Parallel cloth simulation with GPGPU

In a 3D simulation, numerous physically and numerically related calculations are required to represent an object realistically. The existing CPU (central processing unit) technology, however, is incapable of handling such a large computational amount in real time. With the recent hardware-technology...

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Bibliographic Details
Published in:Multimedia tools and applications 2018-11, Vol.77 (22), p.30105-30120
Main Authors: Choi, Young-Hwan, Hong, Min, Choi, Yoo-Joo
Format: Article
Language:English
Subjects:
Algorithms
Central processing units
Cloth
Computation
Computer Communication Networks
Computer Science
Computer simulation
CPUs
Data Structures and Information Theory
Electronic devices
Graphics processing units
Mass-spring systems
Mathematical analysis
Multimedia Information Systems
Personal computers
Special Purpose and Application-Based Systems
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Summary:In a 3D simulation, numerous physically and numerically related calculations are required to represent an object realistically. The existing CPU (central processing unit) technology, however, is incapable of handling such a large computational amount in real time. With the recent hardware-technology advancements, the GPU (graphics processing unit) can be used not only for conventional rendering operations, but also for general-purpose computational functions. In this paper, a mass-spring system for which the CPU and GPU versions are tested under the PC and mobile environments wherein the GPGPU (general-purpose computing on GPUs) is applied is proposed. For this paper, a virtual cloth with a mass-spring system was freely dropped onto a table, and the CPU and GPU performances were compared. The computational GPU performances regarding the PC and mobile devices were improved by 9.41 times and 45.11 times, respectively, compared with the CPU. The proposed GPU mass-spring system was then implemented with an edge-centric algorithm and a node-centric algorithm. The edge-centric algorithm is divided into two parts as follows: one for the spring-force calculation and one for the node-position calculation. These two parts are combined into a single computational process for the node-centric algorithm. For this paper, the computational speeds of the two algorithms were measured. The node-centric algorithm is faster than the edge-centric algorithm under the PC environment, but the edge-centric algorithm is faster under the mobile environment.
ISSN:1380-7501
1573-7721
DOI:10.1007/s11042-018-6188-x