high performance computing on graphics processing units: hgpu.org

The reservoir computer comprises a reservoir of possibly non-linear, possibly chaotic dynamics. By perturbing and taking outputs from this reservoir, its dynamics may be harnessed to compute complex problems at "the edge of chaos". One of the first forms of reservoir computer, the Echo State Network (ESN), is a form of artificial neural network that […]

With the plateauing of processor frequencies and increase in energy consumption in computing, application developers are seeking new sources of performance acceleration. Heterogeneous platforms with multiple processor architectures offer one possible avenue to address these challenges. However, modern heterogeneous programming models tend to be either so low-level as to severely hinder programmer productivity, or so […]

Over the past decade, computing architectures have continued to exploit multiple levels of parallelism in applications. This increased interest in parallel computing has not only fueled the growth of multi-core processors but has also lead to an emergence of several non-traditional computing architectures like General Purpose Graphical Processing Units (GP-GPUs), Cell Processors, and Field Programmable […]

Heterogeneous systems have grown in popularity within the commercial platform and application developer communities. We have seen a growing number of systems incorporating CPUs, Graphics Processors (GPUs) and Accelerated Processing Units (APUs combine a CPU and GPU on the same chip). These emerging class of platforms are now being targeted to accelerate applications where the […]

Graphics Processing Units (GPUs) are widely used to unload the CPUs, liberate other resources of a given computer system, and provide an alternative to multiprocessor computers as a means of processing computationally expensive parallel tasks. The recent trend of utilizing GPUs in embedded systems necessitates the development of timing analysis techniques for finding the joint […]

This article presents a method of implementation genetic algorithm in CUDA. Used algorithm operat on a large population and a complex genotype, so that it exceeded the size of the cache memory. It is not completely transferred to the graphics card. It consists of modules that run on the CPU and are synchronized through it. […]

Nowadays, non-photorealistic volume rendering has become a useful technique in medicine and scientific visualization. One of these rendering techniques is silhouette extraction of iso-surfaces. This paper proposes three methods of extracting silhouettes from relatively large datasets very fast (in some cases, even in real time), using the GPGPU technology. These methods are suitable for different […]

The main goal of this project is to develop a computer program to model the creation of structure in Saturn’s ring system. The computer program will be used to answer these questions: (1) How are gaps in Saturn’s Rings formed; (2) how accurately can I model gap formation with a 3D N-Body simulation; and (3) […]

This article presents the GPU parallelization of new algorithms SD and DPD types for molecular dynamics systems developed by the Molecular Dynamics Group, University of Groningen, the Netherlands. One should note that molecular dynamics simulations are time-consuming simulations of systems, running time ranging from days to weeks and months. Therefore parallelization is a key issue […]

This paper presents the Matlab package DeCo (Density Combination) which is based on the paper by Billio et al. (2013) where a constructive Bayesian approach is presented for combining predictive densities originating from different models or other sources of information. The combination weights are time-varying and may depend on past predictive forecasting performances and other […]

OpenCL is now available on a very large set of processors. This makes this language an attractive layer to address multiple targets with a single code base. The question on how sensitive to the underlying hardware is the OpenCL code in practice remains to be better understood. This paper studies how realistic it is to […]

Unleashing the full potential of heterogeneous systems, consisting of multi-core CPUs and GPUs, is a challenging task due to the difference in processing capabilities, memory availability, and communication latencies of different computational resources. In this paper we propose a novel approach that automatically optimizes task partitioning for different (input) problem sizes and different heterogeneous architectures. […]