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A two-stage scheduling method for stress cloud simulation platform of electronic products

A simulation platform and electronic product technology, applied in the computer field, can solve problems such as poor computing efficiency

Active Publication Date: 2019-02-15
BEIHANG UNIV
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  • Claims
  • Application Information

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Problems solved by technology

[0007] Aiming at the problem of poor calculation efficiency due to the need to calculate multiple simulation test samples for reliability prediction based on fault behavior considering multiple task profiles, the present invention proposes a two-stage scheduling method for an electronic product stress cloud simulation platform, including the following steps :

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  • A two-stage scheduling method for stress cloud simulation platform of electronic products
  • A two-stage scheduling method for stress cloud simulation platform of electronic products
  • A two-stage scheduling method for stress cloud simulation platform of electronic products

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Embodiment Construction

[0063] In this application, after the multi-simulation test sample submits the request, the job scheduler will schedule the job requests backlogged in the job queue according to the preset scheduling method. The scheduling process is divided into two stages: job sorting and assignment. In the job sorting stage, the maximum weight priority algorithm is adopted, and the job with the largest weight is ranked first after comprehensively considering factors such as job calculation amount, job execution efficiency, and job waiting time. The genetic algorithm is used in the job allocation stage to ensure that the overall job set is expected to complete in the shortest time.

[0064] The specific implementation steps are introduced from the maximum weight priority strategy, the performance priority scheduling strategy based on genetic algorithm and the overall scheduling strategy:

[0065] In step S1, the simulation system receives test sample data, each test sample data is packaged i...

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Abstract

The invention provides a two-stage scheduling method of an electronic product stress cloud simulation platform, which comprises the following steps: S1, packaging each test sample data into a job of asimulation system and enters a job sorting queue; S2, standardizing the job priority, job length and job waiting time; S3, calculating a maximum weight priority strategy index matrix; S4, selecting the number of jobs exceeding the number of servers and entering the job distribution queue; S5 Input population size, catastrophe probability, crossover probability and iteration times; S6 initializinggenetic population; S7 calculating individual fitness evaluation; S8 selection; S9 crossing; S10 mutation; S11 a loop performs step S7-S10 reaches the iteration times and outputs the chromosome withthe largest individual fitness value in the population. The system assigns jobs to different servers according to the chromosomes. This method not only considers the job priority, job length and jobwaiting time, but also ensures the fastest use of limited servers for calculation.

Description

technical field [0001] The invention belongs to the technical field of computers, and in particular relates to a two-stage scheduling method for an electronic product stress cloud simulation platform. Background technique [0002] Product reliability prediction refers to the work of estimating the reliability of a product under given working conditions, where the working conditions are mainly heat and vibration. At present, reliability prediction based on fault behavior considering multiple mission profiles is the main approach. It needs to calculate multiple simulation test samples, use simulation software to perform multi-stress simulation, and predict single-point failure and product reliability based on physical models. A single computer can no longer meet the requirements of its calculation efficiency. [0003] In the calculation process, it is necessary to use simulation software for multi-stress simulation. But while the accuracy of the simulation software is gettin...

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Application Information

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IPC IPC(8): G06F17/50
CPCG06F30/23
Inventor 陈颖方家玥康锐
Owner BEIHANG UNIV
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