GPGPU
General-Purpose Computation Using Graphics Hardware

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.

Contribute
Have some GPGPU News to Contribute? Submit it!

Contact Us


Subscribe to a syndicated RSS feed of GPGPU.
Subscribe to a syndicated RSS feed of GPGPU.

Powered by Blosxom.

Hosted by ibiblio.org

SIGGRAPH2002 Course: Interactive Geometric Computations with Graphics Hardware

This SIGGRAPH 2002 course, organized by Dinesh Manocha of UNC Chapel Hill, covered approaches to using graphics hardware for various geometric problems, including voronoi computation, proximity queries, motion planning, and more.

Posted: 19 Nov 2002 [GPGPU /Miscellaneous/Courses] #

Shader Metaprogramming

This paper describes the use of standard C++ to define a high-level shading language directly in the API. The language is nearly indistinguishable from a special-purpose shading language, yet it simplifies implementation, and permits more direct interaction with the specification of textures, parameters, and attributes. ( Shader Metaprogramming. Michael D. McCool, Zheng Qin, and Tiberiu S. Popa. SIGGRAPH/Eurographics Graphics Hardware Workshop, September 2-3, 2002, Saarbruecken, Germany, pp. 57-68.)

Posted: 19 Nov 2002 [GPGPU /High-Level Languages] #

UNC Chapel Hill GAMMA group.

The GAMMA research group at UNC Chapel Hill (led by Profs. Dinesh Manocha and Ming Lin) uses GPUs for Voronoi computations, collision detection, penetration computation and collision response, motion planning, and more.

Posted: 19 Nov 2002 [GPGPU /Miscellaneous/Research Groups] #

CalTech CS101.3: Hacking The GPU

Peter Schröder taught a course in the fall of 2002 at CalTech called Hacking The GPU. The subject matter of the course revolved around general purpose computation. Assignments included stable fluid simulation and mesh smoothing. The course notes page has some useful links.

Posted: 19 Nov 2002 [GPGPU /Miscellaneous/Courses] #


Categories