In this state of the art report I discuss the newly released parallel computing APIs CUDA and OpenCL, and their adoption and current use in visualization. A brief introduction to each API and their approach to parallel computing is given. The main focus though, is on the application of OpenCL and CUDA in different areas of visualization. Each method and field will be given time according to the...

Today’s graphics processors are highly programmable, massively parallel compute engines. With the development of open, industry standards, parallel programming languages such as OpenCLTM and the continued evolution of heterogeneous computing, general-purpose graphics processing units (GPGPUs) offer exciting new capabilities for the embedded market. This paper examines some of the industry facto...

In this white paper we report the work that was done on the problem of generation combinatorial structures with some rare invariant properties. These combinatorial structures are connected integral graphs. All (588) of such graphs of order 1 ≤ n ≤ 12 are known. The main goal of this work was to reduce the time of generation by distributing graph generators over hosts in PRACE-RI, and to reduce ...

We show that efficient simulations of the Kardar-Parisi-Zhang interface growth in 2 + 1 dimensions and of the 3-dimensional Kinetic Monte Carlo of thermally activated diffusion can be realized both on GPUs and modern CPUs. In this article we present results of different implementations on GPUs using CUDA and OpenCL and also on CPUs using OpenCL and MPI. We investigate the runtime and scaling be...

This paper presents a lightweight, open-source and high-performance python package for solving peridynamics problems in solid mechanics. The development of this solver is motivated by the need fast analysis tools to achieve large number simulations required `outer-loop' applications, including sensitivity analysis, uncertainty quantification optimisation. Our software toolbox utilises heterogen...

In big text-processing tasks, the exact patternmatching problem still remains time consuming. As algorithms asymptotically faster than existing ones cannot be developed, there is a need to use another approach to promote efficiency. Thus, parallel computing is able to significantly speed up the process of the exact pattern-matching problem solving. That is why the current work is focused on par...

We present a high performance GPU programming language, based on OpenCL, that is embedded in C++. Our embedding provides shared data structures, typesafe kernel invocation, and the ability to more naturally interleave CPU and GPU functions, similar to CUDA but with the portability of OpenCL. For expressivity, our language provides the FILL abstraction that releases control over data writes to t...