{"title":"Exploiting Locality for the Performance Analysis of Shared Memory Systems in MPSoCs","authors":"Selma Saidi, A. Syring","doi":"10.1109/RTSS.2018.00050","DOIUrl":null,"url":null,"abstract":"The integration trend and increased required computing power is driving the advent of common embedded consumer devices like MPSoCs platforms in the safety critical domain. MPSoCs often feature a shared tightly-coupled memory system where a careful management of data storage and transfers is a key enabler for performance. However, providing real-time guarantees for these platforms is extremely challenging as they rely on exploiting data locality to improve average latencies in shared-memory architectures. This effect is often disregarded by existing real-time analysis approaches which furthermore often focus solely on a single component of the memory system. In this paper, we propose a framework for the timing analysis of shared memory systems composed of on-chip scratchpad memories, off-chip DRAMs and DMA engines. The analysis captures the effect on the performance of the system of the locality of accesses, their interleaving and granularity.","PeriodicalId":294784,"journal":{"name":"2018 IEEE Real-Time Systems Symposium (RTSS)","volume":"110 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE Real-Time Systems Symposium (RTSS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RTSS.2018.00050","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
The integration trend and increased required computing power is driving the advent of common embedded consumer devices like MPSoCs platforms in the safety critical domain. MPSoCs often feature a shared tightly-coupled memory system where a careful management of data storage and transfers is a key enabler for performance. However, providing real-time guarantees for these platforms is extremely challenging as they rely on exploiting data locality to improve average latencies in shared-memory architectures. This effect is often disregarded by existing real-time analysis approaches which furthermore often focus solely on a single component of the memory system. In this paper, we propose a framework for the timing analysis of shared memory systems composed of on-chip scratchpad memories, off-chip DRAMs and DMA engines. The analysis captures the effect on the performance of the system of the locality of accesses, their interleaving and granularity.