These works from the Database Systems Lab at UC Santa Barbara describe how a graphics processor can be effectively used to accelerate the performance of spatial database (GIS databases) operations. Spatial database operations, especially which involve polygon datasets, have been known to be computationally expensive. Sun et al. describe a novel hardware / software co-processing technique which uses basic features of a GPU to reduce the spatial query processing cost. Experimental evaluation shows that their hardware-based approach can significantly outperform leading software-based techniques. (Hardware Acceleration for Spatial Selections and Joins Chengyu Sun, Divyakant Agrawal, Amr El Abbadi. Proceedings of SIGMOD 2003.) However, this evaluation is done in a stand-alone setting where there are no indices, preprocessing or other optimizations available in a database. Bandi et al. extend Sun et al.’s work and integrate the hardware-based technique into a popular commercial database. Rigorous experimentation over real-life data sets shows that the hardware-based approach is very effective and can be complimentary to the optimizations available in a commercial database setting. (Hardware Acceleration in Commercial Databases: A Case Study of Spatial Operations Nagender Bandi, Chengyu Sun, Divyakant Agrawal, Amr El Abbadi to appear in VLDB 2004.)

Modern GPUs perform floating point math and read data from off-chip memory at rates roughly five times that of a fast Pentium 4 CPU. However, the performance of algorithms for computing dense matrix-matrix products on GPUs has lagged behind that of good CPU implementations. In this paper, we show why this result is not an artifact of poorly designed algorithms, and explain how present-day graphics architectures are highly inefficient for computations such as matrix-matrix multiplication that involve significant data reuse. (Understanding the Efficiency of GPU Algorithms for Matrix-Matrix Multiplication. Kayvon Fatahalian, Jeremy Sugerman, and Pat Hanrahan.)

Inspired by the summer Olympics taking place this year, ShaderTech.com is hosting a shader contest this summer with three categories: Materials & Environmental Effects, Image Processing & NPR Effects, and Thinking Outside the Box (this category includes GPGPU applications!).

With over $20,000 worth of prizes available, the Shader Triathlon is a great way to show off your shader skills. Participants can win gold, silver, and bronze prizes for each category, as well as the grand prize: 3ds max, RT/Shader, and a GDC 2005 Gigapass! In addition, all entrants will be entered into a random drawing for the following prizes: 3ds max, RT/Shader, and GPU Gems books.

The Shader Triathlon is sponsored by NVIDIA, discreet, RTzen, and the Game Developers Conference 2005. (ShaderTech.com Shader Triathlon)

ATI’s Ashli version 1.4.0 has been released and is available for download from: Ashli Home. Ashli is a toolkit intended to assist developers exploring programmable shading on GPUs. It supports a reasonable subset of OpenGL (GLSL), Microsoft’s DirectX (HLSL) and RenderMan shading languages. Ashli’s significant contribution is in hardware resource virtualization, segmenting a complex shader program into GPU realizable streams. The posted Ashli viewer application demonstrates the use of shader partitions in a multi-pass rendering context. Ashli outputs both metadata and code, orthogonal to any of the languages supported. Targets include OpenGL ARB_vertex_program and ARB_fragment_program, and DirectX 9.0 Vertex Shader and Pixel Shader versions 2.0 and 2.X API’s. Optionally, Ashli emits a unified Microsoft FX file format, embedding progressive techniques of state and code sections. (Ashli 1.4.0)

3Dlabs Inc. has introduced its PCI Express-based Wildcat Realizm 800. A professional PCI Express-based graphics accelerator, the Wildcat Realizm 800 features a Wildcat Realizm Vertex/Scalability Unit (VSU) and dual Wildcat Realizm Visual Processing Units (VPU). The Wildcat Realizm 800 and the new AGP 8x-based Wildcat Realizm 100 and 200 deliver programmability via the OpenGL Shading Language and Microsoft DirectX 9.0 HLSL shader programs. The Wildcat Realizm 800 is slated for availability in the third calendar quarter of this year at a suggested retail price of $2799. (3Dlabs Wildcat Realizm Family)

Established by NVIDIA Corporation, NVIDIA U is a conference developed to promote the advancement of graphics technology through industry and academic collaboration. NVIDIA U 2004 will be a highly focused, one day event. Conveniently held in Los Angeles one day before GP2 and two days prior to Siggraph 2004, it is sure to sizzle with presentations targeting current and future NVIDIA technology. NVIDIA U is an NDA only conference that provides the ideal forum for leaders in the graphics world to collaborate and share ideas and research in graphics technology. (NVIDIA U Information Page)

This paper by Larsen et al. at Technical University of Denmark introduces a fast GPU accelerated technique for simulating photon mapping. Each of the steps in the photon mapping algorithm are executed either on the CPU or the GPU depending on which of the processors are most appropriate for the task. The indirect illumination is calculated using a new GPU accelerated final gathering method. Caustic photons are traced on the CPU and then drawn using points in the framebuffer, and finally filtered using the GPU. Both diffuse and non-diffuse surfaces are handled by calculating the direct illumination on the GPU and the photon tracing on the CPU. (Simulating Photon Mapping for Real-time Applications. Bent D. Larsen, Niels J. Christensen, To appear at Eurographics Symposium on Rendering, 2004.)

This paper by Govindaraju et al. describes new algorithms for performing fast computation of several common database operations on commodity graphics processors. Specifically, the paper considers operations such as conjunctive selections, aggregations, and semi-linear queries, which are essential computational components of typical database, data warehousing, and data mining applications. The proposed algorithms take into account some of the limitations of the programming model of current GPUs and perform no data rearrangements. These algorithms have been implemented on a programmable GPU (e.g. NVIDIA’s GeForce FX 5900) and applied to databases consisting of up to a million records. The paper compares their performance with an optimized CPU-based implementation. The experiments indicate that the graphics processor available on commodity computer systems is an effective coprocessor for performing database operations. (Fast Database Operations using Graphics Processors. Naga K. Govindaraju, Brandon Lloyd, Wei Wang, Ming C. Lin, Dinesh Manocha to appear at SIGMOD 2004.)

In cooperation with the creators of BrookGPU, GPGPU.org has added discussion forums for beginner and general/advanced Brook topics. Brook users of all levels can use these forums to discuss questions, experiences, and other information with other Brook users and with the developers of BrookGPU.

This paper explores the plausibility of using the GPU for numerical simulations on structured grids (lattices). The paper (1) reviews previous work on using GPUs for non-graphics applications, (2) implements probability-based simulations on the GPU, namely the Ising and percolation models, (3) implements vector operation benchmarks for the GPU, and (4) compares CPU and GPU performance. The original contribution of this work is implementing Monte Carlo type simulations on the GPU. Such simulations have a wide area of applications. They are computationally intensive and, as shown in the paper, lend themselves naturally to implementation on GPUs, providing a computational speedup. A general conclusion from the results obtained is that moving computations from the CPU to the GPU is feasible, yielding good time and price performance for certain lattice computations. Preliminary results also show that it is feasible to use GPUs in parallel. (S.Tomov, M.McGuigan, R.Bennett, G.Smith, J.Spiletic. Benchmarking and Implementation of Probability-Based Simulations on Programmable Graphics Cards, to appear in Computers & Graphics.)