Method for improving performance tuning speed of distributed system
A distributed system and performance technology, applied in transmission systems, biological neural network models, multi-programming devices, etc., can solve problems such as long measurement time, limited search capability, and reduced measurement time system performance.
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[0021] Premise: Assume that the distributed computing system we are tuning now contains n parameters {p 1 ,p 2 ,...,p n}, parameter p i The value range of is: [ p i ,p i ], the algorithm is as follows:
[0022] (1) Put all the [ p i ,p i ] linearly quantized into [0, 100].
[0023] (2) Randomly and uniformly take 200 sets of parameters {v in [0, 100] 1,1 , v 2,1 ,...,v n,1}{v 12 , v 22 ,...,v n2},...,{v 1,200 , v 2,200 ,...,v n,200} and linearly quantize it back to the original interval [ p i ,p i ].
[0024] (3) Test the output under the above 200 sets of parameters, and set the response time and throughput rate as (t 1,1 , r 2,1 ), (t 1,2 , r 2,2 ),…, (t 1,200 , r 2,200 ) Use the 200 sets of output results of the test to train a three-layer neural network model with two hidden layers (see Appendix 1 for the principle and analysis process of the model, and also see Neural Network, Chapter 4, page 111, Neural Network edited by Simon Haykin how to us...
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