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The Release Notes for the CUDA Toolkit. This guide provides the minimal first-steps instructions for installation and verifying CUDA on a standard system. This guide discusses how to install and check for correct operation of the CUDA Development Tools on C# download pdf from url Windows systems.

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This guide discusses how to install and check for correct operation of the CUDA Development Tools on Mac OS X systems. This guide provides a detailed discussion of the CUDA programming model and programming interface. It then describes the hardware implementation, and provides guidance on how to achieve maximum performance. This guide presents established parallelization and optimization techniques and explains coding metaphors and idioms that can greatly simplify programming for CUDA-capable GPU architectures. The intent is to provide guidelines for obtaining the best performance from NVIDIA GPUs using the CUDA Toolkit. This application note is intended to help developers ensure that their NVIDIA CUDA applications will run properly on GPUs based on the NVIDIA Maxwell Architecture. This document provides guidance to ensure that your software applications are compatible with Maxwell.

This application note is intended to help developers ensure that their NVIDIA CUDA applications will run properly on GPUs based on the NVIDIA Pascal Architecture. This document provides guidance to ensure that your software applications are compatible with Pascal. This application note is intended to help developers ensure that their NVIDIA CUDA applications will run properly on GPUs based on the NVIDIA Volta Architecture. This document provides guidance to ensure that your software applications are compatible with Volta. Kepler is NVIDIA’s 3rd-generation architecture for CUDA compute applications. Applications that follow the best practices for the Fermi architecture should typically see speedups on the Kepler architecture without any code changes. This guide summarizes the ways that applications can be fine-tuned to gain additional speedups by leveraging Kepler architectural features.

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Maxwell is NVIDIA’s 4th-generation architecture for CUDA compute applications. Applications that follow the best practices for the Kepler architecture should typically see speedups on the Maxwell architecture without any code changes. This guide summarizes the ways that applications can be fine-tuned to gain additional speedups by leveraging Maxwell architectural features. Pascal is NVIDIA’s 5th-generation architecture for CUDA compute applications.

Applications that follow the best practices for the Maxwell architecture should typically see speedups on the Pascal architecture without any code changes. This guide summarizes the ways that applications can be fine-tuned to gain additional speedups by leveraging Pascal architectural features. Volta is NVIDIA’s 6th-generation architecture for CUDA compute applications. Applications that follow the best practices for the Pascal architecture should typically see speedups on the Volta architecture without any code changes. This guide summarizes the ways that applications can be fine-tuned to gain additional speedups by leveraging Volta architectural features. PTX exposes the GPU as a data-parallel computing device. This document explains how CUDA APIs can be used to query for GPU capabilities in NVIDIA Optimus systems.

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