![]() The CPU and GPU are treated as separate devices that have their own memory spaces. As such, CUDA can be incrementally applied to existing applications. ![]() Serial portions of applications are run on the CPU, and parallel portions are offloaded to the GPU. Support heterogeneous computation where applications use both the CPU and GPU. With CUDA C/C++, programmers can focus on the task of parallelization of the algorithms rather than spending time on their implementation. Provide a small set of extensions to standard programming languages, like C, that enable a straightforward implementation of parallel algorithms. It enables dramatic increases in computing performance by harnessing the power of the graphics processing unit (GPU).ĬUDA was developed with several design goals in mind: Introduction ĬUDA ® is a parallel computing platform and programming model invented by NVIDIA. The installation instructions for the CUDA Toolkit on Microsoft Windows systems. ![]() ![]() CUDA Installation Guide for Microsoft Windows ![]()
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