The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Jun. 26, 2018

Filed:

May. 22, 2013
Applicant:

Institute of Modern Physics, Chinese Academy of Sciences, Gansu, CN;

Inventors:

Lei Yang, Gansu, CN;

Ji Qi, Gansu, CN;

Yuan Tian, Gansu, CN;

Xiaofei Gao, Gansu, CN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 17/10 (2006.01); G06F 17/50 (2006.01);
U.S. Cl.
CPC ...
G06F 17/5009 (2013.01); G06F 17/10 (2013.01); G06T 2210/52 (2013.01); G06T 2210/56 (2013.01);
Abstract

The present invention provides a GPU-based particle flow simulation system and method which includes generating particle information based on particle modeling information inputted from a client terminal, and generating geometric solid information; receiving the particle information and the geometric solid information, determining which GPUs of which computation nodes are to be used based on the number of the particles and the number of idle GPUs in each of the computation nodes; determining which particles are to be processed in which GPUs of which computation nodes based on the determined number of GPUs and a space distribution of the particles, and performing allocation according to the determination result; stimulating particle flow by computing in parallel in the plurality of GPUs a force applied to each particle due to particle collision and thus an acceleration; and presenting a stimulation result. The embodiments of the present invention can implement a virtual experimental simulation of high-density particles, and improve computation efficiency while reducing power consumption.


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