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Synthetic Floating-Point Workloader

IP.com Disclosure Number: IPCOM000060784D
Original Publication Date: 1986-May-01
Included in the Prior Art Database: 2005-Mar-09
Document File: 3 page(s) / 79K

Publishing Venue

IBM

Related People

Genduso, TB: AUTHOR [+2]

Abstract

This article describes a standard method by which floating-point performance of different systems can be tested. In the development of high performance floating-point processors, the need has arisen for a standard by which the floating-point performance of the different systems can be compared. Historically, the need to analyze floating-point performance is not new. One previously developed solution to the dilemma was to determine the type of high level operation (sine, cosine, matrix manipulation, integer to floating-point conversion, etc.) which normally is performed and creates a set of test kernels, each kernel representing adifferent type of numerical operation. Next, the ratio of frequency of occurrence between the different types of operations was determined.

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Synthetic Floating-Point Workloader

This article describes a standard method by which floating-point performance of different systems can be tested. In the development of high performance floating- point processors, the need has arisen for a standard by which the floating-point performance of the different systems can be compared. Historically, the need to analyze floating-point performance is not new. One previously developed solution to the dilemma was to determine the type of high level operation (sine, cosine, matrix manipulation, integer to floating-point conversion, etc.) which normally is performed and creates a set of test kernels, each kernel representing adifferent type of numerical operation. Next, the ratio of frequency of occurrence between the different types of operations was determined. From this research, a benchmark program, which today we call the Whetstone Benchmark, was created. The Whetstone Benchmark is actually a mix of the ten Whetstone kernels. This mix represents an average scientific application. Like most averages, this mix does not represent any real environment. The technique disclosed herein creates a set of mixes, each mix representing an actual engineering/scientific environment. Since new application environments have come into existence from the time the Whetstone kernels were developed, it is necessary to extend the kernel set to include the unique functions of these new environments (i.e., graphics, robotics, etc.). From this new kernel set a user- oriented, menu-driven, software interface, called the synthetic floating-point workloader (SFPW) is developed which performs the test benchmarks quickly and consistently. The SFPW interface converts the kernels into a test system. A high level flow chart for the use of the SFPW is shown in the drawing. The test system is initially program loaded (IPL). It is assumed that, before the IPL, the SFPW has been successfully compiled, linked and loaded into the system and exists as an executable task. The SFPW is then executed. The SFPW presents a menu of the environments which can be simulated. The analyst chooses an environment, or creates a new one, and begins the test. When the test is completed, the SFPW will report the time it took to run the test and the number of Whetstone instructions performed. The test is repeated for different environments and a floating-point performance profile of the processor is created. An added feature of the SFPW is that, once a test is completed, a sensitivity analysis of the test mix can be conducted. The SFPW will vary the ratios of the kernels in the test mix and rerun the test a number of times. Rather than generate a single performance value, this type of testing will produce a representation of how sensitive the floating-point performance is to the environment. The menus that a user might typically see when using the SFPW are set forth and described as follows:

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This is the first menu that the user...