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Best CUDA Books You Should Read

In this post, we have prepared a curated top list of reading recommendations for beginners and experienced. This hand-picked list of the best Cuda books and tutorials can help fill your brain this August and ensure you’re getting smarter. We have also mentioned the brief introduction of each book based on the relevant Amazon or Reddit descriptions.

1. Professional CUDA C Programming (2014)

Best CUDA Books You Should Read

Break into the powerful world of parallel GPU programming with this down-to-earth, practical guide. Designed for professionals across multiple industrial sectors, Professional CUDA C Programming  presents CUDA — a parallel computing platform and programming model designed to ease the development of GPU programming — fundamentals in an easy-to-follow format, and teaches readers how to think in parallel and implement parallel algorithms on GPUs. Each chapter covers a specific topic, and includes…

Author(s): John Cheng, Max Grossman

2. CUDA Programming (2012)

Best CUDA Books You Should Read

If you need to learn CUDA but don’t have experience with parallel computing, CUDA Programming: A Developer’s Introduction offers a 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 hardware, then delving into CUDA installation. Chapters on core concepts including threads, blocks, grids, and memory focus on both parallel and CUDA-specific issues. Later, the book demonstrates CUDA…

Author(s):  Shane Cook

3. CUDA by Example: An Introduction to General-Purpose GPU Programming (2010)

Best CUDA Books You Should Read

In conjunction with a comprehensive software platform, the CUDA Architecture enables programmers to draw on the immense power of graphics processing units (GPUs) when building high-performance applications. GPUs, of course, have long been available for demanding graphics and game applications. CUDA now brings this valuable resource to programmers working on applications in other domains, including science, engineering, and finance.

Author(s): Jason Sanders, Edward Kandrot

4. Programming Massively Parallel Processors, Third Edition: A Hands-on Approach (2016)

Best CUDA Books You Should Read

Programming Massively Parallel Processors: A Hands-on Approach, Third Edition shows both student and professional alike the basic concepts of parallel programming and GPU architecture, exploring, in detail, various techniques for constructing parallel programs. Case studies demonstrate the development process, detailing computational thinking and ending with effective and efficient parallel programs. Topics of performance, floating-point format, parallel patterns…

Author(s): David B. Kirk, Wen-mei W. Hwu

5. CUDA Handbook: A Comprehensive Guide to GPU Programming, The (2013)

Best CUDA Books You Should Read

 The CUDA Handbook begins where CUDA by Example (Addison-Wesley, 2011) leaves off, discussing CUDA hardware and software in greater detail and covering both CUDA 5.0 and Kepler. Every CUDA developer, from the casual to the most sophisticated, will find something here of interest and immediate usefulness. Newer CUDA developers will see how the hardware processes commands and how the driver checks progress; more experienced CUDA developers…

Author(s): Nicholas Wilt

6. CUDA for Engineers: An Introduction to High-Performance Parallel Computing (2015)

Best CUDA Books You Should Read

CUDA for Engineers allows researchers in engineering and mathematics to perform calculations hundreds of times faster than was previously possible on microcomputers. This permits new kinds of calculations to be performed and
reveals this book to be a game changer.

 

Author(s): Duane Storti, Mete Yurtoglu

7. The CUDA Handbook (2018)

Best CUDA Books You Should Read

The CUDA Handbook is the only comprehensive reference to CUDA that exists. Every CUDA developer, from the casual to the most sophisticated, will find something here of interest and immediate usefulness. Newer CUDA developers will see how the hardware processes commands and how…

Author(s): Nicholas Wilt

8. CUDA Fortran for Scientists (2013)

Best CUDA Books You Should Read

CUDA Fortran for Scientists and Engineers shows how high-performance application developers can leverage the power of GPUs using Fortran, the familiar language of scientific computing and supercomputer performance benchmarking. The authors presume no prior parallel computing experience, and cover the basics along with best practices for efficient GPU computing using CUDA Fortran. To help you add CUDA Fortran to existing Fortran codes, the book explains how to understand…

Author(s): Gregory Ruetsch, Massimiliano Fatica

9. Cuda Programming (2014)

Best CUDA Books You Should Read

This book is a practical guide to using CUDA in real applications, by real practitioners. At the same time, however, we cover the necessary theory and background so everyone, no matter what their background, can follow along and learn how to program in CUDA, making this book ideal for both professionals and those studying GPUs or parallel programming.

