We present the first graphical processing unit (GPU) coprocessor-enabled version of the Order-N Electronic Total Energy Package (ONETEP) code for linear-scaling first principles quantum mechanical calculations on materials. This work focuses on porting to the GPU the parts of the code that involve atom-localized fast Fourier transform (FFT) operations. These are among the most computationally i...

In this paper we describe and evaluate a fast implementation of a classical block matching motion estimation algorithm for multiple Graphical Processing Units (GPUs) using the Compute Unified Device Architecture (CUDA) computing engine. The implemented block matching algorithm (BMA) uses summed absolute difference (SAD) error criterion and full grid search (FS) for finding optimal block displac...

In this paper, we present a parallel implementation of the Particle Swarm Optimization (PSO) on GPU using CUDA. By fully utilizing the processing power of graphic processors, our implementation provides a speedup of 215x compared to a sequential implementation on CPU. This speedup is significantly superior to what has been reported in recent papers and is achieved by a few simple optimizations ...

The Folding@home project harnesses a volunteer distributed computing network to perform ab initio molecular simulations of protein folding. Thanks to engineering innovations like a Graphical Processing Unit (GPU) client for running simulations, Folding@home is able to harness over 6.1 petaFLOPS of processing power, allowing it to simulate longer and more complex protein folding mechanisms than ...

Many image processing methods such as corner detection, optical flow and iterative enhancement make use of image tensors. Generally, these tensors are estimated using the structure tensor. In this work we show that the gradient energy tensor can be used as an alternative to the structure tensor in several cases. We apply the gradient energy tensor to common image problem applications such as co...

Providing untrusted applications with shared and dependable access to modern display hardware is of increasing importance. Our new display system, called Blink, safely multiplexes complex graphical content from multiple untrusted virtual machines onto a single Graphics Processing Unit (GPU). Blink does not allow clients to program the GPU directly, but instead provides a virtual processor abstr...

The Durham adaptive optics (AO) real-time controller was initially a proof of concept design for a generic AO control system. It has since been developed into a modern and powerful central-processing-unit-based real-time control system, capable of using hardware acceleration (including field programmable gate arrays and graphical processing units), based primarily around commercial off-the-shel...

This paper introduces SIMinG-1k—a manycore simulator infrastructure. SIMinG-1k is a graphics processing unit accelerated, parallel simulator for design-space exploration of large-scale manycore systems. It features an optimal trade-off between modeling accuracy and simulation speed. Its main objectives are high performance, flexibility, and ability to simulate thousands of cores. SIMinG-1k can ...

Virtual Assembly (VA) is one of the key technologies in advanced manufacturing field. It is a promising application of virtual reality in design and manufacturing field. It has drawn much interest from industries and research institutes in the last two decades. This paper describes a process for integrating an interactive Virtual Reality-based assembly simulation of a digital mockup with the CA...