Title
Load-Prediction Parallelization for Computer Simulation of Electrocardiogram Based on GPU
Abstract
This paper introduces a parallel algorithm using GPU for computer simulation of Electrocardiogram (ECG) based on a 3-dimensional (3D) whole-heart model. The computer heart model includes approximately 50,000 discrete elements (cell models) inside a torso model represented by 344 nodal points with 684 triangular meshes. Since computational burden for computer simulation of ECGs is considerably heavy, we employ GPU to accelerate the speed of calculation. However, GPU is based on SIMD structure which is unsuited for branch structure, so that the computing capabilities of GPU are limited by the branch of program. In order to solve this problem, we present a GPU-based algorithm which concentrates on eliminating branches in computation and optimizing the calculation of electric potentials through the way of load-prediction. The new parallel algorithm accelerates the speed of calculation of ECGs to 6.18 times compared with the former algorithm. This study demonstrates an effective algorithm based on GPU for parallel computing in biomedical simulation study.
Year
DOI
Venue
2012
10.1109/MCSoC.2012.12
MCSoC
Keywords
Field
DocType
electrocardiography,whole-heart model,new parallel algorithm,gpu,load-prediction parallelization,effective algorithm,mesh generation,graphics processing units,former algorithm,triangular mesh,medical signal processing,cell model,ecg,3d whole-heart model,electric potentials,computer heart model,eliminating branches,parallel algorithms,torso model,3-dimensional whole-heart model,simd structure,digital simulation,parallel algorithm,solid modelling,nodal points,parallel computing,cell models,electrocardiogram,computer simulation,gpu-based algorithm,biomedical simulation study,heart,kernel,computational modeling
Kernel (linear algebra),Torso,Polygon mesh,Computer science,Cardinal point,Parallel algorithm,Parallel computing,SIMD,Computational science,Mesh generation,Computation
Conference
ISBN
Citations 
PageRank 
978-0-7695-4800-5
1
0.36
References 
Authors
3
6
Name
Order
Citations
PageRank
Wenfeng Shen13210.23
Liang Wang21567158.46
Jie Li310.36
Weimin Xu4617.98
Daming Wei521544.97
Xin Zhu67316.49