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He took particular interest in mixing paints for his art classes, as well as his chemistry classes in Balwyn High School. His father, being the Superintendent of Melbourne's electrical power station , borrowed an organic chemistry text from the chemists in the quality control laboratory. This ultimately led to an intense interest in synthesizing Azo dyes. At around age 14, Gunther attempted to predict the color of azo dyes based on the chromophore - auxochrome combination.
Apart from drawing up empirical tables, this effort was largely unsuccessful due to his lack of knowledge of quantum theory.
Gunther taught physics at San Jose State University from Gunther was asked to analyze the thermal stability test data from the Voyager RTGs. He discovered that the stability of the silicon - germanium Si-Ge thermoelectric alloy was controlled by a soliton -based precipitation mechanism. Ultimately, he was recruited onto the Dragon multiprocessor workstation project where he also developed the PARCbench multiprocessor benchmark.
This was his first fore into computer performance analysis.
He also performed simulations for the design of the Reliant RM parallel database server. Gunther founded Performance Dynamics Company as a sole proprietorship, registered in California in , to provide consulting and educational services for the management of high performance computer systems with an emphasis on performance analysis and enterprise-wide capacity planning. He went on to release and develop his own open-source performance modeling software called "PDQ Pretty Damn Quick " around That software also accompanied his first textbook on performance analysis entitled The Practical Performance Analyst.
Several other books have followed since then. In , Gunther has embarked on joint research into quantum information systems based on photonics.
Analyzing Computer System Performance with Perl::PDQ
In its simplest rendition, this theory can be considered as providing the quantum corrections to the Abbe - Rayleigh diffraction theory of imaging and the Fourier theory of optical information processing. Inspired by the work of Tukey , Gunther explored ways to help systems analyst visualize performance in a manner similar to that already available in scientific visualization and information visualization. In , he developed a tool called Barry , which employs barycentric coordinates to visualize sampled CPU usage data on large-scale multiprocessor systems.
A barycentric 3-simplex] a tetrahedron , that can be swivelled on the computer screen using a mouse , has been found useful for visualizing packet network performance data. In , he co-founded the PerfViz google group. This scalability law was originally developed by Gunther in while he was employed at Pyramid Technology. Also, because each of the three terms has a definite physical meaning, they can be employed as a heuristic to determine where to make performance improvements in hardware platforms or software applications.
At a more fundamental level, the above equation can be derived  from the Machine Repairman queueing model: . Theorem Gunther : The universal scalability law is equivalent to the synchronous queueing bound on throughput in a modified Machine Repairman with state-dependent service times. Theorem Gunther : Amdahl's law for parallel speedup is equivalent to the synchronous queueing bound on throughput in a Machine Repairman model of a multiprocessor. From Wikipedia, the free encyclopedia. Neil James Gunther. Neil Gunther at Bletchley Park "A quantum leap is neither".
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Thanks for telling us about the problem. Return to Book Page. Makes performance analysis and queueing theory concepts simple to understand and available to anyone with a background in high school algebra Presents the practical application of these concepts in the context of modern, distributed, computer system designs Packed with helpful examples that are based on the author's experience analyzing the performance of large-scale systems Makes performance analysis and queueing theory concepts simple to understand and available to anyone with a background in high school algebra Presents the practical application of these concepts in the context of modern, distributed, computer system designs Packed with helpful examples that are based on the author's experience analyzing the performance of large-scale systems over the past 20 years.
Analyzing Computer System Performance with Perl: : PDQ by Neil J. Gunther
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