 

Author(s): Shane Cook

10. GPU Programming in MATLAB (2016)

Best CUDA Books You Should Read

GPU programming in MATLAB is intended for scientists, engineers, or students who develop or maintain applications in MATLAB and would like to accelerate their codes using GPU programming without losing the many benefits of MATLAB. The book starts with coverage of the Parallel Computing Toolbox and other MATLAB toolboxes for GPU computing, which allow applications to be ported straightforwardly onto GPUs without extensive knowledge of GPU…

Author(s): Nikolaos Ploskas, Nikolaos Samaras

11. Parallel Programming with OpenACC (2016)

Best CUDA Books You Should Read

Parallel Programming with OpenACC is a modern, practical guide to implementing dependable computing systems. The book explains how anyone can use OpenACC to quickly ramp-up application performance using high-level code directives called pragmas. The OpenACC directive-based programming model is designed to provide a simple, yet powerful, approach to accelerators without significant programming effort. Author Rob Farber, working with a team of expert contributors…

Author(s): Rob Farber

12. GPU parallel computing for machine (2017)

Best CUDA Books You Should Read

This book illustrates how to build a GPU parallel computer. If you don’t want to waste your time for building, you can buy a built-in-GPU desktop/laptop machine. All you need to do is to install GPU-enabled software for parallel computing. Imagine that we are in the midst of a parallel computing era. The GPU parallel computer is suitable for machine learning, deep (neural network) learning. For example, GeForce GTX1080 Ti is a GPU board with 3584 CUDA cores. Using the GeForce GTX1080 Ti, the performance is roughly 20 times faster than that of an INTEL i7 quad-core CPU. We have benchmarked the MNIST…

Author(s): Yoshiyasu Takefuji

You might also be interested in: Socket.io, Tensorflow, Ruby on Rails, Appium, Extjs, Moodle, Erlang, Nodejs, Agile, PyQT Books.

We highly recommend you to buy all paper or e-books in a legal way, for example, on Amazon. But sometimes it might be a need to dig deeper beyond the shiny book cover. Before making a purchase, you can visit resources like Genesis and download some Cuda books mentioned below at your own risk. Once again, we do not host any illegal or copyrighted files, but simply give our visitors a choice and hope they will make a wise decision.

Die kompakte Stadt der Zukunft: Auf dem Weg zu einer inklusiven und nachhaltigen Stadtgesellschaft

Author(s): Nina Berding, Wolf-D. Bukow, Karin Cudak (eds.)
Publisher: VS Verlag für Sozialwissenschaften, Year: 2018, Size: 5 Mb, Ext: pdf
ID: 2156200

GPU Parallel Program Development Using CUDA

Author(s): Tolga Soyata
Publisher: Chapman and Hall/CRC, Year: 2018, Size: 5 Mb, Ext: pdf
ID: 2191209

GPU Parallel Program Development Using CUDA

Author(s): Tolga Soyata
Publisher: Chapman and Hall/CRC, Year: 2018, Size: 4 Mb, Ext: pdf
ID: 2205699

Leggere Francesco

Author(s): Emilce Cuda
Publisher: Bollati Boringhieri, Year: 2018, Size: 2 Mb, Ext: epub
ID: 2207196

Deep Belief Nets in C++ and CUDA C volume 1 Restricted Boltzmann Machines and Supervised Feedforward Networks

Author(s): Timothy Masters
Publisher: Apress, Year: 2018, Size: 3 Mb, Ext: pdf
ID: 2213295

Deep Belief Nets in C++ and CUDA C: Volume 1: Restricted Boltzmann Machines and Supervised Feedforward Networks

Author(s): Timothy Masters
Publisher: Apress, Year: 2018, Size: 2 Mb, Ext: epub
ID: 2213505

Deep Belief Nets in C++ and CUDA C volume 2 Autoencoding in the Complex Domain

Author(s): Timothy Masters
Publisher: Apress, Year: 2018, Size: 5 Mb, Ext: pdf
ID: 2224317

Bildung für Newcomer: Wie Schule und Quartier mit Einwanderung aus Südosteuropa umgehen

Author(s): Karin Cudak
Publisher: VS Verlag für Sozialwissenschaften, Year: 2017, Size: 9 Mb, Ext: pdf
ID: 1677147

Parallel computing for data science : with examples in R, C++ and CUDA

Author(s): Matloff, Norman S.
Publisher: CRC Press, Year: 2016, Size: 2 Mb, Ext: pdf
ID: 1369243

Inclusive City: Überlegungen zum gegenwärtigen Verhältnis von Mobilität und Diversität in der Stadtgesellschaft

Author(s): Melanie Behrens, Wolf-Dietrich Bukow, Karin Cudak, Christoph Strünck (eds.)
Publisher: VS Verlag für Sozialwissenschaften, Year: 2016, Size: 6 Mb, Ext: pdf
ID: 1468722

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