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Nvidia Cuda

General Information

compiler for parallel CUDA codes

CUDA Toolkit 11.0 Update 1 Downloads | NVIDIA Developer

https://developer.nvidia.com/cuda-downloads

Operating System Architecture Compilation Distribution Version Installer Type Do you want to cross-compile? Yes No Select Host Platform.

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CUDA Zone | NVIDIA Developer

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...

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CUDA - Wikipedia

https://en.wikipedia.org/wiki/CUDA

CUDA (Compute Unified Device Architecture) is a parallel computing platform and application programming interface (API) model created by Nvidia.

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GitHub - NVIDIA/cuda-samples: Samples for CUDA Developers which...

https://github.com/NVIDIA/cuda-samples

For Microsoft platforms, NVIDIA's CUDA Driver supports DirectX. Few CUDA Samples for Windows demonstrates Vulkan is a low-overhead, cross-platform 3D graphics and compute API.

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nvidia/cuda - Docker Hub

https://hub.docker.com/r/nvidia/cuda

CUDA is a parallel computing platform and programming model developed by NVIDIA for general computing on graphical processing units (GPUs). With CUDA, developers can dramatically speed up...

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Nvidia CUDA H.264 Encoder for video and screen recording

https://www.bandicam.com/support/tips/nvidia-cuda/

If your graphics card supports the Nvidia CUDA H.264 encoder, you can enhance the recording Bandicam 1.9.0 or a higher version supports the Nvidia CUDA H.264 encoder, so Bandicam users...

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Вышла Nvidia Cuda 11.0 — Актуальные Новости Из Геймдева На...

https://dtf.ru/s/gamedevnews/167238-vyshla-nvidia-cuda-11-0

Вышла NVIDIA CUDA 11.0 Поддержка микроархитектуры Ampere GPU (compute_80 и sm_80).

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NVIDIA CUDA

http:///10.2172/1532687

Jonas Lippuner, 2019, 'NVIDIA CUDA'

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Evolving a CUDA kernel from an nVidia template

http://dx.doi.org/10.1109/cec.2010.5585922

Rather than attempting to evolve a complete program from scratch we demonstrate genetic interface programming (GIP) by automatically generating a parallel CUDA kernel with identical functionality to existing highly optimised ancient sequential C code (gzip). Generic GPGPU nVidia kernel C++ code is converted into a BNF grammar. Strongly typed genetic programming uses the BNF to generate compilable and executable graphics card kernels. Their fitness is given by running the population on a GPU with randomised subsets of training data itself derived from gzip's SIR test suite. Back-to-back validation uses the original code as a test oracle.

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Efficient Parallel CUDA Random Number Generator on NVIDIA GPUs

http:///10.5626/jok.2015.42.12.1467

Youngtae Kim,Gyuhyeon Hwang, 2015, 'Efficient Parallel CUDA Random Number Generator on NVIDIA GPUs', Journal of KIISE, vol. 42, no. 12, pp. 1467-1473

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NVCR: A Transparent Checkpoint-Restart Library for NVIDIA CUDA

http://xplorestaging.ieee.org/ielx5/60[...]/6008799/06008825.pdf?arnumber=6008825

Today, CUDA is the de facto standard programming framework to exploit the computational power of graphics processing units (GPUs) to accelerate various kinds of applications. For efficient use of a large GPU-accelerated system, one important mechanism is checkpoint-restart that can be used not only to improve fault tolerance but also to optimize node/slot allocation by suspending a job on one node and migrating the job to another node. Although several checkpoint-restart implementations have been developed so far, they do not support CUDA applications or have some severe limitations for CUDA support. Hence, we present a checkpoint-restart library for CUDA that first deletes all CUDA resources before check pointing and then restores them right after check pointing. It is necessary to restore each memory chunk at the same memory address. To this end, we propose a novel technique that replays memory related API calls. The library supports both CUDA runtime API and CUDA driver API. Moreover, the library is transparent to applications, it is not necessary to recompile the applications for check pointing. This paper demonstrates that the proposed library can achieve checkpoint-restart of various applications at acceptable overheads, and the library also works for MPI applications such as HPL.

