high performance computing on graphics processing units: hgpu.org

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.

Current generations of graphics processing units have turned into highly parallel devices with general computing capabilities. Thus, graphics processing units may be utilized, for example, to solve time dependent partial differential equations by the Fourier split operator method. In this contribution, we demonstrate that graphics processing units are capable to calculate fast Fourier transforms much […]

Many contemporary visualization tools comprise some image filtering approach. Since image filtering approaches are very computationally demanding, the acceleration using graphics-hardware (GPU) is very desirable to preserve interactivity of the main visualization tool itself. In this article we take a close look on GPU implementation of two basic approaches to image filtering -fast Fourier transform […]

The present work presents a cycle-level execution-driven simulator for modern GPU architectures. We discuss the simulation model used for our GPU simulator, based in the concept of boxes and signals, and the relation between the timing simulator and the functional emulator. The simulation model we use helps to increase the accuracy and reduce the number […]

The increased programmability of graphics hardware allows efficient GPU implementations of a wide range of general computations on commodity PCs. An important factor in such implementations is how to fully exploit the SIMD computing capacities offered by modern graphics processors. Linear expressions in the form of bar{y}= Abar{x}+ bar{b}, where A is a matrix, and […]

The exceptional growth of graphics hardware in programmability and data processing speed in the past few years has fuelled extensive research in using it for general purpose computations more than just image-processing and gaming applications. We explore the use of graphics processors (GPU) to speedup the computations involved in Fuzzy c-means (FCM). FCM is an […]