摘要
Simplified spherical harmonics approximation （SPN） equations are widely used in modeling light propagation in biological tissues. However, with the increase of order N, its computational burden will severely aggravate. We propose a graphics processing unit （GPU） accelerated framework for SPN equations. Compared with the conven- tional central processing unit implementation, an increased performance of the GPU framework is obtained with an increase in mesh size, with the best speed-up ratio of 25 among the studied cases. The influence of thread distribution on the performance of the GPU framework is also investigated.
Simplified spherical harmonics approximation （SPN） equations are widely used in modeling light propagation in biological tissues. However, with the increase of order N, its computational burden will severely aggravate. We propose a graphics processing unit （GPU） accelerated framework for SPN equations. Compared with the conven- tional central processing unit implementation, an increased performance of the GPU framework is obtained with an increase in mesh size, with the best speed-up ratio of 25 among the studied cases. The influence of thread distribution on the performance of the GPU framework is also investigated.
基金
partly supported by the National Natural Science Foundation of China(Nos.81227901,81571725,61471279,and 61405149)
the Natural Science Basic Research Plan in Shaanxi Province of China(Nos.2015JZ019 and 2015JQ6249)
the Fundamental Research Funds for the Central Universities(Nos.NSIZ021402 and NSIY061406)
