Modeling and evaluating energy-performance efficiency of parallel processing on multicore based power aware systems
Modeling and evaluating energy-performance efficiency of parallel processing on multicore based power aware systems
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DOI：
10.1109/ipdps.2009.5160979
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发表时间：
2009-05
期刊：
影响因子：
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通讯作者：
Rong Ge;Xizhou Feng;K. Cameron
中科院分区：
文献类型：
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作者：
Rong Ge;Xizhou Feng;K. Cameron
在节能高端计算中，一个典型的问题是找到一个能量性能高效的资源分配用于计算给定的工作负载。这个问题的分析解决方案包括两个步骤：第一次估计的性能和能源成本的工作负载运行各种资源分配，第二次搜索的分配空间，以确定最佳的分配，根据能源性能效率的措施。在本文中，我们开发的分析模型，以近似的性能和能源成本的科学工作负载的多核基于功率感知系统。该性能模型将Amdahl定律和功耗感知加速比模型扩展到基于多核的功耗感知计算环境。功率和能量模型描述了资源分配和工作负载特性的功率效应。作为一个概念证明，我们展示了模型参数推导和模型验证使用的性能，功率和能源配置文件上收集的原型多核基于功率感知集群。
In energy efficient high end computing, a typical problem is to find an energy-performance efficient resource allocation for computing a given workload. An analytical solution to this problem includes two steps: first estimating the performances and energy costs for the workload running with various resource allocations, and second searching the allocation space to identify the optimal allocation according to an energy-performance efficiency measure. In this paper, we develop analytical models to approximate performance and energy cost for scientific workloads on multicore based power aware systems. The performance models extend Amdahl's law and power-aware speedup model to the context of multicore-based power aware computing. The power and energy models describe the power effects of resource allocation and workload characteristics. As a proof of concept, we show model parameter derivation and model validation using performance, power, and energy profiles collected on a prototype multicore based power aware cluster.