Introduction

GPGPU stands for General-Purpose computation on GPUs. With the increasing programmability of commodity graphics processing units (GPUs), these chips are capable of performing more than the specific graphics computations for which they were designed. They are now capable coprocessors, and their high speed makes them useful for a variety of applications. The goal of this page is to catalog the current and historical use of GPUs for general-purpose computation.

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SUPERCOMPUTING 2007 Tutorial: High Performance Computing with CUDA

Welcome to the course notes for the full-day SUPERCOMPUTING 2007 CUDA Tutorial!

The tutorial was held at SUPERCOMPUTING 2007 on Sunday, November 11, 2007.

Massimiliano Fatica, NVIDIA Corporation
David Luebke, NVIDIA Corporation

Ian Buck, NVIDIA Corporation
Bernard Deschizeaux, CGGVeritas
Mark Harris, NVIDIA Corporation
John Owens, University of California, Davis
Jim Phillips, University of Illinois, Urbana-Champaign
John Stone, University of Illinois, Urbana-Champaign

• Welcome! (PDF)
• Introduction (PDF)
• Programming CUDA (PDF)
• CUDA Libraries (PDF)
• Data-Parallel Algorithms and Data Structures (PDF)
• Optimizing CUDA (PDF)
• Case Study: Molecular Visualization and Analysis (PDF)
• Case Study: Molecular Dynamics (PDF)
• Case Study: Wave Propagation Through Earth (PDF)

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Course Abstract
Course Organizers
Course Speakers
Course Outline
Full Course Notes

Links

Other GPGPU Courses


• SIGGRAPH 2005
• SIGGRAPH 2004
• IEEE VIS 2005
• IEEE VIS 2004

High-Level Shading Languages


• Cg: C for Graphics
  
• HLSL: The D3D Shading Language
  
• The OpenGL Shading Language
  

GPGPU Languages


• Sh - University of Waterloo
  
• Brook - Stanford University
  

Shader Conversion


• Babelshader
  

Debugging Tools


• imdebug
  
• Shadesmith
  

Utility Code


• Framebuffer Object Class
  
• RenderTexture