Your CUDA applications can be deployed across all NVIDIA GPU families available on-premise and on GPU instances in the cloud. For developing custom algorithms, you can use available integrations with commonly used languages and numerical packages as well as well-published development APIs. GPU-accelerated CUDA libraries enable drop-in acceleration across multiple domains such as linear algebra, image and video processing, deep learning, and graph analytics. The toolkit includes GPU-accelerated libraries, debugging and optimization tools, a C/C++ compiler, and a runtime library to deploy your application. With the CUDA Toolkit for macOS, you can develop, optimize, and deploy your applications on GPU-accelerated embedded systems, desktop workstations, enterprise data centers, cloud-based platforms, and HPC supercomputers. NVIDIA CUDA Toolkit for Mac provides a development environment for creating high-performance GPU-accelerated applications.
