CUDA FORTRAN efficient programming practice Since 2007, with NVIDIA GPU as the representative of accelerator parallel computing, the share of supercomputers with accelerators in top 500 has increased year by year, and the mainstream application software supporting accelerators has also grown explosively. There are millions of technicians studying accelerator computing, and universities and research institutions around the world are competing to offer relevant courses. To enable FORTRAN applications to use GPU acceleration, the Portland group designed CUDA FORTRAN language, which is supported in its own PGI compiler. The application of meteorology, theoretical physics and other fields can make use of the powerful computing power of GPU after simple transformation.

Filename	Size	Update
CUDA Fortran 高效编程实践.pdf	2618856	2019-11-20
__MACOSX	0	2019-11-20
__MACOSX\._CUDA Fortran 高效编程实践.pdf	3044	2019-11-20

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