high performance computing on graphics processing units: hgpu.org

A methodology and its associated algorithms are presented for mapping a novel, field-based vehicular mobility model onto graphical processing unit computational platform for simulating mobility in large-scale road networks. Of particular focus is the achievement of real-time execution, on desktop platforms, of vehicular mobility on road networks comprised of millions of nodes and links, and […]

A major challenge in the field of Modeling & Simulation is providing efficient parallel computation for a variety of algorithms. Algorithms that are described easily and computed efficiently for continuous simulation, may be complex to describe and/or efficiently execute in a discrete event context, and vice-versa. Real-world models often employ multiple algorithms that are optimally […]

Lists intersection is an important operation in mod- ern web search engines. Many prior studies have focused on the single-core or multi-core CPU platform or many-core GPU. In this paper, we propose a CPU-GPU cooperative model that can integrate the computing power of CPU and GPU to perform lists intersection more efficiently. In the so-called […]

This paper presents a hybrid algorithm for rendering approximate motion and defocus blur with precise stochastic visibility evaluation. It demonstrates—for the first time, with a full stochastic technique—real-time performance on conventional GPU architectures for complex scenes at 1920×1080 HD resolution. The algorithm operates on dynamic triangle meshes for which per-vertex velocity or corresponding vertices from […]

Matching image features between an image and a map of landmarks is usually a time consuming process in mobile robot localization or Simultaneous Localisation And Mapping algorithms. The main problem is being able to match features in spite of viewpoint changes. Methods based on interest point descriptors such as SIFT have been implemented on GPUs […]

Dynamic Tubular Grids (DT-Grids) are designed to encode gridaligned data in level-set simulations. While they are extremely efficient for storing sparse volumetric data, they require logarithmic time for random access. We demonstrate that DT-Grids can be used to efficiently render sparse volumetric data that would otherwise not be able to fit in texture memory. For […]

We present an introduction to the field of GPU accelerated computer vision by examining several projects that provide the framework for researchers and developers to tap into the computational power of Graphics Processing Units (GPU). Our goal is to identify the tools and areas where GPU acceleration can provide the highest performance increases in computer […]

The future of high-performance computing is likely to rely on the ability to efficiently exploit huge amounts of parallelism. One way of taking advantage of this parallelism is to formulate problems as “embarrassingly parallel” Monte-Carlo simulations, which allow applications to achieve a linear speedup over multiple computational nodes, without requiring a super-linear increase in inter-node […]

Random number generation is a very important operation in computational science e.g. in Monte Carlo simulations methods. It is also a computationally intensive operation especially for high quality random number generation. In this paper, we present the design and implementation of a parallel implementation of one of the most widely used random number generators, namely […]

NVIDIA have released a new platform (CUDA) for general purpose computing on their graphical processing units (GPU). This paper evaluates use of this platform for statistical machine learning applications. The transfer rates to and from the GPU are measured, as is the performance of matrix vector operations on the GPU. An implementation of a sparse […]

This paper presents an approach that allows for performing regression on large data sets in reasonable time. The main component of the approach consists in speeding up the slowest operation of the used algorithm by running it on the Graphics Processing Unit (GPU) of the video card, instead of the processor (CPU). The experiments show […]

Desktop software developers interest in graphics hardware is increasing as a result of modern graphics cards’ capabilities to act as compute devices that augment the main processor. This capability means parallel computing is no longer a dedicated task for the CPU. A trend toward heterogeneous computing combines the main processor and graphics processing unit (GPU). […]