Stephan Wong, Anthony Brandon, Fakhar Anjam, Roel Seedorf, R. Giorgi, Zhibin Yu, Nikola Puzovic, S. Mckee, Magnus Sjalander, L. Carro, G. Keramidas
{"title":"Early results from ERA — Embedded Reconfigurable Architectures","authors":"Stephan Wong, Anthony Brandon, Fakhar Anjam, Roel Seedorf, R. Giorgi, Zhibin Yu, Nikola Puzovic, S. Mckee, Magnus Sjalander, L. Carro, G. Keramidas","doi":"10.1109/indin.2011.6034998","DOIUrl":null,"url":null,"abstract":"The growing complexity and diversity of embedded systems — combined with continuing demands for higher performance and lower power consumption — place increasing pressure on embedded platforms designers. To address these problems, the Embedded Reconfigurable Architectures project (ERA), investigates innovations in both hardware and tools to create next-generation embedded systems. Leveraging adaptive hardware enables maximum performance for given power budgets. We design our platform via a structured approach that allows integration of reconfigurable computing elements, network fabrics, and memory hierarchy components. Commercially available, off-the-shelf processors are combined with other proprietary and application-specific, dedicated cores. These computing and network elements can adapt their composition, organization, and even instruction-set architectures in an effort to provide the best possible trade-offs in performance and power for the given application(s). Likewise, network elements and topologies and memory hierarchy organization can be selected both statically at design time and dynamically at run-time. Hardware details are exposed to the operating system, run-time system, compiler, and applications. This combination supports fast platform prototyping of high-efficient embedded system designs. Our design philosophy supports the freedom to flexibly tune all these hardware elements, enabling a better choice of power/performance trade-offs than that afforded by the current state of the art.","PeriodicalId":378407,"journal":{"name":"2011 9th IEEE International Conference on Industrial Informatics","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 9th IEEE International Conference on Industrial Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/indin.2011.6034998","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 13
Abstract
The growing complexity and diversity of embedded systems — combined with continuing demands for higher performance and lower power consumption — place increasing pressure on embedded platforms designers. To address these problems, the Embedded Reconfigurable Architectures project (ERA), investigates innovations in both hardware and tools to create next-generation embedded systems. Leveraging adaptive hardware enables maximum performance for given power budgets. We design our platform via a structured approach that allows integration of reconfigurable computing elements, network fabrics, and memory hierarchy components. Commercially available, off-the-shelf processors are combined with other proprietary and application-specific, dedicated cores. These computing and network elements can adapt their composition, organization, and even instruction-set architectures in an effort to provide the best possible trade-offs in performance and power for the given application(s). Likewise, network elements and topologies and memory hierarchy organization can be selected both statically at design time and dynamically at run-time. Hardware details are exposed to the operating system, run-time system, compiler, and applications. This combination supports fast platform prototyping of high-efficient embedded system designs. Our design philosophy supports the freedom to flexibly tune all these hardware elements, enabling a better choice of power/performance trade-offs than that afforded by the current state of the art.