GPGPU Course at UNC Chapel Hill

October 29th, 2004

A course on general-purpose computation on graphics processors is being taught this semester by Dinesh Manocha at The University of North Carolina at Chapel Hill. This seminar course covers algorithmic and system issues as well as a number of applications. It will review the current state of the art and investigate many open issues. (GPGP)

Course on GPGPU at University of Aarhus, Denmark

October 29th, 2004

A short course on GPGPU is given at the Department of Computer Science, University of Århus, Denmark by Jesper Mosegaard and Thomas Sangild Sørensen. (GPGPU_E04)

Scout: A Hardware-Accelerated System for Quantitatively Driven Visualization and Analysis

October 20th, 2004

This IEEE Visualization 2004 paper by McCormick et al. describes the Scout System and Language that allow the GPU to be programmed for scientific visualization. Scout uses a data parallel language that allows the user to program visual mappings from data values to the final rendered result. These techniques can be used to replace standard user interface components, such as the transfer function editor commonly used in volume rendering. (“Scout: A Hardware-Accelerated System for Quantitatively Driven Visualization and Analysis”, Patrick S. McCormick, Jeff Inman, James P. Ahrens, Chuck Hansen and Greg Roth, In Proceedings IEEE Visualization 2004, pages 171-178, October 2004.)

GPGPU Course Notes from IEEE Visualization 2004

October 20th, 2004

The complete course notes have been posted for the full-day GPGPU course held at IEEE Visualization 2004. The course, titled “GPGPU: General-Purpose Computing on Graphics Processors“, was held on Monday, October 11th, 2004 in Austin, Texas. The course begins with the architectural, economic, and programmatic motivations behind GPGPU. It then introduces a “hello world” GPGPU example and describes the stream programming model in detail (including Brook). Mathematical and algorithmic primitives are then presented, followed by descriptions of many of the low-level technical details required for effective real-world GPGPU programming. The course concludes with several case studies and a disscusison of the future architectual, application, and research possibilities for GPGPU. The course organizer was Aaron Lefohn, and the presenters were Ian Buck, Aaron Lefohn, John Owens, and Robert Strzodka. ( “GPGPU: General-Purpose Computing on Graphics Processors,” IEEE Visualization 2004)

GPUs: Engines for Future High-Performance Computing

October 6th, 2004

This talk by John Owens of UC Davis discusses trends in GPU architecture and their current and potential uses for high-performance computing. The invited talk was given at the Eighth Annual Workshop on High-Performance Embedded Computing (HPEC 2004). (GPUs: Engines for Future High-Performance Computing)

Room Acoustics Computation on Graphics Hardware

October 6th, 2004

In this masters thesis by Marcin Jdrzejewski, ray tracing is implemented on the GPU to accelerate computation of sound paths between sound sources and receivers. Each ray averages 16-20 wall reflections, and those rays that intersect a sphere approximating the receiver are included in an echogram that is used in the auralization process. Typically 4096 rays are used, but the application can run in real time with up to 64K rays. A demo application, article and some movies can be downloaded from the following link. (Computation of room acoustics on a GPU.)

BionicFX uses GPU as Powerful Audio Effect Processor

September 5th, 2004

From a press release at www.BionicFX.com: “BionicFX announces a revolutionary technology for music production that turns NVIDIA video cards into audio effects processors. Audio Video Exchange (AVEX) converts digital audio into graphics data, and then performs effect calculations using the 3D architecture of the GPU. The latest video cards from NVIDIA are capable of more than 40 gigaflops of processing power compared to less than 6 gigaflops on Intel and AMD CPUs. AVEX represents a major technological achievement that allows music hobbyists and professional artists to run studio quality audio effects at high sample rates on their desktop computer. (Press Release: “Revolutionary Programming and Innovation uses GPU as Powerful Audio Effect Processor”)

Typhoonlabs publish a GPGPU-based Fractal Explorer

September 5th, 2004

TyphoonLabs have published the Fractal Explorer v1.0, an application to explore the most common fractals (such as Julia sets, Mandelbrot sets, and some alternate Julia planes) using the GPU to compute them. It can easily be extended with new fractals written in the OpenGL Shading Language. (TyphoonLabs Fractal Explorer v1.0)

FX Composer 1.5 Released

August 27th, 2004

NVIDIA recently released an updated version of FX Composer with support for Shader Model 3.0 and tons of new sample shaders. The latest version also includes many developer-requested UI improvements, support for NV4x GPU performance analysis, and a beta SDK that allows developer to write their own automation scripts, importers/exporters, etc. The best way to view all the sample shaders is by downloading the latest NVIDIA SDK and looking at the “Effects” tab where you will find descriptions and screenshots of 250+ effects. (FX Composer Homepage)

Cg 1.3 Beta 2 Released

August 19th, 2004

Cg Release 1.3 Beta 2 has been released with support for the latest GeForce 6 Series (NV4X) GPUs. This version of Cg offers the following features and improvements:

  • New vp40 profile, which enables texture sampling from within vertex programs
  • New fp40 profile, which provides a robust branching model in fragment programs, and support for output to multiple draw buffers (“MRTs”)
  • Support for writing more than one color output (i.e., MRTs) in the arbfp1 and ps_2* profiles
  • New semantics to access OpenGL fixed-function state vectors from within ARB_vertex_program and ARB_fragment_program
  • New “-fastprecision” option for arbfp*, fp30, and fp40 profiles, to use reduced precision storage (fp16) when appropriate
  • Support for 16 profiles

(http://developer.nvidia.com/object/cg_toolkit.html)

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