Professional CUDA C Programming

Professional CUDA C Programming
John Cheng (Author), Max Grossman (Author), Ty McKercher (Author)

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CUDA Fortran for Scientists and Engineers: Best Practices for Efficient CUDA Fortran Programming

CUDA Fortran for Scientists and Engineers: Best Practices for Efficient CUDA Fortran Programming
Gregory Ruetsch (Author), Massimiliano Fatica (Author)

New!: $69.95 $58.75 (as of 10/16/2013 20:50 PST)
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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 the target GPU architecture, identify computationally intensive parts of the code, and modify the code to manage the data and parallelism and optimize performance. All of this is done in Fortran, without having to rewrite in another language. Each concept is illustrated with actual examples so you can immediately evaluate the performance of your code in comparison.

• Leverage the power of GPU computing with PGI's CUDA Fortran compiler
• Gain insights from members of the CUDA Fortran language development team
• Includes multi-GPU programming in CUDA Fortran, covering both peer-to-peer and message passing interface (MPI) approaches
• Includes full source code for all the examples and several case studies
• Download source code and slides from the book's companion website

• Rank: #23002 in Books
• Published on: 2013-10-01
• Original language: English
• Number of items: 1
• Dimensions: 1.55 pounds
• Binding: Paperback
• 338 pages

CUDA Handbook: A Comprehensive Guide to GPU Programming, The

CUDA Handbook: A Comprehensive Guide to GPU Programming, The
Nicholas Wilt (Author)

New!: $59.99 $44.66 (as of 06/08/2013 19:35 PST)

Hardware

 

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 will appreciate the expert coverage of topics such as the driver API and context migration, as well as the guidance on how best to structure CPU/GPU data interchange and synchronization.

 

The accompanying open source code–more than 25,000 lines of it, freely available at www.cudahandbook.com–is specifically intended to be reused and repurposed by developers.

 

Designed to be both a comprehensive reference and a practical cookbook, the text is divided into the following three parts:

Part I, Overview, gives high-level descriptions of the hardware and software that make CUDA possible.

Part II, Details, provides thorough descriptions of every aspect of CUDA, including

•  Memory
• Streams and events
•  Models of execution, including the dynamic parallelism feature, new with CUDA 5.0 and SM 3.5
• The streaming multiprocessors, including descriptions of all features through SM 3.5
• Programming multiple GPUs
• Texturing

The source code accompanying Part II is presented as reusable microbenchmarks and microdemos, designed to expose specific hardware characteristics or highlight specific use cases.

Part III, Select Applications, details specific families of CUDA applications and key parallel algorithms, including

•  Streaming workloads
  
• Reduction
• Parallel prefix sum (Scan)
  
• N-body
• Image Processing

These algorithms cover the full range of potential CUDA applications.

 

• Rank: #51623 in Books
• Published on: 2013-06-24
• Original language: English
• Number of items: 1
• Dimensions: .0" h x .0" w x .0" l, .0 pounds
• Binding: Paperback
• 528 pages