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首页> 外文会议>Instrumentation and Measurement Technology Conference (I2MTC), 2012 IEEE International >Design and performance measurement of a high-performance computing cluster
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Design and performance measurement of a high-performance computing cluster

机译：高性能计算集群的设计和性能评估

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Graphics processor units (GPU) are specialized hardware accelerators that can be utilized for computations needing high parallelism and high memory bandwidth. Propelled by the attractive Flops/$ ratio and its capability to outperform a CPU cluster at the equivalent cost, large-scale GPU clusters are gaining popularity in the high-performance computing (HPC) community. However, the design challenges associated with the setup and application development process for an efficient HPC cluster includes: a) data movement and locality on the hardware accelerators; b) task mapping and allocation; and c) setting up a well-balanced system. In this paper, we present our experience setting up a GPU cluster for HPC applications; particularly signal processing for digital wideband receivers. We describe the architecture, hardware and software platform of the proposed cluster. The proposed GPU cluster implementing a 1.25 GHz digital wideband receiver was compared and contrasted against a HPC based predecessor receiver system. The adaptability of the GPU cluster was further demonstrated by utilizing it for a multiple receiver implementation that demanded higher data processing capability and throughput.
机译：图形处理器单元（GPU）是专用的硬件加速器，可用于需要高并行度和高内存带宽的计算。诱人的Flops / $比率及其以等效成本胜过CPU群集的能力的推动下，大型GPU群集在高性能计算（HPC）社区中越来越受欢迎。但是，与有效的HPC群集的设置和应用程序开发过程相关的设计挑战包括：a）硬件加速器上的数据移动和局部性； b）任务映射和分配； c）建立一个平衡的系统。在本文中，我们介绍了为HPC应用设置GPU集群的经验。特别是数字宽带接收机的信号处理。我们描述了所建议集群的体系结构，硬件和软件平台。将提议的实现1.25 GHz数字宽带接收机的GPU集群与基于HPC的前身接收机系统进行了对比。通过将GPU群集用于要求更高数据处理能力和吞吐量的多接收器实施中，进一步证明了GPU群集的适应性。

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