high performance computing on graphics processing units: hgpu.org

The acceleration of an existing linear feature detection algorithm for 2D images using GPUs is discussed. The two most time consuming components of this process are implemented on the GPU, namely, linear feature detection using dual-peak directional non-maximum suppression, and a gap filling process that joins disconnected feature masks to rectify false negatives. Multiple steps […]

There has been large amounts of research on image authentication method. Many of the schemes perform well in verification results; however, most of them are time-consuming in traditional serial manners. And improving the efficiency of authentication process has become one of the challenges in image authentication field today. In the future, it’s a trend that […]

Recently, fusion speed has emerged as an important factor in the image fusion and a substantial amount of memory and computing power are required for a high-speed fusion. This paper shows approaches to accelerate multi-scale image fusion speed on GPU (graphics processing unit) using CUDA (compute unified device architecture). The GPU has evolved into a […]

This paper presents a fast parallel method to solve the radiative transport equation in inhomogeneous participating media. We apply a novel approximation scheme to find a good initial guess for both the direct and scattered components. Then, the initial approximation is used to bootstrap an iterative multiple scattering solver, i.e., we let the iteration concentrate […]

Logical simulation is the primary method to verify the correctness of IC designs. However, today’s complex VLSI designs pose ever higher demand for the throughput of logic simulators. In this work, a parallel logic simulator was developed by leveraging the computing power of modern graphics processing units (GPUs). To expose more parallelism, we implemented a […]

This paper describes a multi-threaded parallel design and implementation of the Smith-Waterman (SW) algorithm on graphic processing units (GPUs) with NVIDIA corporation’s Compute Unified Device Architecture (CUDA). Central to this is a divide and conquer approach which divides the computation of a whole pairwise sequence alignment matrix into multiple sub-matrices (or parallelograms) each running efficiently […]

Cluster identification tasks occur in a multitude of contexts in physics and engineering such as, for instance, cluster algorithms for simulating spin models, percolation simulations, segmentation problems in image processing, or network analysis. While it has been shown that graphics processing units (GPUs) can result in speedups of two to three orders of magnitude as […]

This paper presents a massively parallel ant colony optimization – pattern search (ACO-PS) algorithm with graphics hardware acceleration on nonlinear function optimization problems. The objective of this study is to determine the effectiveness of using graphics processing units (GPU) as a hardware platform for ACO-PS. GPU, the common graphics hardware found in modern personal computers, […]

We present a development environment for distributed GPU computing targeted for multi-GPU systems, as well as graphics clusters. Our system is based on CUDA and logically extends its parallel programming model for graphics processors to higher levels of parallelism, namely, the PCI bus and network interconnects. While the extended API mimics the full function set […]

Optimizing programs for Graphic Processing Unit (GPU) requires thorough knowledge about the values of architectural features for the new computing platform. However, this knowledge is frequently unavailable, e.g., due to insufficient documentation, which is probably a result of the infancy of general purpose computing on the GPU. What makes the modeling of program performance on […]

Terrains are challenging geometric objects for real-time rendering and interactive manipulation. State-of-the-art terrain rendering systems use custom, multi-resolution, representations like geometry clipmaps for fast rendering on the GPU. In this paper, we present a system that exploits the power and flexibility of the modern GPUs to store, render, and manipulate terrains with minimal CPU involvement. […]

Markov clustering is becoming a key algorithm with in bioinformatics for determining clusters in networks. For instance, clustering protein interaction networks is helping find genes implicated in diseases such as cancer. However, with fast sequencing and other technologies generating vast amounts of data on biological networks, performance and scalability issues are becoming a critical limiting […]