twelve-ways

twelve-ways - Twelve Ways to Fool the Masses When Giving...

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Sheet1 Page 1 Twelve Ways to Fool the Masses When Giving Performance Results on Parallel Computers David H. Bailey 06/11/91 Ref: Supercomputing Review, Aug. 1991, pg. 54--55 Abstract Many of us in the field of highly parallel scientific computing recognize that it is often quite difficult to match the run time performance of the best conventional supercomputers. This humorous article outlines twelve ways commonly used in scientific papers and presentations to artificially boost performance rates and to present these results in the ``best possible light'' compared to other systems. The author is with the Numerical Aerodynamic Simulation (NAS) Systems Division at NASA Ames Research Center, Moffett Field, CA 94035. Many of us in the field of highly parallel scientific computing recognize that it is often quite difficult to match the run time performance of the best conventional supercomputers. But since lay persons usually don't appreciate these difficulties and therefore don't understand when we quote mediocre performance results, it is often necessary for us to adopt some advanced techniques in order to deflect attention from possibly unfavorable facts. Here are some of the most effective methods, as observed from recent scientific papers and technical presentations: 1. Quote only 32-bit performance results, not 64-bit results. We all know that it is hard to obtain impressive performance using 64-bit floating point arithmetic. Some research systems do not even have 64-bit hardware. Thus always quote 32-bit results, and avoid mentioning this fact if at all possible. Better still, compare your 32-bit results with 64-bit results on other systems. 32-bit arithmetic may or may not be appropriate for your application, but the audience doesn't need to be bothered with such details. 2. Present performance figures for an inner kernel, and then represent these figures as the performance of the entire application. It is quite difficult to obtain high performance on a complete large-scale scientific application, timed from beginning of execution through completion. There is often a great deal of data movement and initialization that depresses overall performance rates. A good solution to this dilemma is to present results for an inner kernel of an application, which can be souped up with artificial tricks. Then imply in your presentation that these rates are equivalent to the overall performance of the entire application.
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Sheet1 Page 2 3. Quietly employ assembly code and other low-level language constructs. It
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twelve-ways - Twelve Ways to Fool the Masses When Giving...

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