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Power Mitigation by Performance Equalization in a Heterogeneous Reconfigurable Multicore Architecture

机译:通过异构可重配置多核体系结构中的性能均衡来降低功耗

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This paper presents an integrated self-aware computing model mitigating the power dissipation of a heterogeneous reconfigurable multicore architecture by dynamically scaling the operating frequency of each core. The power mitigation is achieved by equalizing the performance of all the cores for an uninterrupted exchange of data. The multicore platform consists of heterogeneous Coarse-Grained Reconfigurable Arrays (CGRAs) of application-specific sizes and a Reduced Instruction-Set Computing (RISC) core. The CGRAs and the RISC core are integrated with each other over a Network-on-Chip (NoC) of six nodes arranged in a topology of two rows and three columns. The RISC core constantly monitors and controls the performance of each CGRA accelerator by adjusting the operating frequencies unless the performance of all the CGRAs is optimally balanced over the platform. The CGRA cores on the platform are processing some of the most computationally-intensive signal processing algorithms while the RISC core establishes packet based synchronization between the cores for computation and communication. All the cores can access each other's computational and memory resources while processing the kernels simultaneously and independently of each other. Besides general-purpose processing and overall platform supervision, the RISC processor manages performance equalization among all the cores which mitigates the overall dynamic power dissipation by 20.7 % for a proof-of-concept test.
机译:本文提出了一种集成的自我感知计算模型,该模型通过动态缩放每个内核的工作频率来减轻异构可重配置多核体系结构的功耗。通过均衡所有内核的性能以实现不间断的数据交换,从而降低了功耗。多核平台由应用程序特定大小的异构粗粒度可重构阵列(CGRA)和精简指令集计算(RISC)内核组成。 CGRA和RISC核心通过以两个行和三个列的拓扑排列的六个节点的片上网络(NoC)相互集成。除非所有CGRA的性能在平台上达到最佳平衡,否则RISC内核会通过调整工作频率来不断监视和控制每个CGRA加速器的性能。平台上的CGRA内核正在处理一些计算量最大的信号处理算法,而RISC内核则在内核之间建立了基于分组的同步以进行计算和通信。所有内核都可以访问彼此的计算和内存资源,同时同时且彼此独立地处理内核。除了通用处理和总体平台监督之外,RISC处理器还管理所有内核之间的性能均衡,这对于概念验证测试将总体动态功耗降低了20.7%。

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