high performance computing on graphics processing units: hgpu.org

We explore a novel algorithm to analyze arbitrary distributions of 3D-points. Using a direct tensor field visualization technique allows to easily identify regions of linear, planar or isotropic structure. This approach is very suitable for visual data mining and exemplified upon geoscience applications. It allows to distinguish, for example, power lines and flat terrains in […]

This paper will report our evaluation to use openCL as a platform for hard realtime scheduling. Specifically, we have evaluated which types of tasks are faster on GPGPU than on CPU. We have investigated computational tasks, memory intensive tasks (especially tasks using low latency GDDR memory) and disk intensive tasks. This study is the first […]

Markov chains are a useful tool in statistics that allow us to sample and model a large population of individuals. We can extend this idea to the challenge of sampling solutions to problems. Using Markov chain Monte Carlo (MCMC) techniques we can also attempt to approximate the number of solutions with a certain confidence based […]

This thesis addresses the memory efficiency of general-purpose applications running on massively multi-threaded, data-parallel GPU architectures. Although scalable, data-parallel GPU architectures and their associated general-purpose programming models offer impressive computational capability and attractive power budgets, the pace of migrating general-purpose applications to this emerging class of architectures is significantly hindered by the efficiency of memory […]

Acceleration of cryptographic applications on massive parallel computing platforms, such as Graphic Processing Units (GPUs), becomes a real challenge concerning practical implementations. In this paper, we propose a parallel algorithm for Elliptic Curve (EC) point multiplication in order to compute EC cryptography on these platforms. The proposed approach relies on the usage of the Residue […]

The recent rise in the popularity of Graphics Processing Units (GPUs) has been fueled by software frameworks, such as NVIDIA’s Compute Unified Device Architecture (CUDA) and Khronos Group’s OpenCL that make GPUs available for general purpose computing. However, CUDA and OpenCL are still lowlevel approaches that require users to handle details about data layout and […]

Graphics processing units (GPU) have taken an important role in the general purpose computing market in recent years. At present, the common approach to programming GPU units is to write GPU specific code with low level GPU APIs such as CUDA. Although this approach can achieve good performance, it creates serious portability issues as programmers […]

Radiosity is a popular global illumination algorithm capable of achieving photorealistic rendering results. However, its use in interactive environments is limited by its computational complexity. This paper presents a GPGPU-based implementation of the gathering radiosity approach using texture-based discretisation and the OpenCL framework. Hemicubes are rendered to a texture array and processed by OpenCL kernels […]

The graphics processing unit (GPU) continues to make in-roads as a computational accelerator for highperformance computing (HPC). However, despite its increasing popularity, mapping and optimizing GPU code remains a difficult task; it is a multi-dimensional problem that requires deep technical knowledge of GPU architecture. Although substantial literature exists on how to map and optimize GPU […]

Various powerful polyhedral techniques exist to optimize computation intensive programs effectively. Applying these techniques on any non-trivial program is still surprisingly difficult and often not as effective as expected. Most polyhedral tools are limited to a specific programming language. Even for this language, relevant code needs to match specific syntax that rarely appears in existing […]

Massively parallel programming is an increasingly growing field with the recent introduction of general purpose GPU computing. Modern graphics processors from NVidia and AMD have massively parallel architectures that can be used for 3D ren-dering, financial analysis, physics simulations, and biomedical analysis. These mas-sively parallel systems are exposed to programmers through interfaces such as NVidias […]

The alignment or registration of two images or volumetric datasets is frequently a requirement in modern image-processing applications, particularly within the context of medical imaging. Modern graphics-processing units (GPUs) are designed to perform simple 3D graphics-pipeline tasks on a massively parallel scale; this processing power can be harnessed for general computation via libraries such as […]