high performance computing on graphics processing units: hgpu.org

CUDA (Compute Unified Device Architecture) is an efficient architecture developed by NVIDIA to compute parallel algorithms on Graphic Processing Unit (GPU). Using the API associated with this architecture, we develop fast parallel algorithms to compute standard methods for computerized tomography. Computation times are compared to their similar implementations on CPU to illustrate the efficiency of […]

Using Digital Holographic Microscopy (DHM) we can gather information from a whole volume and thus we can avoid the small depth of field constraint of the conventional microscopes. This way a volume inspection system can be constructed, which is capable to find, segment, collect, and later classify those objects that flow through an inspection chamber. […]

Nowadays Graphic Processing Units (GPU) are gaining increasing popularity in high performance computing (HPC). While modern GPUs can offer much more computational power than CPUs, they also consume much more power. Energy efficiency is one of the most important factors that will affect a broader adoption of GPUs in HPC. In this paper, we systematically […]

The method Finite Difference Time Domain (FDTD) is widely used in electromagnetic simulations to solve problems of microwave tomography, radar and telecommunications. Since this method is a data intensive and computation intensive problem, there are a lot of initiatives to improve the scalability and the performance of the FDTD. Despite the progress, performance in FDTD […]

Many-core graphics processors are playing today an important role in the advancements of modern highly concurrent processors. Their ability to accelerate computation is being explored under several scientific fields. In the current paper we present the acceleration of a widely used data clustering algorithm, K-means, in the context of high performance GPU clusters. As opposed […]

The characteristics of modern graphics processing unit (GPU) is programmable, high price / performance ratio and high speed. It has a strong ability to adapt the parallel calculation, Based on this, the article study the general method of GPU calculating and use compute unified device architecture (CUDA) to design new parallel algorithm to accelerate the […]

The graphics processor unit (GPU) is able to provide a low-cost and flexible software-based multi-core architecture for high performance computing. However, it is still very challenging to efficiently map the real-world applications to GPU and fully utilize the computational power of GPU. As a case study, we present a GPU-based implementation of a real-world digital […]

The paper focuses on the FraDIA vision subsystem part responsible for GPU-based image processing. The developed set of classes encapsulates the OpenCL subroutines and utilizes GPU to fulfill the robotic requirements for real-time visual data processing. The class structure reflects the proposed classification of image processing algorithms.

Since real-time acquisition of 3D echocardiographic data is achievable in practice, many volume rendering algorithms have been proposed for visualization purposes. However, due to the large amounts of data and computations involved a tradeoff between image quality and computational efficiency has to be made. The main goal of our study was to generate high quality […]

In the last decade, there has been a dramatic growth in research and development of massively parallel many-core architectures like graphics hardware, both in academia and industry. This changed also the way programs are written in order to leverage the processing power of a multitude of cores on the same hardware. In the beginning, programmers […]

We present preliminary results of the acceleration of the three-dimensional (3D) alternating direction implicit finite-difference time-domain (ADI-FDTD) method on graphics processor units (GPUs). Although the ADI-FDTD iteration comprises two substeps, which each require solving a tridiagonal matrix system of equations over xy, xz, yz planes of the domain, the application of this scheme frees the […]

One important bottleneck when visualizing large data sets is the data transfer between processor and memory. Cacheaware (CA) and cache-oblivious (CO) algorithms take into consideration the memory hierarchy to design cache efficient algorithms. CO approaches have the advantage to adapt to unknown and varying memory hierarchies. Recent CA and CO algorithms developed for 3D mesh […]