Graphic Processing Units (GPUs) are fast, highly parallel units. In addition to processing 3D graphics, modern GPUs can be programmed for more general-purpose computation. A GPU consists of a large number of ‘shader processors’, and conceptually operates as a single instruction multiple data (SIMD) or multiple instruction multiple data (MIMD) stream processor. A modern GPU can have several hund...

We show how the cofactorization step, a compute-intensive part of the relation collection phase of the number field sieve (NFS), can be farmed out to a graphics processing unit. Our implementation on a GTX 580 GPU, which is integrated with a state-of-the-art NFS implementation, can serve as a cryptanalytic co-processor for several Intel i7-3770K quad-core CPUs simultaneously. This allows those ...

This paper presents the first attempt at combining Cloud with Graphic Processing Units (GPUs) in a complementary manner within the framework of a real-time high performance computation architecture for the application of detecting and tracking multiple moving targets based on Wide Area Motion Imagery (WAMI). More specifically, the GPU and Cloud Moving Target Tracking (GC-MTT) system applied a f...

The scope of computers has been expanding into increasing number of fields. With the growing need for computationally intense applications in every field, it is necessary to constantly meet the demands of performance requirements. The performance of the system relies heavily upon the processor and therefore the development of this technology is crucial. The processors of this age are handling g...

We develop a neuroevolution-potential (NEP) framework for generating neural network based machine-learning potentials. They are trained using an evolutionary strategy performing large-scale molecular dynamics (MD) simulations. A descriptor of the atomic environment is constructed on Chebyshev and Legendre polynomials. The method implemented in graphic processing units within open-source GPUMD p...

This paper presents a parallel approach to estimate the parameters in the heat loading of a district heating system by use of the traditional particle swarm optimisation (TPSO) on the Graphic Processing Unit (GPU) using OpenCL. The running time of the algorithm is greatly reduced compared to running on CPU. The heat load is approximated by the sum of time dependent and temperature dependent com...

In the last years reconfigurable computing grew from a niche application to an important R&D scene. But also today most architectures lack essential features for the convenient use as a co-processing unit. E.g. embedded accelerator design with traditional FPGAs is very similar to sophisticated ASIC-design due to the bit-level granularity of FPGAs. In this paper important topics for reconfigurab...