Abstract
The primary goal of cloth simulation is to express object behavior in a realistic manner and achieve real-time performance by following the fundamental concept of physic. In general, the mass–spring system is applied to real-time cloth simulation with three types of springs. However, hard spring cloth simulation using the mass–spring system requires a small integration time-step in order to use a large stiffness coefficient. Furthermore, to obtain stable behavior, constraint enforcement is used instead of maintenance of the force of each spring. Constraint force computation involves a large sparse linear solving operation. Due to the large computation, we implement a cloth simulation using adaptive constraint activation and deactivation techniques that involve the mass–spring system and constraint enforcement method to prevent excessive elongation of cloth. At the same time, when the length of the spring is stretched or compressed over a defined threshold, adaptive constraint activation and deactivation method deactivates the spring and generate the implicit constraint. Traditional method that uses a serial process of the Central Processing Unit (CPU) to solve the system in every frame cannot handle the complex structure of clothmodel in real-time. Our simulation utilizes the Graphic Processing Unit (GPU) parallel processing with compute shader in OpenGL Shading Language (GLSL) to solve the system effectively. In this paper, we design and implement parallel method for cloth simulation, and experiment on the performance and behavior comparison of the mass–spring system, constraint enforcement, and adaptive constraint activation and deactivation techniques the using GPU-based parallel method.
Highlights
The applications of physically based simulation have been widely applied in many industries, including film or animation, education, games, health care, and AR application
We proposed the parallel algorithm for sparse matrix–matrix multiplication (SpMM) of Compressed Sparse Row (CSR) format and Compressed Sparse Column (CSC) format by utilizing Graphic Processing Unit (GPU) library, such as atomic operations
The result show that the GPU-based parallel mass–spring system is on average 61 times faster than Central Processing Unit (CPU)-based mass–spring system single core. Another comparison shows that the GPU-based constraint enforcement is on average 124 times faster, which is faster than the naïve approach that is implemented on the CPU single core
Summary
The applications of physically based simulation have been widely applied in many industries, including film or animation, education, games, health care, and AR application. The naïve algorithm of cloth simulation that use a serial process of a CPU to compute force and find a new position in every frame cannot handle the complex structure of cloth simulation in real-time. OpenGL is used for rendering, so the additional GPGPU program or library can be excluded, since GLSL can be utilized to perform parallel processing of the cloth simulation by using OpenGL compute shader as a GPU kernel program. The specific contributions of our paper are: Cloth simulation is implemented based on the mass–spring system, implicit constraint enforcement, and adaptive constraint activation and deactivation, using the compute shader. The performance comparison result of the cloth simulation using the mass–spring system, constraint enforcement and adaptive constraint activation and deactivation method that are implemented on GLSL compute shader are provided as well. In order to compare and contrast each method understandably, we conduct an experiment on the scenario that the cloth receives a strong force pushing the cloth object
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