Haris Javaid, Xin He, A. Ignjatović, S. Parameswaran
{"title":"Optimal synthesis of latency and throughput constrained pipelined MPSoCs targeting streaming applications","authors":"Haris Javaid, Xin He, A. Ignjatović, S. Parameswaran","doi":"10.1145/1878961.1878978","DOIUrl":null,"url":null,"abstract":"A streaming application, characterized by a kernel that can be broken down into independent tasks which can be executed in a pipelined fashion, inherently allows its implementation on a pipeline of Application Specific Instruction set Processors (ASIPs), called a pipelined MPSoC. The latency and throughput requirements of streaming applications put constraints on the design of such a pipelined MPSoC, where each ASIP has a number of available configurations differing by additional instructions, and instruction and data cache sizes. Thus, the design space of a pipelined MPSoC is all the possible combinations of ASIP configurations (design points). In this paper, a methodology is proposed to optimize the area of a pipelined MPSoC under a latency or a throughput constraint. The final design point is a set of ASIP configurations with one configuration for each ASIP. We proposed an Integer Linear Programming (ILP) based solution to the area optimization problem under a latency constraint, and an algorithm for optimization of pipelined MPSoC area under a throughput constraint. The proposed solutions were evaluated using four streaming applications: JPEG encoder; JPEG decoder; MP3 encoder; and H.264 decoder. The time to find the Pareto front of each pipelined MPSoC was less than 4 minutes where design spaces had up to 1016 design points, illustrating the applicability of our approach.","PeriodicalId":118816,"journal":{"name":"2010 IEEE/ACM/IFIP International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"24","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE/ACM/IFIP International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1878961.1878978","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 24
Abstract
A streaming application, characterized by a kernel that can be broken down into independent tasks which can be executed in a pipelined fashion, inherently allows its implementation on a pipeline of Application Specific Instruction set Processors (ASIPs), called a pipelined MPSoC. The latency and throughput requirements of streaming applications put constraints on the design of such a pipelined MPSoC, where each ASIP has a number of available configurations differing by additional instructions, and instruction and data cache sizes. Thus, the design space of a pipelined MPSoC is all the possible combinations of ASIP configurations (design points). In this paper, a methodology is proposed to optimize the area of a pipelined MPSoC under a latency or a throughput constraint. The final design point is a set of ASIP configurations with one configuration for each ASIP. We proposed an Integer Linear Programming (ILP) based solution to the area optimization problem under a latency constraint, and an algorithm for optimization of pipelined MPSoC area under a throughput constraint. The proposed solutions were evaluated using four streaming applications: JPEG encoder; JPEG decoder; MP3 encoder; and H.264 decoder. The time to find the Pareto front of each pipelined MPSoC was less than 4 minutes where design spaces had up to 1016 design points, illustrating the applicability of our approach.
流应用程序的特点是内核可以分解成独立的任务,可以以流水线的方式执行,本质上允许它在应用特定指令集处理器(application Specific Instruction set processor, asip)的流水线上实现,称为流水线MPSoC。流应用程序的延迟和吞吐量要求限制了这种流水线MPSoC的设计,其中每个ASIP都有许多可用的配置,这些配置因附加指令、指令和数据缓存大小而不同。因此,流水线MPSoC的设计空间是ASIP配置(设计点)的所有可能组合。在本文中,提出了一种在延迟或吞吐量限制下优化流水线MPSoC面积的方法。最后的设计点是一组ASIP配置,每个ASIP都有一个配置。我们提出了一种基于整数线性规划(ILP)的延迟约束下的面积优化问题的解决方案,以及一种吞吐量约束下的流水线MPSoC面积优化算法。采用四种流媒体应用对所提出的解决方案进行了评估:JPEG编码器;JPEG解码器;MP3编码器;H.264解码器。在设计空间多达1016个设计点的情况下,找到每个流水线MPSoC的Pareto前端的时间不到4分钟,这说明了我们方法的适用性。