OpenCL Programming by Example

Name: OpenCL Programming by Example
Rating: 4.25 (4 reviews)

Ravishekhar Banger · Koushik Bhattacharyya

ଡିସେମ୍ବର 2013 · Packt Publishing Ltd

4.2

4ଟି ସମୀକ୍ଷା

ଇବୁକ୍

304

ପୃଷ୍ଠାଗୁଡ଼ିକ

ରେଟିଂ ଓ ସମୀକ୍ଷାଗୁଡ଼ିକୁ ଯାଞ୍ଚ କରାଯାଇନାହିଁ ଅଧିକ ଜାଣନ୍ତୁ

ଏହି ଇବୁକ୍ ବିଷୟରେ

This book follows an example-driven, simplified, and practical approach to using OpenCL for general purpose GPU programming. If you are a beginner in parallel programming and would like to quickly accelerate your algorithms using OpenCL, this book is perfect for you! You will find the diverse topics and case studies in this book interesting and informative. You will only require a good knowledge of C programming for this book, and an understanding of parallel implementations will be useful, but not necessary.

ମୂଲ୍ୟାଙ୍କନ ଓ ସମୀକ୍ଷା

4.2

4ଟି ସମୀକ୍ଷା

ଲେଖକଙ୍କ ବିଷୟରେ

Ravishekhar Banger calls himself a Parallel Programming Dogsbody. Currently he is a specialist in OpenCL programming and works for library optimization using OpenCL. After graduation from SDMCET, Dharwad, in Electrical Engineering, he completed his Masters in Computer Technology from Indian Institute of Technology, Delhi. With more than eight years of industry experience, his present interest lies in General Purpose GPU programming models, parallel programming, and performance optimization for the GPU. Having worked for Samsung and Motorola, he is now a Member of Technical Staff at Advanced Micro Devices, Inc. One of his dreams is to cover most of the Himalayas by foot in various expeditions. You can reach him at [email protected].; Koushik Bhattacharyya is working with Advanced Micro Devices, Inc. as Member Technical Staff and also worked as a software developer in NVIDIA®. He did his M.Tech in Computer Science (Gold Medalist) from Indian Statistical Institute, Kolkata, and M.Sc in pure mathematics from Burdwan University. With more than ten years of experience in software development using a number of languages and platforms, Koushik's present area of interest includes parallel programming and machine learning.

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