Abstract
The paper describes additional features offered by new Kepler architecture of NVIDIA graphic processors, and their usage for creating high performance programs in a wide range of scientific compute-intensive applications. Recommendations are given for their use at realization of sci-tech computation algorithms by means of graphic processors. New capabilities of the parallel computation platform CUDA are also described, in particular, regarding a set of program development tool extensions for the Fortran, C and C++ languages. The extended capabilities make it possible to minimize the time of application development and to increase the programming productivity.
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