A Synthetic Benchmark
A Synthetic Benchmark
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DOI：
10.1093/comjnl/19.1.43
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发表时间：
1976
期刊：
影响因子：
--
通讯作者：
H. Curnow;B. Wichmann
中科院分区：
文献类型：
--
作者：
H. Curnow;B. Wichmann
一种简单的方法是通过基准程序来衡量的，除非仔细构建这样的程序，否则在安装中运行的数千个程序不太可能是衡量科学计算机的示例基准。目前的d：这与评估计算机功率的其他方法相比（1974年12月）。为了计时每个任务，幸运的是，获得的速度的比率与所执行的任务的性质差异很大。在机器上实际上可以通过高级语言来克服这些变化，以指定该方法的附加优势任何情况下，大多数科学编程都是用高级语言执行的，因此这些测量结果将是机器能力的更好指南，而不是基于使用低级语言的示例来测量ts。处理速度出现在Wichmann [7]中，它在微秒中允许在50台计算机上执行42个Algol 60中的基本语句。通过从此间隔进行相同的测量来找到该声明的时间，并除以两千次的重复数量。通过两个机器提供一个基本语句时间，时代之间的42个比率可以通过假设TIJ tij的时间（i = 1至n）提供了一个简单的比较度量。 ）在机器J（j = 1至m）满意度上
A simple method of measuring performance is by means of a benchmark program. Unless such a program is carefully constructed it is unlikely to be typical of the many thousands of programs run at an installation. An example benchmark for measuring the processor power of scientific computers is presente d: this is compared with other methods of assessing computer power. (Received December 1974) An important characteristic of computers used for scientifi c work is the speed of the central processor unit. A simple technique for comparing this speed for a variety of machines is to time some clearly defined task on each one. Un fortunately the ratio of speeds obtained varies enormously with the nature of the task being performed. If the task is defined informally in words, large variations c an be caused by small differences in the tasks actually performed on the machines. These variations can be largely overcome by using a high level language to specify the task. An additional advantage of this method is that the efficiency of the compile r and the differences in machine architecture are automatically taken into account. In any case, most scientific programming is performed in high level languages, so these measurements will be a better guide to the machine’s capabilities than measuremen ts based on use of low level languages. An example of the use of machine-independent languages to measure processing speed appears in Wichmann [7] which gives the times taken in microseconds to execute 42 basic statements in ALGOL 60 on some 50 machines. The times were measured by placing each statement in a loop executed sufficiently often to give a reasonable interval to measure. The time for the statement is found by taking from this interval the same measurement with a dummy statement and dividing by the number of repetitions. The two thousand or so time measurements provide a lot of information about the various implementations of ALGOL 60 but do not directly give a performance measure. With basic statement times for only two machines, the average of the 42 ratios between the times provides a simple comparative measure. This technique can be generalised by assuming that the times Tij for a statement i (i = 1 to n) on machine j (j = 1 to m) satisfies