high performance computing on graphics processing units: hgpu.org

The development of parallel architectures is now nearly ubiquitous in not only the high-performance computing field, but also the commodity electronics market. Even embedded processors found in cell phones and tablet computers are starting to incorporate parallel architectures. These architectures are exploiting both SIMD (Single-Instruction Multiple-Data) and SIMT (Simple- Instruction Multiple-Thread) parallelism to achieve higher […]

Two block cyclic reduction linear system solvers are considered and implemented using the OpenCL framework. The topics of interest include a simplified scalar cyclic reduction tridiagonal system solver and the impact of increasing the radix-number of the algorithm. Both implementations are tested for the Poisson problem in two and three dimensions, using a Nvidia GTX […]

Nowadays, there is a lack of performance models for the execution of programs implemented using the CUDA model for GPU (Graphics Processing Units) devices. We have designed and implemented a suite of micro-benchmarks, called uBench. The purpose of uBench is to identify the effects on performance derived from the combination of: (1) the hardware details […]

Bioinformatics and Computational Biology (BCB) is a relatively new multidisciplinary field which brings together many aspects of the fields of biology, computer science, statistics, and engineering. Bioinformatics extracts useful information from biological data and makes these more intuitive and understandable by applying principles of information sciences, while computational biology harnesses computational approaches and technologies to […]

We present a comparison of several modern C++ libraries providing high-level interfaces for programming multi- and many-core architectures on top of CUDA or OpenCL. The comparison focuses on the solution of ordinary differential equations and is based on odeint, a framework for the solution of systems of ordinary differential equations. Odeint is designed in a […]

Simulators are limited by the available resources on the GPU as well as the CPU. Simulation of P systems with active membrane using GPUs is a new concept in the development of applications for membrane computing. P systems are an alternative approach to extract all performance available on GPUs due to its parallel nature. In […]

From the beginning the Geant4 Visualisation System was designed to support several simultaneous graphics systems written to common abstract interfaces. Today it has matured into a powerful diagnostic and presentational tool. It comes with a library of models that may be added to the current scene and which include the representation of the Geant4 geometry […]

We develop an inertial coupling method for modeling the dynamics of point-like "blob" particles immersed in an incompressible fluid, generalizing previous work for compressible fluids [F. Balboa Usabiaga, I. Pagonabarraga, and R. Delgado-Buscalioni, J. Comp. Phys., 235:701-722, 2013]. The coupling consistently includes excess (positive or negative) inertia of the particles relative to the displaced fluid, […]

Molecular dynamics (MD) is an important research tool extensively applied in materials science. Running MD on a graphics processing unit (GPU) is an attractive new approach for accelerating MD simulations. Currently, GPU implementations of MD usually run in a one-host-process-one-GPU (OHPOG) scheme. This scheme may pose a limitation on the system size that an implementation […]

Many computational applications have high performance and energy-efficiency requirements which "off-the-shelf" general-purpose processors cannot meet. On the other hand, designing special-purpose hardware accelerators can be prohibitively expensive in terms of development time. One approach to the problem is to design an Application-Specific Instruction set Processor (ASIP), which is programmable, but tailored for the task at […]

GPU computing originated in the opening of the graphics processing units (GPUs), which are devices intended to produce computer graphics, for general purpose computations. Since computer graphics is based on matrix operations, GPUs are purposely designed to implement such operations efficiently. Spectral transforms are defined in terms of sets of basis functions, which can be […]

In general, the GPU computing denotes computing over a GPU system consisting of a graphics processing unit (GPU) and a central processing unit (CPU). Such systems are aimed at accelerating the general purpose computations which considerably extends possible applications, making computationally demanding algorithms feasible in various areas of science and engineering practice. The general purpose […]