high performance computing on graphics processing units: hgpu.org

The Arnold diffusion constitutes a dynamical phenomenon which may occur in the phase space of a non-integrable Hamiltonian system whenever the number of the system degrees of freedom is M>=3. The diffusion is mediated by a web-like structure of resonance channels, which penetrates the phase space and allows the system to explore the whole energy […]

Medical simulators are gaining importance because the experience and skills necessary to perform many of the medical procedures are difficult to obtain due to patient safety and ethical issues. With the development of graphic cards, stereographic and haptic devices, more VR-based simulators are being created. We are developing an interactive ultrasound image simulation that include […]

Three distinctively different implementations of convolutional perfectly matched layer for the FDTD method on CUDA enabled graphics processing units are presented. All implementations store additional variables only inside the convolutional perfectly matched layers, and the computational speeds scale according to the thickness of these layers. The merits of the different approaches are discussed, and a […]

Computerized tomography (CT) plays a critical role in the practice of modern medicine. However, the radiation associated with CT is significant. Methods that can enable CT imaging at reduced radiation exposure without sacrificing image quality are therefore extremely important. This paper introduces a novel method for enabling improved reconstruction at lower radiation exposure levels. The […]

This dissertation maps various kernels and applications to a spectrum of programming models and architectures and also presents architecture-aware algorithms for different systems. The kernels and applications discussed in this dissertation have widely varying computational characteristics. For example, we consider both dense numerical computations and sparse graph algorithms. This dissertation also covers emerging applications from […]

GPUs are becoming an attractive computing platform not only for traditional graphics computation but also for general-purpose computation because of the computational power, programmability and comparatively low cost of modern GPUs. This has lead to a variety of complex GPGPU applications with significant performance improvements. The LU decomposition represents a fundamental step in many computationally […]

Metagenomics method directly sequences and analyzes genome information from microbial communities. There are usually more than hundreds of genomes from different microbial species in the same community, and the main computational tasks for metagenomics data analysis include taxonomical and functional component of these genomes in the microbial community. Metagenomic data analysis is both data- and […]

Application of geometric transformation to images requires an interpolation step. When applied to image rotation, the presently most efficient GPU implementation for the cubic spline image interpolation still cost about 10 times as much as linear interpolation. This implementation involves two steps: a prefilter step performs a two-pass forward-backward recursive filter, then a cubic polynomial […]

In this paper, we propose, develop and implement a tool that increases the computational speed of exotic derivatives pricing at a fraction of the cost of traditional methods. Our paper focuses on investigating the computing efficiencies of GPU systems. We utilize the GPU’s natural parallelization capabilities to price financial instruments. We outline our implementation, solutions […]

This paper proposes an error correction method for solving linear systems of equations and the evaluation of an implementation using mixed precision techniques. While different technologies are available, graphic processing units (GPUs) have been established as particularly powerful coprocessors in recent years. For this reason, our error correction approach is focused on a CUDA implementation […]

Advanced visualization algorithms are typically computationally expensive but highly data parallel which make them attractive candidates for GPU architectures. However, porting algorithms on a GPU still remains a challenging process. The Mint programming model addresses this issue with its simple and high level interface. It targets the users who seek real-time performance without investing in […]

A recent development in High Performance Computing is the availability of NVIDIA’s Fermi or the 20-series GPUs. These offer features such as inbuilt atomic double precision support and increased shared memory. This thesis focuses on optimizing and evaluating the new features offered by the Fermi series GPUs for data mining algorithms involving reductions. Using three […]