Benchmarking the Powering Computations for Application Tuning

Yonggang Che, Chuanfu Xu, Zhenghua Wang
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引用次数: 1

Abstract

Powering is an important operation in many computation intensive workloads. This paper investigates the performance of different styles to calculate the powering operations from the application level. A series of small benchmark codes that calculate the powering operations in different ways are designed. Their performance is evaluated on Intel Xeon CPU under Intel compilation environments. The results show that the number of floating-point operations and the related runtime are sensitive to the value of the exponent Y and how it is used. When Y is an immediate integer number whose value is known at compile time, the cost of powering is much less than the situation when Y is an integer variable whose value is known at runtime. When Y is defined as a real variable, the cost of powering is always high, be it equals to an integer number or not. Based on the investigations, performance optimizations are applied to a kernel subroutine from a real-world supersonic combustion simulation code, which intensively involves powering operations. The result shows that the performance of that subroutine is improved for 13.25 times on the Intel Xeon E5-2692 CPU.
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为应用程序调优测试强大的计算能力
在许多计算密集型工作负载中,供电是一项重要的操作。本文从应用层考察了不同风格的性能,计算了供电操作。设计了一系列小型基准代码,以不同的方式计算供电操作。在Intel编译环境下,在Intel Xeon CPU上对其性能进行了评估。结果表明,浮点运算的次数和相关的运行时间对指数Y的值及其使用方式很敏感。当Y是一个即时整数,其值在编译时已知时,启动的成本远低于Y是一个整数变量,其值在运行时已知时的情况。当Y被定义为实变量时,无论是否等于整数,供电成本总是很高的。在此基础上,将性能优化应用于来自真实世界超音速燃烧模拟代码的核心子程序,该程序主要涉及动力操作。结果表明,在Intel至强E5-2692 CPU上,该子程序的性能提高了13.25倍。
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