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Professional CUDA C Programming

multiple industrial sectors, Professional CUDA C Programming presents CUDA -- a parallel computing platform and programming model designed to ease;

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Hands-On GPU Programming with Python and CUDA

Nsight Effectively use CUDA libraries such as cuBLAS, cuFFT, and cuSolver Apply GPU programming to modern data science applications Book;

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CUDA Programming

detailed guide to CUDA with a grounding in parallel fundamentals. It starts by introducing CUDA and bringing you up to speed on GPU parallelism and;

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Introduction to Cuda and Gpu Programming

introduction to popular CUDA libraries (such as cuBLAS, cuFFT, NPP, and Thrust),the OpenCL programming language, an overview of GPU programming using;

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Hands-On GPU-Accelerated Computer Vision with OpenCV and CUDA

power of GPU Key Features Explore examples to leverage the GPU processing power with OpenCV and CUDA Enhance the performance of algorithms on;

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Image Processing Using CUDA

. Initially shader based frameworks like GLSL, Cg etc have been used for GP-GPU. NVIDIA has developed CUDA to write scalable parallel programs in C;

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GPU Parallel Program Development Using CUDA

their horizons. It provides a brief introduction to popular CUDA libraries (such as cuBLAS, cuFFT, NPP, and Thrust),the OpenCL programming;

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CUDA Fortran for Scientists and Engineers

experience, and cover the basics along with best practices for efficient GPU computing using CUDA Fortran. To help you add CUDA Fortran to;

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Programming Massively Parallel Processors

-point format, parallel patterns, and dynamic parallelism are covered in depth. This best-selling guide to CUDA and GPU parallel programming has;

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CUDA Application Design and Development

needs of working software developers who need to understand GPU programming with CUDA and increase efficiency in their projects. CUDA;

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CUDA for Engineers

CUDA for Engineers gives you direct, hands-on engagement with personal, high-performance parallel computing, enabling you to do;

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Hands-On GPU Computing with Python

PyCuda and PyOpenCL Learn to use the CUDA libraries like CuDNN for deep learning on GPUs Book DescriptionGPUs are proving to be excellent general;

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GPU Computing Gems Jade Edition

explains how GPU execution is achieved with algorithm implementation techniques and approaches to data structure layout. More specifically, it;

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Programming Massively Parallel Processors

specifically for massively parallel environments. Shows you how to achieve both high-performance and high-reliability using the CUDA;

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GPU Programming in MATLAB

Computing Toolbox and other MATLAB toolboxes for GPU computing, which allow applications to be ported straightforwardly onto GPUs without extensive;

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GPU Computing Gems Emerald Edition

, allowing knowledge to cross-pollinate across the GPU spectrum. Many examples leverage NVIDIA's CUDA parallel computing architecture, the most;

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Accelerating MATLAB with GPU Computing

> Starting with the basics, setting up MATLAB for CUDA (in Windows, Linux and Mac OS X) and profiling, it then guides users through advanced topics;

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Programming Massively Parallel Processors

concepts of parallel programming and GPU architecture, exploring, in detail, various techniques for constructing parallel programs. Case;

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Multicore and GPU Programming

Multicore and GPU Programming: An Integrated Approach, Second Edition offers broad coverage of key parallel computing tools, essential;

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Programming Massively Parallel Processors

of parallel programming and GPU architecture. Concise, intuitive, and practical, it is based on years of road-testing in the authors' own parallel;

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Fast Medical Image Reconstruction using Graphics Processing Unit

to running CUDA code in MATLAB. This book exercises the acceleration of MRI reconstruction algorithm on NVIDIA's GeForce G 103M based GPU and;

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GPGPU Programming for Games and Science

; configuring two or more GPUs to act as one; and IEEE floating-point support on a GPU. The book goes on to explore practical matters;

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GPGPU Programming for Games and Science

GPUs to act as one; and IEEE floating-point support on a GPU. The book goes on to explore practical matters of programming a GPU, including;

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An Introduction to Parallel Programming

An Introduction to Parallel Programming, Second Edition presents a tried-and-true tutorial approach that shows students how to develop;

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Real-time Knowledge-based Fuzzy Logic Model for Soft Tissue Deformation

continues to grow, as there is a major bottleneck in surgical simulation designation and every patient is unique. Deformable models, the core;

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Gpu Gems 3

(GPU) programming techniques. The programmability of modern GPUs allows developers to not only distinguish themselves from one another but also;

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Metal Programming Guide

Master Metal: The Next-Generation Graphics and GPU Programming Platform for Apple Developers Metal enables Apple developers to;

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