@CUDAHandbook: BREAKING: The CUDA Handbook text is now available on the website, https://cudahandbook.com! Svbstack article in the fir…

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The CUDA Handbook, a comprehensive guide to GPU programming with CUDA, is now available online for free reading with ads or ad-free via membership. The book covers architecture, APIs, and algorithms, with open-source code.

BREAKING: The CUDA Handbook text is now available on the website, https://t.co/D4VweCJkHo! Svbstack article in the first reply.
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BREAKING: The CUDA Handbook text is now available on the website, https://t.co/D4VweCJkHo!

Svbstack article in the first reply.


The CUDA Handbook

Source: https://www.cudahandbook.com/ Prefer to read without ads?Become a member— from $10/month — and support the work.

The CUDA Handbook v2.0 — A Comprehensive Guide to GPU Programming

Welcome to the official website forThe CUDA Handbook.

The CUDA Handbook, published byPearson InformIT, is a comprehensive guide to programming GPUs with CUDA. It covers every detail about CUDA, from system architecture, address spaces, machine instructions and warp synchrony to the CUDA runtime and driver API to key algorithms such as reduction, parallel prefix sum (scan), and N-body.

The CUDA Handbookincludes the following:

  • Detailed descriptions of every CUDA abstraction and how it maps onto the hardware.
  • Microbenchmarks to measure performance of everything from peak global memory bandwidth.
  • Microdemos to illustrate in-depth the workings of features such as texture-mapping and the new warp shuffle instruction (new in SM 3.0).
  • Detailed descriptions of key parallel algorithms, such as reduction, Scan, and N-body, with source code implementations.

Thesource codeaccompanyingThe CUDA Handbookis open source, available ongithub.

Reading is free, supported by ads. Prefer none?Become a member— from $10/month — and read the entire site ad-free.

Check outThe CUDA Handbookblog!

Follow The CUDA Handbook on Twitter (@CUDAHandbook)!

Corrections are applied directly to the online text. If you spot an error, pleasesend email.

Nicholas Wilt was on the inception team for CUDA, starting in 2005 and continuing work on it until he left NVIDIA in late 2010. As the primary architect of CUDA’s driver API, he is responsible for most of the low-level abstractions that CUDA programs deal with: from contexts and modules to streams and events, portable and mapped pinned memory, CUDA arrays and texture and surface references.

Before joining NVIDIA in 2002, Mr. Wilt worked on multimedia at Microsoft in various roles. Among other things, he was the development lead for Direct3D 5.0 and Direct3D 6.0, worked on the Video Mixing Renderer (VMR) that shipped in Windows XP, and built a prototype page-flipping desktop that eventually became the Windows Desktop Manager.

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