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Modeling and analysis of performances for concurrent multithread applications on multicore and graphics processing unit systems

机译:多核和图形处理单元系统上并发多线程应用程序的性能建模和分析

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The capabilities of multicore processors lead them to be widely adopted in systems at any scale, since their are able to provide more computing power at a lower consumption and dissipation cost. System designers are challenged to a deeper understanding of multicore functioning in order to fully exploit them while keeping the optimal balance between cores utilization and optimal throughput, response time and energy usage.Besides the advancement of general purpose CPUs, the same technological evolution leads to the rise of GPUs, dramatic evolution of graphical coprocessors, that are now affordable, efficient, dedicated computing units, capable of parallel computing and equipped with facilities that make them suited for supporting the main CPU of a system in running ordinary applications. The availability of commercial off-the-shelf (COTS) multicore computers, eventually equipped with one or more GPUs, makes them the basic building block of data centers devoted to cloud applications or scientific computing.The way to optimal exploitation of such a wide amount of computing power passes through the ability of matching the best scheduling of hardware resources with the software characteristics of the applications. This requires appropriate models and evaluation methods.Simulation and analytical techniques are essential tools to support the design and the management process of such architectures, but a sound characterization of the workloads is required. Typical workloads consist in multithreaded applications, with different characteristics, that dynamically span over the cores of multiple machines, connected by fast networks.In this paper we propose several parametric performance models for different configurations of multicore machines, with or without GPU support, running multiple class multithreaded applications, aiming to supply a detailed modeling help for complex data centers. Copyright © 2015 John Wiley & Sons, Ltd.
机译:多核处理器的功能使它们能够在任何规模的系统中被广泛采用,因为它们能够以更低的功耗和耗散成本提供更多的计算能力。系统设计人员面临着对多核功能的更深刻理解的挑战,以便充分利用它们,同时保持内核利用率与最佳吞吐量,响应时间和能源使用之间的最佳平衡。除了通用CPU的进步以外,相同的技术发展还导致了多核功能的发展。 GPU的兴起,图形协处理器的飞速发展,现在已经可以负担得起,高效,专用的计算单元,能够进行并行计算,并配备了适合在运行普通应用程序时支持系统主CPU的功能。最终配备一个或多个GPU的商用现货(COTS)多核计算机的可用性使其成为致力于云应用程序或科学计算的数据中心的基本构建块。通过将最佳的硬件资源调度与应用程序的软件特征相匹配的能力,可以实现计算能力的提高。这需要适当的模型和评估方法。仿真和分析技术是支持此类体系结构的设计和管理过程的基本工具,但是需要对工作负载进行合理的描述。典型的工作负载由具有不同特征的多线程应用程序组成,这些应用程序动态地跨越由快速网络连接的多台计算机的核心。在本文中,我们针对具有或不具有GPU支持的多核计算机的不同配置提出了几种参数性能模型,这些模型可以运行多个类多线程应用程序,旨在为复杂的数据中心提供详细的建模帮助。版权所有©2015 John Wiley&Sons,Ltd.

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