high performance computing on graphics processing units: hgpu.org

There is growing interest in using GPUs to accelerate graph algorithms such as breadth-first search, computing page-ranks, and finding shortest paths. However, these algorithms do not modify the graph structure, so their implementation is relatively easy compared to general graph algorithms like mesh generation and refinement, which morph the underlying graph in non-trivial ways by […]

Parallelization is a straightforward approach to enhance the efficiency for evolutionary computation due to its inherently parallel nature. Since NVIDIA released the compute unified device architecture (CUDA), graphic processing units have enabled lots of scalable parallel programs in a wide range of fields. However, parallelization of model building for EDAs is rarely studied. In this […]

Graphics processing units (GPUs) have been growing in popularity due to their impressive processing capabilities, and with general purpose programming languages such as NVIDIA’s CUDA interface, are becoming the platform of choice in the scientific computing community. Today the research community successfully uses GPU to solve a broad range of computationally demanding, complex problems. This […]

Anti-virus software is the main defense mechanism against malware, which is becoming more common and advanced. A significant part of the virus scanning process is dedicated to scanning a given file against a set of virus signatures. As it is important that the overall scanning process be as fast as possible, efforts must be done […]

GPUs (Graphics Processor Units) are being increasingly embraced by the high performance computing and computational communities as an effective way of considerably reducing application execution time by accelerating significant parts of their codes. CUDA (Compute Unified Device Architecture) is a new technology developed by NVIDIA which leverages the parallel compute engine in GPUs. However, the […]

We design, implement, and evaluate GPU-based algorithms for the maximum cardinality matching problem in bipartite graphs. Such algorithms have a variety of applications in computer science, scientific computing, bioinformatics, and other areas. To the best of our knowledge, ours is the first study which focuses on GPU implementation of the maximum cardinality matching algorithms. We […]

In this paper, we have researched and developed solutions for optimizing the radix sort algorithmic function using the Compute Unified Device Architecture (CUDA). The radix sort is a common parallel primitive, an essential building block for many data processing algorithms, whose optimization improves the performance of a wide class of parallel algorithms useful in data […]

Advances in sequencing technologies have revolutionized the field of genomics by providing cost effective and high throughput solutions. In this paper, we develop a parallel sequence assembler implemented on general purpose graphic processor units (GPUs). Our work was largely motivated by a growing need in the genomic community for sequence assemblers and increasing use of […]

In this paper, we present three parallel cultural algorithms using CUDA-enabled GPUs. Firstly, we used the GPU to accelerate an expensive fitness function. Next, the parallel versions of both standard and multi-population CAs were presented. Experiments show that the standard CA with an expensive fitness function was made more than 600 times faster. On lightweight […]

This paper gives an introduction to how graphical processing units can be used in non-graphical related problems or tasks. First a history of GPU is provided. The next part focuses on GPU programming. A brief description is given about the available hardware facilities and the available programming languages. As an initial result of the project […]

The wide usage of GPGPU programming models and compiler techniques enables the optimization of data-parallel programs on commodity GPUs. However, mapping GPGPU applications running on discrete parts to emerging integrated heterogeneous architectures such as the AMD Fusion APU and Intel Sandy/Ivy bridge with the CPU and the GPU on the same die has not been […]

Ray tracing presents an efficient rendering algorithm for scientific visualization using common visualization tools and scales with increasingly large geometry counts while allowing for accurate physically-based visualization and analysis, which enables enhanced rendering and new visualization techniques. Interactivity is of great importance for data exploration and analysis in order to gain insight into large-scale data. […]