high performance computing on graphics processing units: hgpu.org

Solution of large-scale dense nonsymmetric eigenvalue problem is required in many areas of scientific and engineering computing, such as vibration analysis of automobiles and analysis of electronic diffraction patterns. In this study, we focus on the Hessenberg reduction step and consider accelerating it using GPU. Our main strategy is to use the CUBLAS, an optimized […]

Graphics processing units provide a large computational power at a very low price which position them as an ubiquitous accelerator. Efficient primitives that can expand the range of operations performed on the GPU are thus important. Discrete Range Searching(DRS) is one such primitive with direct applications to string processing, document and text retrieval systems, and […]

The evolution of the graphics processing units (GPU) driven by the computer games business brought a graphics hardware as a high performance, programmable and non-expensive chips. Nowadays, the graphic card has a truly programmable architecture which allows to process data with high parallelism and high memory access rate. That is the key motivation fact for […]

The method Finite Difference Time Domain (FDTD) is widely used in electromagnetic simulations. Since this method is a data intensive and computation intensive problem, there are a lot of initiatives to improve the scalability and the performance of the FDTD. Specifically the use of GPU to accelerate the FDTD is in focus, which has a […]

Nowadays, several industrial applications are being ported to parallel architectures. These applications take advantage of the potential parallelism provided by multiple core processors. Many-core processors, especially the GPUs(Graphics Processing Unit), have led the race of floating-point performance since 2003. While the performance improvement of general- purpose microprocessors has slowed significantly, the GPUs have continued to […]

The generation of molecular conformations and the evaluation of interaction potentials are common tasks in molecular modeling applications, particularly in protein-ligand or protein-protein docking programs. In this work, we present a GPU-accelerated approach capable of speeding up these tasks considerably. For the evaluation of interaction potentials in the context of rigid protein-protein docking, the GPU-accelerated […]

BACKGROUND: In actual surgery, smoke and bleeding due to cauterization processes provide important visual cues to the surgeon, which have been proposed as factors in surgical skill assessment. While several virtual reality (VR)-based surgical simulators have incorporated the effects of bleeding and smoke generation, they are not realistic due to the requirement of real-time performance. […]

The answers to data assimilation questions can be expressed as path integrals over all possible state and parameter histories. We show how these path integrals can be evaluated numerically using a Markov Chain Monte Carlo method designed to run in parallel on a Graphics Processing Unit (GPU). We demonstrate the application of the method to […]

The rapidly increasing number of cores in modern microprocessors is pushing the current high performance computing (HPC) systems into the petascale and exascale era. The hybrid nature of these systems – distributed memory across nodes and shared memory with non-uniform memory access within each node – poses a challenge to application developers. In this paper, […]

We introduce GPUMiner, a novel parallel data mining system that utilizes new-generation graphics processing units (GPUs). Our system relies on the massively multi-threaded SIMD (Single Instruction, Multiple-Data) architecture provided by GPUs. As specialpurpose co-processors, these processors are highly optimized for graphics rendering and rely on the CPU for data input/output as well as complex program […]

With the evolution of graphics processing units (GPUs) in floating point operations and programmability, GPU has increasingly become powerful and cost-efficient computing architectures, its range of application has expanded tremendously, especially in the area of computational simulation. In this article, the Fourier method combined with GPU acceleration techniques is applied to simulate large-scale transient temperature […]

Extraction of frequent patterns from a transactional database is a fundamental task in data mining. Its applications include association rules, time series, etc. The Apriori approach is a commonly used generate-and-test approach to obtain frequent patterns from a database with a given threshold. Many parallel and distributed methods have been proposed for frequent pattern mining […]