cuda的音标

Any GPU device has a device driver, so targeting it makes more sense than generating CUDA or OpenCL code which would require from users to install other SDKs.

所有GPU设备都有设备驱动，因此针对它来编程更合理，这样会比生成CUDA或者OpenGL的代码更好，因为那还需要用户安装其它的SDK。

The parallel programming model that GPU cluster applied is MPI+ CUDA. Firstly, the data of difference image will be assigned to each compute node in cluster, and then the assigned data are computed on GPU with parallel computing.

基于GPU集群的并行化方法采用MPI+CUDA的编程模型，先将待聚类的差异影像图分配到集群的各个计算节点中，然后在计算节点中利用GPU进行并行计算。

Appendix B lists the mathematical functions supported in CUDA.

附录B列举CUDA中支持的数学函数。