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Сеченов П.А., Оленников А.А. Применение технологии параллельного программирования NVIDIA CUDA в задаче расплавления шарообразной частицы

http:///10.25136/2306-4196.2018.5.20345

2018, 'Сеченов П.А., Оленников А.А. Применение технологии параллельного программирования NVIDIA CUDA в задаче расплавления шарообразной частицы', Кибернетика и программирование, vol. 5, no. 5, pp. 8-14

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Efficient implementation of integrall image algorithm on NVIDIA CUDA

http://xplorestaging.ieee.org/ielx7/83[...]/8379817/08379824.pdf?arnumber=8379824

GPU computing makes it possible to perform more efficient implementation results by trying to optimize tasks that require massively parallel computing due to its particular capabilities. This is the main reason for the increase in the number of implemented GPU algorithms. Compared to the CPU, GPU computing has proved its efficiency in accelerating the processing of algorithms. This paper presents an implementation of the integral image algorithm on GPU by using the programming language CUDA. Integral image is important and crucial step in many image-processing algorithms. We also show a comparison between the performance of our algorithm on CPU and GPU on as well as the accelerations obtained. We also compare our algorithm with other GPU implementations using the programming language CUDA. The achieved results show clearly the efficiency of our algorithm. We achieve high speedup results comparing to other CPU and the GPU implementations.

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Application of NVIDIA CUDA Technology for Numerical Simulation of Electromagnetic Pulses Propagation

http:///10.14258/izvasu(2015)1.1-06

Ilya Molostov,Vsevolod Scherbinin, 2015, 'Application of NVIDIA CUDA Technology for Numerical Simulation of Electromagnetic Pulses Propagation', Izvestiya of Altai State University

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CUDA-accelerated Computational Fluid Dynamics (NVIDIA Webinar)

https://figshare.com/articles/CUDA-acc[...]Fluid_Dynamics_NVIDIA_Webinar_/8324921

This webinar discusses how NVIDIA GPUs and NVIDIA CUDA can enable high-fidelity Computational Fluid Dynamics for Higher Education and Research. Flow field computations for transient and turbulent flow problems are very compute-intensive and time-consuming. Popular existing numerical techniques often compromise on the underlying physics or require a massive amount of computational resources. Accurate high-fidelity CFD simulations on locally available hardware hence are highly appreciated by academia and industry. After a brief review of the theoretical basics and implementation details of a CUDA-accelerated CFD solver, results from several international research projects are presented. They all demonstrate that GPU computing can be a game changer for state-of-the art research projects in many relevant areas of Computational Fluid Dynamics.

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Parallelization of the conjugate gradient method using the technology NVidia Cuda

http:///10.17117/nv.2014.02.155

G.R. Shangareeva,S.A. Mustafina, 2014, 'Parallelization of the conjugate gradient method using the technology NVidia Cuda', Scientific Bulletin, no. 2, pp. 155-162

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NVIDIA cuda software and gpu parallel computing architecture

http://dx.doi.org/10.1145/1296907.1296909

In the past, graphics processors were special purpose hardwired application accelerators, suitable only for conventional rasterization-style graphics applications. Modern GPUs are now fully programmable, massively parallel floating point processors. This talk will describe NVIDIA's massively multithreaded computing architecture and CUDA software for GPU computing. The architecture is a scalable, highly parallel architecture that delivers high throughput for data-intensive processing. Although not truly general-purpose processors, GPUs can now be used for a wide variety of compute-intensive applications beyond graphic.

