high performance computing on graphics processing units: hgpu.org

Simulators are still the primary tools for development and performance evaluation of applications running on massively parallel architectures. However, current virtual platforms are not able to tackle the complexity issues introduced by 1000-core future scenarios. We present a fast and accurate simulation framework targeting extremely large parallel systems by specifically taking advantage of the inherent […]

As one of the most popular accelerators, Graphics Processing Unit (GPU) has demonstrated high computing power in several application fields. On the other hand, GPU also produces high power consumption and has been one of the most largest power consumers in desktop and supercomputer systems. However, software power optimization method targeted for GPU has not […]

This paper deals with depth maps extraction from multi-view video. Contrary to standard stereo matching-based approaches, depth maps are computed here using optical flow estimations between consecutive views. We compare our approach with the one proposed in the Depth Estimation Reference Software (DERS) for normalization purposes in the ISO-MPEG 3DV group. Experiments conducted on sequences […]

In the following paper we present techniques for data-parallel execution of the cellular potts model (CPM) on graphics processing units (GPUs). We have developed data-structures and algorithms that are optimized to use available hardware resources on the GPU. To the best of our knowledge, this is the first attempt at using data-parallel techniques for simulating […]

Demand for 3D visualization is increasing in mobile devices as users have come to expect more realistic immersive experiences. However, limited networking and computing resources on mobile devices remain challenges. A solution is to have a proxy-based framework that offloads the burden of rendering computation from mobile devices to more powerful servers. We present the […]

Motif is overrepresented pattern in biological sequence and motif finding is an important problem in bioinformatics. Due to high computational complexity of motif finding, more and more computational capabilities are required as the rapid growth of available biological data, such as gene transcription data. Among many motif finding algorithms, Gibbs sampling is an effective method […]

In this paper, several methods of optimizing parallel implementation of 2D FDTD algorithm are presented. Some practical problems occurring in real simulations are taken into consideration. Moreover, the presented methods are supported with appropriate tests and practical examples.

The Gauss-Seidel method is very efficient for solving problems such as tightly-coupled constraints with possible redundancies. However, the underlying algorithm is inherently sequential. Previous works have exploited sparsity in the system matrix to extract parallelism. In this paper, we propose to study several parallelization schemes for fully-coupled systems, unable to be parallelized by existing methods, […]

Over the last few years, we have witnessed the proliferation of GPU devices onHPC environments. Manufacturers produce new versions of their devices every few years, though, posing a new problem for scientists and engineers using their technology: is it worth the time and effort spent optimizing the codes for the current version? Or it is […]

Emerging general-purpose Graphics Processing Unit (GPU) provides a multi-core platform for wide applications, including machine learning algorithms. In this paper, we proposed several techniques to accelerate Support Vector Machines (SVM) on GPUs. Sparse matrix format is introduced into parallel SVM to achieve better performance. Experimental results show that the speedup of 55x-133.8x over LIBSVM can […]

The power of graphics processing unit(GPU) has been increasing rapidly more than that of CPU. It is not surprising that many software libraries were developed which enable us to use the power of GPU for general computations especially in parallel data processing. In this paper, we propose implementations of the standard block cipher ARIA of […]

The increase in computational power of off-the-shelf hardware offers more and more advantageous tradeoffs among efficiency, cost and availability, thus enhancing the feasibility of of cryptanalytic attacks aiming to lower the security of widely used cryptosystems. In this paper we illustrate an GPU-based software implementation of the most efficent variant of Data Encryption Standard (DES), […]