Automatic starting-stopping and computation task dynamic allocation method for mass parallel coarse particle computation

Abstract

The invention discloses an automatic starting-stopping and computation task dynamic allocation method for mass parallel coarse particle computation. The method comprises the following steps: defining parallel coarse particles according to a problem computation characteristic; dynamically allocating computation tasks in the parallel coarse particles and input parameters corresponding to the computation tasks to all processes including a master process by the master process according to a file marking technology and a dynamic allocation computation task strategy; dynamically allocating memories to the processes including the computation tasks based on an automatic starting-stopping technology; and after completion of parallel computation of all the parallel coarse particles, collecting output parameters of all the processes by the master process, and combining and integrating the output parameters to obtain a final result of complete running. Through adoption of the method, communications among the processes are reduced to the maximum extent; the hard disk reading-writing bottleneck occurring since a memory peak value is greater than an available physical memory during multi-process parallel computation is avoided; meanwhile, the problem of non-equivalent complexity of computation examples is solved perfectly; and the parallel computation efficiency is increased greatly.

Description

technical field [0001] The invention relates to the technical field of high-performance computing, in particular to a method for automatic start-stop and dynamic distribution of computing tasks in parallel with massive computing coarse particles. Background technique [0002] In the fields of optimization design of electromagnetic functional materials, logging response and inversion, complex electromagnetic environment and multi-physics field coupling calculation, marine environment numerical simulation, molecular dynamics and personalized drug design and screening, etc., a large number of large-scale numerical data of the same type are required. calculate. This kind of large-scale numerical calculation has different structures due to different computing instances, resulting in unequal computational complexity of different computing instances. For such unequal massive calculations, it is necessary to design high-efficiency parallel computing methods, fully considering the co...

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Problems solved by technology

The result of this comparison shows that if there are many open processes for parallel computing and no measures are taken, part of the hard disk storage space may be read as virtual memory during the computing process, which will reduce the running speed of the program by more than a hundred times

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