high performance computing on graphics processing units: hgpu.org

Medical Imaging is a technique aimed to develop tools to improve medical diagnosis and procedures. Medical imaging applications use different types of signals to create images of the inside of the human body. It is a very important technique that decreases the complication rate during procedures and provides with more information for more accurate diagnosis. […]

The market of computer graphics is dominated by GPU based technologies. However today’s fast central processing units (CPU) based on modern architectural design offer new opportunities in the field of classical software rendering. Because the technological development of the GPU architecture almost reached the limits in the field of the programming model, the CPU-based solutions […]

R-trees are popular spatial indexing techniques that have been widely used in many geospatial applications. The increasingly available Graphics Processing Units (GPUs) resources for general computing have attracted considerable research interests in applying the massive data parallel technologies to index and query geospatial data based on R-trees. In this paper, we investigate on the potentials […]

Simulations, like fluid dynamics, are very computationally intensive problems. Since the Lattice Boltzmann method uses a discrete grid of cells for simulating the flow, there are no dependencies between the single cells during the computation for one time step. Therefore, the computing can easily be done in parallel. During the last years, multi-CPU computers have […]

Despite the experience of several decades the numerical simulation of computational fluid dynamics is still an enormously challenging and active research field. Most simulation tasks of scientific and industrial relevance require the modeling of multiple physical effects, complex numerical algorithms, and have to be executed on supercomputers due to their high computational demands. Facing these […]

This work focuses on compiler and run-time techniques for improving the productivity and the performance portability of general-purpose parallel programming. More specifically, we focus on shared-memory task-parallel languages, where the programmer explicitly exposes parallelism in the form of short tasks that may outnumber the cores by orders of magnitude. The compiler, the run-time, and the […]

Resource allocation is an integral, evolving part of many data center management problems such as virtual machine placement in data centers, network virtualization, and multi-path network routing. Since the problems are inherently NP-Hard, most existing systems use custom-designed heuristics to find a suitable solution. However, such heuristics are often rigid, making it difficult to extend […]

One of application that needs high performance computing resources is molecular d ynamic. There is some software available that perform molecular dynamic, one of these is a well known GROMACS. Our previous experiment simulating molecular dynamics of Indonesian grown herbal compounds show sufficient speed up on 32 n odes Cluster computing environment. In order to […]

In a major breakthrough, in 2009 Gentry introduced the first plausible construction of a fully homomorphic encryption (FHE) scheme. FHE allows the evaluation of arbitrary functions directly on encrypted data on untwisted servers. In 2010, Gentry and Halevi presented the first FHE implementation on an IBM x3500 server. However, this implementation remains impractical due to […]

This article describes parallel algorithm of face detection on images for GPU architecture. This algorithm is an extension of an algorithm from OpenCV library. A computational structure is presented for the developed algorithm. Also, scheduling algorithm was developed to balance a workload among GPU’s threads.

Current trends in processor architectures increasingly include more cores on a single chip and more complex memory hierarchies, and such a trend is likely to continue in the foreseeable future. These processors offer unprecedented opportunities for speeding up demanding computations if the available resources can be effectively utilized. Simultaneously, parallel programming languages such as OpenMP […]

The particle filter is a Bayesian estimation technique based on Monte Carlo simulation. The nonparametric nature of particle filters makes them ideal for non-linear, non-Gaussian dynamic systems. Particle filtering has many applications: in computer vision, robotics, and econometrics to name just a few. Although superior to Kalman filters, particle filters have higher computational requirements, which […]