This paper reviews the latest developments of displacement mapping algorithms implemented on the vertex, geometry, and fragment shaders of graphics cards. Displacement mapping algorithms are classified as per-vertex and per-pixel methods. Per-pixel approaches are further categorized as safe algorithms that aim at correct solutions in all cases, to unsafe techniques that may fail in extreme cases but are usually much faster than safe algorithms, and to combined methods that exploit the robustness of safe and the speed of unsafe techniques. The paper discusses the possible roles of vertex, geometry, and fragment shaders to implement these algorithms. Then the particular GPU based bump, parallax, relief, sphere, horizon mapping, cone stepping, local ray tracing, pyramidal and view-dependent displacement mapping methods, as well as their numerous variations are reviewed providing also implementation details of the shader programs. The paper presents these methods using uniform notation and also points out when different authors referred to similar concepts differently. In addition to basic displacement mapping, self-shadowing and silhouette processing are also reviewed. Based on the authors' experiences gained having re-implemented these methods, their performance and quality are compared, and the advantages and disadvantages are fairly presented. (Displacement Mapping on the GPU - State of the Art László Szirmay-Kalos and Tamás Umenhoffer. Computer Graphics Forum. 2008.)

Slides from the 2007 AstroGPU conference, held at the Institute for Advanced Study in Princeton last November, have been posted to the AstroGPU Website.

In conjunction with The 2008 International Conference on Computational Science and Its Applications (ICCSA 2008, UCHPC '08 is a technical session on UnConventional High Performance Computing. This session focuses on uses of hardware for HPC that was not originally intended for HPC. UCHPC invites papers on all aspects of unconventional HPC and its related areas describing either proven and tested solutions or novel ideas and concepts. Topics for submissions include but are not limited to the following areas: cluster solutions; performance issues and scalability; innovative use of hardware and software; and HPC on GPUs, Cell BE, FPGAs and other hardware. Please see the Call for Papers for more information.

ARCS 2008, the 21st Conference on Architecture of Computing Systems, is proud to announce a full day GPGPU tutorial, covering concepts, building blocks and case studies with a special focus on NVIDIA CUDA GPU Computing technology. ARCS is held in Dresden, Germany, on February 25-28, 2008. For more details, please visit The ARCS 2008 Website.

This Ph.D. thesis by Jansen describes a GPGPU development system that is embedded in the C++ programming language using ad-hoc polymorphism (i.e. operator overloading). While this technique is already known from the Sh library and the RapidMind Development Platform, GPU++ uses a more generic class interface and requires no knowledge of GPU programming at all. Furthermore, there is no separation between the different computation units of the CPU and GPU - the appropriate computation frequency is automatically chosen by the GPU++ system using several optimization algorithms. ("GPU++: An Embedded GPU Development System for General-Purpose Computations". Thomas Jansen. Ph.D. Thesis, University of Munich, Germany.