See the API documentation for more information CUDA 10.0 adds support for new programming constructs called CUDA Graphs, a new asynchronous task-graph programming model that enables more efficient launch and execution.CUDA 10.0 adds support for the Turing architecture (compute_75 and sm_75).Using built-in capabilities for distributing computations across multi-GPU configurations, scientists and researchers can develop applications that scale from single GPU workstations to cloud installations with thousands of GPUs 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, you can develop, optimize and deploy your applications on GPU-accelerated embedded systems, desktop workstations, enterprise data centers, cloud-based platforms and HPC supercomputers. The NVIDIA CUDA Toolkit provides a development environment for creating high performance GPU-accelerated applications.
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