high performance computing on graphics processing units: hgpu.org

A software based GPU design, where most of the 3D pipeline is executed in software on shaders, with minimal support from custom hardware blocks, provides three benefits, it: (1) simplifies the GPU design, (2) turns 3D graphics into a general purpose application, and (3) opens the door for applying compiler optimization to the whole 3D […]

This paper presents and briefly describes the state of the art of accelerating image processing with graphics hardware (GPU) and discusses some of its caveats. Then it describes GpuCV, an open source multiplatform library for GPU-accelerated image processing and Computer Vision operators and applications. It is meant for computer vision scientist not familiar with GPU […]

We investigated the possible way for treatment of electrostatic interactions by solving numerically Poisson’s equation using Conjugate Gradient method and Stabilized BiConjugate Gradient method. The aim of the research was to test the execution time of prototype programs running on BLueGene/P and CPU/GPU system. The results show that the tested methods are applicable for electrostatics […]

Iris recognition is quite a computation intensive task with huge amounts of pixel processing. After the image acquisition of the eye, Iris recognition is basically divided into Iris localization, Feature Extraction and Matching steps. Each of these tasks involves a lot of processing. It thus becomes essential to improve the performance of each step to […]

Query-by-content, by means of similarity search, is a fundamental operation for applications that deal with multimedia data. For this kind of query it is meaningless to look for elements exactly equal to a given one as query. Instead, we need to measure the dissimilarity between the query object and each database object. This search problem […]

Mars Rovers are the unmanned machines on planet MARS which are send to analyze and provide details about the planet. GPU and Genetic Algorithms are upcoming technologies used in Mars Rovers for analyzing and sending the data back to the Earth base station. GPU stands for Graphics Processing Unit in which Image compression is the […]

Random Forests are a popular and powerful machine learning technique, with several fast multi-core CPU implementations. Since many other machine learning methods have seen impressive speedups from GPU implementations, applying GPU acceleration to random forests seems like a natural fit. Previous attempts to use GPUs have relied on coarse-grained task parallelism and have yielded inconclusive […]

Due to their potential computation power, GPUs are often used for high performance computing. However, discrete GPUs are connected to the CPU via the PCIe bus, which can cause bottlenecks due to high latency and low bandwidth to the CPU. Lately, integrated GPUs have become more common, and due to being integrated on the CPU-chip, […]

Volume rendering has always been a popular topic in computer graphics as it captures more realistic rendering results. However, most of the rendering targets are focused on participating media distributed in the scene. In this project we integrate an Octree data structure with our path tracer in CUDA to achieve efficient volume rendering of models. […]

We propose a method for preconditioner construction and parallel implementations of the Preconditioned Conjugate Gradient algorithm on GPU platforms. The preconditioning matrix is an approximate inverse derived from an algorithm for the iterative improvement of a solution to linear equations. Using a sparse matrix-vector product, our preconditioner is well suited for massively parallel GPU architecture. […]

We present direct astrophysical N-body simulations with up to a few million bodies using our parallel MPI/CUDA code on large GPU clusters in China, Ukraine and Germany, with different kinds of GPU hardware. These clusters are directly linked under the Chinese Academy of Sciences special GPU cluster program in the cooperation of ICCS (International Center […]

We develop a systematic Bayesian framework for physics constrained parameter inference of stochastic differential equations (SDE) from partial observations. The physical constraints are derived for stochastic climate models but are applicable for many fluid systems. We first derive a condition for the Lyapunov stability of stochastic climate models based on energy conservation. Stochastic climate models […]