high performance computing on graphics processing units: hgpu.org

Intelligent optimization algorithms are very effective to tackle complex problems that would be difficult or impossible to solve exactly. A key component within these algorithms is the random number generators (RNGs) which provide random numbers to drive the stochastic search process. Much effort is devoted to develop efficient RNGs with good statistical properties, and many […]

The realistic simulation of ultrasound wave propagation is computationally intensive. The large size of the grid and low degree of reuse of data means that it places a great demand on memory bandwidth. Graphics Processing Units (GPUs) have attracted attention for performing scientific calculations due to their potential for efficiently performing large numbers of floating […]

In this paper, the graphic processor unit (GPU) implementation of the finite-difference time domain (FDTD) algorithm is presented to investigate the electromagnetic (EM) scattering from one dimensional (1-D) Gaussian rough soil surface. The FDTD lattices are truncated by uniaxial perfectly matched layer (UPML), in which the finite-difference equations are carried out for the total computation […]

Discrete wavelet transform (DWT) has been widely used in many image compression applications, such as JPEG2000 and compressive sensing MRI. Even though a lifting scheme [1] has been widely adopted to accelerate DWT, only a handful of research has been done on its efficient implementation on many-core accelerators, such as graphics processing units (GPUs). Moreover, […]

Support Vector Machine (SVM) has been widely used in data-mining and Big Data applications as modern commercial databases start to attach an increasing importance to the analytic capabilities. In recent years, SVM was adapted to the field of High Performance Computing for power/performance prediction, auto-tuning, and runtime scheduling. However, even at the risk of losing […]

Unsteady free-wake solutions of wind turbine flow fields involve computationally intensive interaction calculations, which generally limit the total amount of simulation time or the number of turbines that can be simulated by the method. This problem, however, can be addressed easily using high-level of parallelization. Especially when exploited with a GPU, a Graphics Processing Unit, […]

This paper introduces the development of a new GPU-based database to accelerate data retrieval. The main goal is to explore new ways of handling complex data types and managing data and workloads in massively parallel databases. This paper presents three novel innovations to create an efficient virtual database engine that executes the majority of database […]

The Compact Muon Solenoid (CMS) experiment at the Large Hadron Collider (LHC) is a general-purpose particle detector and comprises the largest silicon-based tracking system built to date with 75 million individual readout channels. The precise reconstruction of particle tracks from this tremendous amount of input channels is a compute-intensive task. The foreseen LHC beam parameters […]

In this paper CUDA (Compute Unified Device Architecture) programming and OpenMP (Open Multi-Processing) are used for the GPU (Graphics Processing Unit) and CPU (Central Processing Unit) parallel computation of material damage. The material damage is evaluated by a multilevel finite element analysis within material domains reconstructed from a high-resolution micro-focus X-ray computed tomography system. An […]

Sequence alignment is a task that calculates the degree of similarity between two sequences. Given a query sequence, finding a database sequence which is most similar to the query by sequence alignment is the first step in bioinformatics research. The first sequence alignment algorithm was proposed by Needle-man and Wunsch. They got the optimal global […]

Medusa is a parallel graph processing system on graphics processors (GPUs). The core design of Medusa is to enable developers to leverage the massive parallelism and other hardware features of GPUs by writing sequential C/C++ code for a small set of APIs. This simplifies the implementation of parallel graph processing on the GPU. The runtime […]

The demands placed on systems to analyse corpus data increase with input size, and the traditional approaches to processing this data are increasingly having impractical run-times. We show that the use of desktop GPUs presents a significant opportunity to accelerate a number of stages in the normal corpus analysis pipeline. This paper contains our exploratory […]