GPGPU |
General-Purpose Computation Using Graphics Hardware
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IntroductionGPGPU 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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CUDPP 1.0a Adds Segmented Scan and Sparse Matrix-Vector Multiplication Version 1.0 alpha of CUDPP, the CUDA Data-Parallel Algorithms Library, has been released. This version adds the segmented scan algorithm and sparse matrix-vector multiplication to CUDPP's repertoire. Other new features include an improved "plan"-based configuration interface, an improved scan algorithm for higher performance, support for more inclusive scans and more scan operators, an improved stream compaction interface. In addition, CUDPP 1.0a adds support for CUDA 2.0 and the Windows Vista and Mac OS X (10.5.2 and higher) operating systems. CUDPP works with NVIDIA CUDA versions 1.1 and higher.
Posted: 20 Apr 2008 [GPGPU /Miscellaneous/Developer Resources] # Shader Maker: a simple, truly cross-platform GLSL editor Shader Maker is a simple, cross-platform GLSL editor. It works on Windows, Linux, and Mac OS X. Shader Maker provides the basics of a shader editor, such that students can get started with writing their own shaders as quickly as possible. This includes: syntax highlighting in the GLSL editors; vertex, fragment, and geometry shader editors; interactive editing of uniform variables; light source parameters; pre-defined simple shapes (e.g., torus); a simple OBJ loader; and more.(
http://cg.in.tu-clausthal.de/publications.shtml#shader_maker
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Posted: 20 Apr 2008 [GPGPU /Tools] # GRIP - A Rugged GPU Accelerated Image Processing System Vision4ce launched a new line of General-purpose Rugged Image Processing (GRIP) products at the recent SPIE Defense and Security Symposium in Orlando from 18th-20th March 2008. The GRIP-Beta showed cutting edge GPGPU-based image processing demonstrations, analog and Gigabit Ethernet video streams and the robust functionality in the Gripworkx image processing framework. The Vision4ce team with GRIP now addresses numerous rugged embedded computing challenges with a cost effective, readily available rugged solution that might normally be served by more expensive and lengthy FPGA approaches. See www.vision4ce.com for more information.
Posted: 20 Apr 2008 [GPGPU /GPUs] # SHARCNET Symposium on GPU and CELL Computing University of Waterloo This one-day symposium will explore the use of GPUs, CELL processors, FPGAs and multi-core CPUs for large-scale scientific computing. The symposium program includes invited talks on the LANL Roadrunner CELL supercomputer, the RapidMind platform for multicore CPUs and many-core accelerators, and NVIDIA CUDA. For more information, see http://www.sharcnet.ca/events/ssgc2008/ Posted: 20 Apr 2008 [GPGPU /Conferences] # |
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GPGPU PeopleFor a list of people doing GPGPU work, See the GPGPU wiki |
