high performance computing on graphics processing units: hgpu.org

A novel parallel approach to run standard particle swarm optimization (SPSO) on Graphic Processing Unit (GPU) is presented in this paper. By using the general-purpose computing ability of GPU and based on the software platform of Compute Unified Device Architecture (CUDA) from NVIDIA, SPSO can be executed in parallel on GPU. Experiments are conducted by […]

This paper presents a performance analysis of an accelerated 2-D rigid image registration implementation that employs the Compute Unified Device Architecture (CUDA) programming environment to take advantage of the parallel processing capabilities of NVIDIA’s Tesla C870 GPU. We explain the underlying structure of the GPU implementation and compare its performance and accuracy against a fast […]

Graphics processors (GPU) offer the promise of more than an order of magnitude speedup over conventional processors for certain non-graphics computations. Because the GPU is often presented as a C-like abstraction (e.g., Nvidia’s CUDA), little is known about the characteristics of the GPU’s architecture beyond what the manufacturer has documented. This work develops a microbechmark […]

Graphics processors are continuing their trend of vastly outperforming CPUs while becoming more general purpose. The latest generation of graphics processors have introduced the ability handle integers natively. This has increased the GPU’s applicability to many fields, especially cryptography. This paper presents an application oriented approach to block cipher processing on GPUs. A new block […]

We study the role of dust-dust collisional charging in protoplanetary discs. We show that dust-dust collisional charging becomes an important process in determining the charge state of dust and gas, if there is dust enhancement and/or dust is fluffy, so that dust surface area per disc volume is locally increased. We solve the charge equilibrium […]

The widespread adoption of on-board volumetric imaging in cancer radiotherapy has stimulated research efforts to develop online adaptive radiotherapy techniques to handle the inter-fraction variation of the patient’s geometry. Such efforts face major technical challenges to perform treatment planning in real-time. To overcome this challenge, we are developing a supercomputing online re-planning environment (SCORE) at […]

DSPSR is a high-performance, open-source, object-oriented, digital signal processing software library and application suite for use in radio pulsar astronomy. Written primarily in C++, the library implements an extensive range of modular algorithms that can optionally exploit both multiple-core processors and general-purpose graphics processing units. After over a decade of research and development, DSPSR is […]

We study the energy transfer in light-harvesting complexes (LHC) and the importance of quantum coherence and the backaction of the molecular environment on the energy flow. We calculate the energy-transfer efficiency and the trapping time for the Fenna-Matthews-Olson (FMO) complex within the exact hierarchical approach proposed by Ishizaki and Fleming (J. Chem. Phys. vol 130, […]

We compare the performance of the treecode and the fast multipole method (FMM) on GPUs. These fast algorithms are used to accelerate a vortex particle simulation of two leapfrogging vortex rings. The performance of the treecode and FMM depends strongly on the number of particles, type of hardware, distribution of particles, and the required accuracy. […]

Parallel computing provides efficient solutions for combinatorial optimization problem. However, since the communications among computing processes are rather cost-consuming, the actual parallel or distributed algorithm comes with substantial expenditures, such as, hardware, management, and maintenance. In this study, a parallel immune algorithm based on graphic processing unit (GPU) that originally comes to process the computer […]

As neuroimaging algorithms and technology continue to grow faster than CPU performance in complexity and image resolution, data-parallel computing methods will be increasingly important. The high performance, data-parallel architecture of modern graphical processing units (GPUs) can reduce computational times by orders of magnitude. However, its massively threaded architecture introduces challenges when GPU resources are exceeded. […]

As the line between GPUs and CPUs begins to blur, it’s important to understand what makes GPUs tick.