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Stereoscopic video chroma key processing using NVIDIA CUDA

http:///10.2478/v10065-012-0039-6

Jarosław Sagan, 2013, 'Stereoscopic video chroma key processing using NVIDIA CUDA', Annales UMCS, Informatica, vol. 13, no. 1

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GPU computing with NVIDIA CUDA

http:///10.1145/1281500.1281647

Ian Buck, 2007, 'GPU computing with NVIDIA CUDA', ACM SIGGRAPH 2007 courses on - SIGGRAPH '07

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Canny edge detection on NVIDIA CUDA

http://xplorestaging.ieee.org/ielx5/45[...]/4562948/04563088.pdf?arnumber=4563088

The Canny edge detector is a very popular and effective edge feature detector that is used as a pre-processing step in many computer vision algorithms. It is a multi-step detector which performs smoothing and filtering, non-maxima suppression, followed by a connected-component analysis stage to detect ldquotruerdquo edges, while suppressing ldquofalserdquo non edge filter responses. While there have been previous (partial) implementations of the Canny and other edge detectors on GPUs, they have been focussed on the old style GPGPU computing with programming using graphical application layers. Using the more programmer friendly CUDA framework, we are able to implement the entire Canny algorithm. Details are presented along with a comparison with CPU implementations. We also integrate our detector in to MATLAB, a popular interactive simulation package often used by researchers. The source code will be made available as open source.

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Evolving a CUDA kernel from an nVidia template

http:///10.1109/cec.2010.5585922

W. B. Langdon,M. Harman, 2010, 'Evolving a CUDA kernel from an nVidia template', IEEE Congress on Evolutionary Computation

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Parallelizing and optimizing LIP-canny using NVIDIA CUDA

http://www.springerlink.com/index/pdf/10.1007/978-3-642-13033-5_40

The Canny algorithm is a well known edge detector that is widely used in the previous processing stages in several algorithms related to computer vision. An alternative, the LIP-Canny algorithm, is based on a robust mathematical model closer to the human vision system, obtaining better results in terms of edge detection. In this work we describe LIP-Canny algorithm under the perspective from its parallelization and optimization by using the NVIDIA CUDA framework. Furthermore, we present comparative results between an implementation of this algorithm using NVIDIA CUDA and the analogue using a C/C++ approach.

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Inter-Pixel Filtrering of Digital Images with CUDA from NVIDIA

http:///10.24132/csrn.2020.3001.3

José Valero, 2020, 'Inter-Pixel Filtrering of Digital Images with CUDA from NVIDIA', Computer Science Research Notes

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Exploring NVIDIA-CUDA for video coding

http://dl.acm.org/ft_gateway.cfm?id=1730839&ftid=763010&dwn=1

Today, world is rapidly turning to high definition multimedia. From engineering and programming point of view, this usually means more computation is needed and more memory space is required to achieve these higher qualities. In this paper we explore the use of parallelization opportunities in graphics processors to accelerate video encoding. We evaluate the NVIDIA CUDA[1] toolkit and evaluate the performance of motion estimation in video encoding. The main goal of this paper is to evaluate the capabilities of NVIDIA/CUDA and develop a process for implementing video/multimedia applications. We have discovered that the difference in performance when CUDA is not used properly can be over 100x. We show how we were able to use CUDA capabilities to reduce the motion estimation time from 7000 milli seconds to 70 milli seconds.

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cuThomasBatch and cuThomasVBatch, CUDA Routines to compute batch of tridiagonal systems on NVIDIA GPUs

http:///10.1002/cpe.4909

Pedro Valero-Lara,Ivan Martínez-Pérez,Raül Sirvent,Xavier Martorell,Antonio J. Peña, 2018, 'cuThomasBatch and cuThomasVBatch, CUDA Routines to compute batch of tridiagonal systems on NVIDIA GPUs', Concurrency and Computation: Practice and Experience, vol. 30, no. 24, p. e4909

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Nvidia's GeForce RTX 3090, RTX 3080, and 3070 specs have been leaked

https://www.techspot.com/news/86559-nv[...]rce-rtx-3090-3080-3070-specs-have.html

There's less than 24 hours before Nvidia makes the official debut of Ampere on consumer RTX graphics cards, but leaks have kept on coming. Slides and photos from manufacturer Gainward have all but ...

