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引用次数: 0

摘要

多核主机系统和多核加速器设备的异构计算平台今年在主流HPC计算市场上迈出了重要的一步,惠普Apollo 6000 system的ProLiant XL250a服务器采用了英特尔®Xeon Phi™协处理器。尽管许多应用程序开发人员试图以与GPGPU加速平台相同的方式使用它,但这样做会丧失多核主机处理器的处理能力,并在业务操作中引入功率低效率。在本文中,我们提出了一个应用程序优化框架,将顺序遗留应用程序转换为高度并行的应用程序,利用主机CPU和加速器设备上的硬件资源来实现同步异构计算。作为案例研究,我们将研究如何应用该框架并采用结构化方法来开发期权定价应用程序,以利用异构计算环境的优势。
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A Performance Optimization Framework for the Simultaneous Heterogeneous Computing Platforms
Heterogeneous computing platforms with multicore host system and many-core accelerator devices have taken a major step forward in the mainstream HPC computing market this year with the announcement of HP Apollo 6000 System's ProLiant XL250a server features the Intel® Xeon Phi™ coprocessors. Although many application developers attempt to use it in the same way as GPGPU acceleration platforms, doing so forfeits the processing capability of multicore host processors and introduces power inefficiency in business operations. In this paper, we propose an application optimization framework to turn sequential legacy applications into highly parallel applications that make use of the hardware resources both on the host CPU and on the accelerator devices to enable simultaneous heterogeneous computing. As a case study, we look at how to apply this framework and adopt a structured methodology to develop option pricing applications to take advantages of a heterogeneous computing environment.
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Session details: Afternoon Session 2 Adaptive GPU Array Layout Auto-Tuning A Performance Optimization Framework for the Simultaneous Heterogeneous Computing Platforms Session details: Keynote Address Session details: Afternoon Session 1
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