high performance computing on graphics processing units: hgpu.org

The CCTV surveillance industry is undergoing a sea change due to the adoption of IP technologies. This is allowing the integration of a plethora of new cameras and other sensors into huge integrated networks. Adoption of IP technologies is presenting opportunities for scalable visual analytics that has the potential to add enormous value to entire […]

Cortical modeling is an area of research seeking to model and simulate the cerebral cortex of the brain, which is of fundamental importance to conscious thought and action. Computational power is a major challenge in this field and the problem is inherently well-suited to SIMD architectures. This suggests the implementation of a general-purpose GPU framework […]

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 […]

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 […]

The Graphics Processing Unit (GPU) is gaining popularity as a co-processor to the Central Processing Unit (CPU), due to its ability to surpass the latter’s performance in certain application fields. Nonetheless, harnessing the GPU’s capabilities is a non-trivial exercise that requires good knowledge of parallel programming. Thus, providing ways to extract such computational power has […]

Searching similarities between sequences is a fundamental operation in bioinformatics, providing insight in biological functions as well as tools for high-throughput data. There is a need to have algorithms able to process efficiently billions of sequences. To look for approximate similarities, a common heuristic is to consider short words that appear exactly in both sequences, […]

Co-located with 27th IEEE International Parallel & Distributed Processing Symposium (IPDPS 2013). his workshop aims to bring the programming community together to explore and discuss various options to make programming heterogeneous systems less challenging and more interesting. The workshop seeks to explore programming methodologies in the form of directive-based approaches, language extensions, novel tools and […]

Concurrency has recently come to the forefront of computing as multi-core processors become more and more common. General purpose graphics processing unit computing brings with them new language support for dealing with co-processor environments such as OpenCL and CUDA. Programming language support for multi-core architectures introduces a fundamentally new mechanism for modularity – a kernel. […]

Heterogeneous computing system increases the performance of parallel computing in many domain of general purpose computing with CPU, GPU and other accelerators. With Hardware developments, the software developments like Compute Unified Device Architecture(CUDA) and Open Computing Language (OpenCL) try to offer a simple and visualized tool for parallel computing. But it turn out to be […]

This work presents the parallelisation of a shallow water simulation model. Two parallel implementations are developed. One is for a multi-core NUMA architecture, developed in OpenMP. The other one is for a many-core GPU-accelerated architecture and is developed in OpenCL. The parallelisation process is based on an iterative approach, starting off from a naive implementation. […]

Today graphics processing units (GPUs) are not only able to generate graphical imaging but also able to expose its multicore architecture to increase computationally heavy general purpose algorithms that can be adapted to the multicore architecture of the GPU. The study conducted in this thesis explores the efficiency of using the general purpose graphics processing […]