I. Mavroidis, I. Papaefstathiou, L. Lavagno, Dimitrios S. Nikolopoulos, Dirk Koch, J. Goodacre, I. Sourdis, Vassilis D. Papaefstathiou, M. Coppola, Manuel Palomino
{"title":"ECOSCALE:用于未来百亿亿级系统的可重构计算和运行时系统","authors":"I. Mavroidis, I. Papaefstathiou, L. Lavagno, Dimitrios S. Nikolopoulos, Dirk Koch, J. Goodacre, I. Sourdis, Vassilis D. Papaefstathiou, M. Coppola, Manuel Palomino","doi":"10.3850/9783981537079_1021","DOIUrl":null,"url":null,"abstract":"In order to reach exascale performance, current HPC systems need to be improved. Simple hardware scaling is not a feasible solution due to the increasing utility costs and power consumption limitations. Apart from improvements in implementation technology, what is needed is to refine the HPC application development flow as well as the system architecture of future HPC systems. ECOSCALE tackles these challenges by proposing a scalable programming environment and architecture, aiming to substantially reduce energy consumption as well as data traffic and latency. ECOSCALE introduces a novel heterogeneous energy-efficient hierarchical architecture, as well as a hybrid many-core+OpenCL programming environment and runtime system. The ECOSCALE approach is hierarchical and is expected to scale well by partitioning the physical system into multiple independent Workers (i.e. compute nodes). Workers are interconnected in a tree-like fashion and define a contiguous global address space that can be viewed either as a set of partitions in a Partitioned Global Address Space (PGAS), or as a set of nodes hierarchically interconnected via an MPI protocol. To further increase energy efficiency, as well as to provide resilience, the Workers employ reconfigurable accelerators mapped into the virtual address space utilizing a dual stage System Memory Management Unit with coherent memory access. The architecture supports shared partitioned reconfigurable resources accessed by any Worker in a PGAS partition, as well as automated hardware synthesis of these resources from an OpenCL-based programming model.","PeriodicalId":311352,"journal":{"name":"2016 Design, Automation & Test in Europe Conference & Exhibition (DATE)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"41","resultStr":"{\"title\":\"ECOSCALE: Reconfigurable computing and runtime system for future exascale systems\",\"authors\":\"I. Mavroidis, I. Papaefstathiou, L. Lavagno, Dimitrios S. Nikolopoulos, Dirk Koch, J. Goodacre, I. Sourdis, Vassilis D. Papaefstathiou, M. Coppola, Manuel Palomino\",\"doi\":\"10.3850/9783981537079_1021\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to reach exascale performance, current HPC systems need to be improved. Simple hardware scaling is not a feasible solution due to the increasing utility costs and power consumption limitations. Apart from improvements in implementation technology, what is needed is to refine the HPC application development flow as well as the system architecture of future HPC systems. ECOSCALE tackles these challenges by proposing a scalable programming environment and architecture, aiming to substantially reduce energy consumption as well as data traffic and latency. ECOSCALE introduces a novel heterogeneous energy-efficient hierarchical architecture, as well as a hybrid many-core+OpenCL programming environment and runtime system. The ECOSCALE approach is hierarchical and is expected to scale well by partitioning the physical system into multiple independent Workers (i.e. compute nodes). Workers are interconnected in a tree-like fashion and define a contiguous global address space that can be viewed either as a set of partitions in a Partitioned Global Address Space (PGAS), or as a set of nodes hierarchically interconnected via an MPI protocol. To further increase energy efficiency, as well as to provide resilience, the Workers employ reconfigurable accelerators mapped into the virtual address space utilizing a dual stage System Memory Management Unit with coherent memory access. The architecture supports shared partitioned reconfigurable resources accessed by any Worker in a PGAS partition, as well as automated hardware synthesis of these resources from an OpenCL-based programming model.\",\"PeriodicalId\":311352,\"journal\":{\"name\":\"2016 Design, Automation & Test in Europe Conference & Exhibition (DATE)\",\"volume\":\"34 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-03-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"41\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 Design, Automation & Test in Europe Conference & Exhibition (DATE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3850/9783981537079_1021\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 Design, Automation & Test in Europe Conference & Exhibition (DATE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3850/9783981537079_1021","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 41
摘要
为了达到百亿亿次的性能,目前的HPC系统需要改进。由于不断增加的公用事业成本和功耗限制,简单的硬件扩展不是可行的解决方案。除了实现技术的改进之外,还需要完善HPC应用程序开发流程以及未来HPC系统的系统架构。ECOSCALE通过提出可扩展的编程环境和架构来解决这些挑战,旨在大幅降低能耗、数据流量和延迟。ECOSCALE引入了一种新型的异构节能分层架构,以及混合多核+OpenCL编程环境和运行时系统。ECOSCALE方法是分层的,通过将物理系统划分为多个独立的worker(即计算节点),有望很好地扩展。worker以树状的方式相互连接,并定义一个连续的全局地址空间,可以将其视为分区全局地址空间(Partitioned global address space, PGAS)中的一组分区,也可以将其视为通过MPI协议分层连接的一组节点。为了进一步提高能源效率,并提供弹性,工人使用可重构加速器映射到虚拟地址空间,利用双级系统内存管理单元具有一致的内存访问。该体系结构支持由PGAS分区中的任何Worker访问的共享分区可重构资源,以及来自基于opencl的编程模型的这些资源的自动硬件合成。
ECOSCALE: Reconfigurable computing and runtime system for future exascale systems
In order to reach exascale performance, current HPC systems need to be improved. Simple hardware scaling is not a feasible solution due to the increasing utility costs and power consumption limitations. Apart from improvements in implementation technology, what is needed is to refine the HPC application development flow as well as the system architecture of future HPC systems. ECOSCALE tackles these challenges by proposing a scalable programming environment and architecture, aiming to substantially reduce energy consumption as well as data traffic and latency. ECOSCALE introduces a novel heterogeneous energy-efficient hierarchical architecture, as well as a hybrid many-core+OpenCL programming environment and runtime system. The ECOSCALE approach is hierarchical and is expected to scale well by partitioning the physical system into multiple independent Workers (i.e. compute nodes). Workers are interconnected in a tree-like fashion and define a contiguous global address space that can be viewed either as a set of partitions in a Partitioned Global Address Space (PGAS), or as a set of nodes hierarchically interconnected via an MPI protocol. To further increase energy efficiency, as well as to provide resilience, the Workers employ reconfigurable accelerators mapped into the virtual address space utilizing a dual stage System Memory Management Unit with coherent memory access. The architecture supports shared partitioned reconfigurable resources accessed by any Worker in a PGAS partition, as well as automated hardware synthesis of these resources from an OpenCL-based programming model.