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https://blogs.nvidia.com/blog/2014/02/25/cuda-by-numbers/
CUDA, the parallel programming model that unlocks the power of GPU acceleration, is growing fast.. There are 275 CUDA-based applications tuned to run on GPU accelerators, compared with 90 just three years ago. Most of these applications are household names for researchers and engineers, used every day to accelerate scientific discoveries and engineering results.
https://www.geforce.com/hardware/technology/cuda/applications
Using NVIDIA CUDA technology, 3D-Coat featuring voxel sculpting technology, provides an array of tools for 3D model sculpting, detailing and coloring. Nebula 3 Nebula is a VST multi-effect plug-in that is able to emulate and replicate several types of expensive audio equipment, eliminating the …
https://developer.nvidia.com/cuda-zone
CUDA® is a parallel computing platform and programming model developed by NVIDIA for general computing on graphical processing units (GPUs). With CUDA, developers are able to dramatically speed up computing applications by harnessing the power of GPUs.
https://www.nvidia.com/en-us/data-center/gpu-accelerated-applications/catalog/
Accelerate your computational research and engineering applications with NVIDIA® Tesla® GPUs. A companion processor to the CPU in a server, find out how Tesla GPUs increase application performance in many industries.
https://create.pro/blog/opencl-vs-cuda/
Nov 28, 2017 · CUDA is a closed Nvidia framework, it’s not supported in as many applications as OpenCL (support is still wide, however), but where it is integrated top quality Nvidia support ensures unparalleled performance.
https://www.infoworld.com/article/3299703/what-is-cuda-parallel-programming-for-gpus.html
The CUDA Toolkit includes libraries, debugging and optimization tools, a compiler, documentation, and a runtime library to deploy your applications. It has components that support deep learning ...
https://developer.nvidia.com/cuda-gpus
Recommended GPU for Developers NVIDIA TITAN RTX NVIDIA TITAN RTX is built for data science, AI research, content creation and general GPU development. Built on the Turing architecture, it features 4608, 576 full-speed mixed precision Tensor Cores for accelerating AI, and 72 RT cores for accelerating ray tracing. It also includes 24 GB of GPU memory for training neural networks with large batch ...
https://devtalk.nvidia.com/default/topic/1066488/cuda-setup-and-installation/x86-32-bit-support-for-cuda-to-build-32bit-opencv/
Nov 14, 2019 · Deployment and execution of CUDA applications on x86_32 is still supported, but is limited to use with GeForce GPUs. To create 32-bit CUDA applications, use the cross-development capabilities of the CUDA Toolkit on x86_64. Support for developing and running x86 32-bit applications on x86_64 Windows is limited to use with: GeForce GPUs CUDA Driver
https://www.geforce.com/hardware/technology/cuda/supported-gpus?field_gpu_type_value=All&page=1
GeForce® 940MX is designed to deliver a premium laptop experience, giving you up to 4X faster graphics performance for gaming while also accelerating photo and video-editing applications. Working together seamlessly with NVIDIA® Optimus®, GeForce 940MX gives you longer battery life …
https://docs.nvidia.com/cuda/volta-compatibility-guide/index.html
This application note, Volta Compatibility Guide for CUDA Applications, is intended to help developers ensure that their NVIDIA ® CUDA ® applications will run on GPUs based on the NVIDIA ® Volta Architecture. This document provides guidance to developers who are already familiar with programming in CUDA C++ and want to make sure that their software applications are compatible with Volta.
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