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Nvidia’s RTX 3090 & 3080 Specs Have Leaked Before Its Launch And They Seem Like Gaming Monsters

https://www.mensxp.com/technology/game[...]nd-they-seem-like-gaming-monsters.html

The leak comes from videocardz.com and it shows that Nvidia is planning to launch two GPUs at the event and an additional video card some point later. The cards will be the GeForce RTX 3090, GeForce ...

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Nvidia’s RTX 3080 and 3090 graphics cards are leaked with pics and reported specs

https://www.techradar.com/news/nvidias[...]re-leaked-with-pics-and-reported-specs

Nvidia’s GeForce RTX 3080 and RTX 3090 have witnessed some major leakage, with images from two manufacturers spilled online – plus the purported final specs of the graphics cards – and pics of the RTX ...

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Nvidia’s Datacenter Revenue Has Surpassed Gaming for the First Time

https://www.extremetech.com/extreme/31[...]-for-the-first-time-in-company-history

Nvidia racked up a record quarter, for multiple reasons. Data center revenue beat gaming for the first time ever, pushing Nvidia to its best Q2 in history.

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NVIDIA GeForce RTX 3080 and RTX 3070 specs: here's what we know so far

https://www.tweaktown.com/news/74808/n[...]s-heres-what-we-know-so-far/index.html

We just had some GeForce RTX 3090 leaked specs, now it's time for the RTX 3080 and RTX 3070: RTX 3080 should have 10/20GB RAM.

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Nvidia RTX 30 series specifications tip up

https://www.fudzilla.com/news/graphics[...]a-rtx-30-series-specifications-show-up

RTX 3090, RTX 3080 and RTX 3070 incoming As we are close to the official announcement, it comes as no surprise that we are hearing more about Nvidia's upcoming RTX 30 series cards, and so far, ...

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Nvidia could become the Apple of the data center, analyst contends

https://www.marketwatch.com/story/nvid[...]ok-cap-run-up-2020-08-20?mod=home-page

Nvidia Corp. could come to dominate the data center the way Apple Inc. did smartphones, according to one analyst amid several glowing reports from ...

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Alleged GeForce RTX 3090, 3080 and 3070 Specifications Leak Just Ahead Of Launch

https://hothardware.com/news/geforce-r[...]rtx-3090-3080-3070-specifications-leak

Supposed specifications for three of NVIDIA's next generation GeForce RTX graphics cards have leaked out just days ahead of a scheduled GeForce Special Event.

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How to Enable CUDA on Premiere & After Effects (nVidia GPUs Only)

How to Enable CUDA on Premiere & After Effects (nVidia GPUs Only)

GPU-Z: \r\rLike on Facebook! Stalk Me on Twitter! Stalk Me on Instagram!\r\rREMEMBER, THIS IS UNOFFICIAL TWEAK! IT DOES NOT WORK WITH EVERY CARD! I cannot answer questions such as Will this work with X card? because .\r\rHey all! In this video I will show you how to enable GPU acceleration on Adobe Premiere and Adobe After Effects, for better pre-render and render times.\r\rCUDA. The Best Way To Get Your Videos Rendered! Hit the LIKE button if this video helped you out! Download the drivers: .

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Nvidia Quadro 4000 256CORE Cuda 2GB Dual-link Dvi Dual Disp Port

Nvidia Quadro 4000 256CORE Cuda 2GB Dual-link Dvi Dual Disp Port

Get Detail Review And Special Big Sale Price NOW!!! Click Link Below: http://www.amazon.com/exec/obidos/ASIN/B004GV0JUU/most-wanted-product-20 Nvidia Quadro 4000 256CORE Cuda 2GB Dual-link Dvi Dual Disp Port Disclaimer: I am a participant in the Amazon Services LLC Associates Program, an affiliate advertising program designed to provide a means for sites to earn advertising fees by advertising and linking to Amazon. Amazon and the Amazon logo are trademarks of Amazon, Inc. or its affiliates.

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Cuda, cudeńka...

Cuda, cudeńka...

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