Cluster based Monte Carlo Simulation of Light Transport in Multi-layered
by Chao Jiang, Pengcheng Li, Qingming Luo
Center for Biomedical Photonics, Wuhan
National Laboratory for Optoelectronics,
Huazhong University of Science
and Technology, Wuhan
430074, PR China
September 10, 2009
simulation is of great significance in simulating the light propagation in
tissues, which quantifies the light delivered to the treated tissue and is an
important factor for improving clinical results. However, Monte Carlo simulation is quite
time-consuming because of the extensive computational burden. It limits the
practical application of Monte Carlo
method greatly. Erik Alerstam et al developed a GPU
based Monte Carlo simulation program called “CUDAMCML” and it improves the
performance greatly compared with the conventional programs running on the
CPU. Lo et al also provides a multi-gpu supported
version on a single computer called “GPUMCML”. To further
improve the performance of GPU based Monte Carlo simulation for photon
transport in turbid media, We developed a new version of Monte Carlo program for simulation of light
transport in multi-layered tissues base on the GPU Cluster. We call it
"GCMCML"(GPU Cluster based MCML) in simple words. It has the same
function as Lihong Wang and Steven L. Jacques'
original "MCML" running on the CPU. In our "GCMCML",
Distributed Computing of GPU Clusters installed in different personal
computers within a local area network (LAN) are
employed to accelerate the simulation greatly. The latest version of GCMCML
supports multiple GPUs on each node of the cluster.
Moreover, We appreciate some nice insights of CUDAMCML of Erik Alerstam et al and the GPUMCML of Lo et al for optimizing
the performance of single GPU based MCML very much. They improve the
performance of our single-node program greatly.
GCMCML source codes package (updated on August 3rd 2010)
These packages include the following files: the source codes of GCMCML,
a Microsoft visual studio 2005 project, a makefile
for compile the program in Linux and seed file for generating random number .
There is also a manual which tells how to build the environment and use our
Some other tips
We recommend that the GPUs of each node are Geforce 9800GT with 512M
video memory or more advanced Nvidia GPU.
If you have any question, you can write to us using this email address: email@example.com