,对于复杂的多处理器嵌入式系统架构的设计非常重要。在系统级DSE期间,会考虑系统参数,例如处理器的数量和类型、内存的类型和大小,或者应用程序任务到体系结构资源的映射。基于仿真的DSE,使用系统级仿真来评估不同的设计实例,通常计算成本很高。即使使用高水平的仿真和高效的探索算法,评估设计点的仿真时间也成为这种DSE的真正瓶颈。因此,需要搜索的巨大设计空间需要有效的设计空间修剪技术。本文提出并研究了在DSE过程中,将快速但不太准确的分析性能估计与缓慢但更准确的仿真相结合的不同策略。通过将这些分析估计与模拟交叉,我们的混合方法显着减少了DSE过程中所需的模拟次数。实验结果表明,这种混合DSE是一种很有前途的技术,与基于仿真的DSE相比,它可以产生类似质量的解决方案,但只需要一小部分执行时间。
Interleaving methods for hybrid system-level MPSoC design space exploration
System-level design space exploration (DSE), which is performed early in the design process, is of eminent importance to the design of complex multi-processor embedded system architectures. During system-level DSE, system parameters like, e.g., the number and type of processors, the type and size of memories, or the mapping of application tasks to architectural resources, are considered. Simulation-based DSE, in which different design instances are evaluated using system-level simulations, typically are computationally costly. Even using high-level simulations and efficient exploration algorithms, the simulation time to evaluate design points forms a real bottleneck in such DSE. Therefore, the vast design space that needs to be searched requires effective design space pruning techniques. This paper presents and studies different strategies for interleaving fast but less accurate analytical performance estimations with slower but more accurate simulations during DSE. By interleaving these analytical estimations with simulations, our hybrid approach significantly reduces the number of simulations that are needed during the process of DSE. Experimental results have demonstrated that such hybrid DSE is a promising technique that can yield solutions of similar quality as compared to simulation-based DSE but only at a fraction of the execution time.