high performance computing on graphics processing units: hgpu.org

Initially, computers were invented as devices to speed-up computations and facilitate the performance of repetitive mathematical operations. Their wider application in different areas upgraded this basic role and converted computers from calculating machines into devices for processing large amounts of data, with processing understood in a very general sense. The wonderfully large and ever increasing […]

We developed a novel parallel algorithm for particle filtering (and learning) which is specifically designed for GPUs (graphics processing units) or similar parallel computing devices. In our new algorithm, a full cycle of particle filtering (computing the value of the likelihood for each particle, constructing the cumulative distribution function (CDF) for resampling, resampling the particles […]

Linear least squares problems are commonly solved by QR factorization. When multiple solutions have to be computed with only minor changes in the underlying data, knowledge of the difference between the old data set and the new one can be used to update an existing factorization at reduced computational cost. This paper investigates the viability […]

Wireless networking technologies have fundamentally changed the way we compute, allowing ubiquitous, anytime, any-where access to information. At the same time, wireless technologies come with the security cost that adversaries may receive signals and engage in unauthorized communication even when not physically close to a network. Because of the utmost importance of wireless security, many […]

In a social network, epidemic spread could be a spread of an infection, opinions, trends, fads, diseases or worm propagation in network. Epidemic spread computation on such huge and ever growing social networks is incredibly challenging. High-performance computing using GPUs has become an important tool to solve computationally intensive problems. This paper presents a GPU […]

This thesis presents an efficient computational voxelization approach that utilizes the graphics pipeline. Our approach is hybrid in that it performs a precise gap-free computational voxelization, employs fixed-function components of the GPU, and utilizes the stages of the graphics pipeline to improve parallelism. This approach makes use of the latest features of OpenGL and fully […]

General-purpose Graphic processing units (GPGPUs) are at their best in accelerating computation by exploiting abundant thread-level parallelism (TLP) offered by many classes of HPC applications. To facilitate such high TLP, emerging programming models like CUDA and OpenCL allow programmers to create work abstractions in terms of smaller work units, called cooperative thread arrays (CTAs), consisting […]

Computing Nash equilibria is a very important problem in strategic analysis of markets, conflicts and resource allocation. Unfortunately, computing these equilibria even for moderately sized games is computationally expensive. To obtain faster execution times it is essential to exploit the available parallelism offered by the currently available massively parallel architectures. To address this issue, we […]

The demand for more and more compute power is growing rapidly in many fields of research. Accelerators, like GPUs, are one way to fulfill these requirements, but they often require a laborious rewrite of the application using special programming paradigms like CUDA or OpenCL. The Intel(R) Xeon Phi(TM) coprocessor is based on the Intel(R) Many […]

GPUs (Graphics Processing Units) have gained wide adoption as accelerators for general purpose computing. They are widely used in error-sensitive applications, i.e. General Purpose GPU (GPGPU) applications However, the reliability implications of using GPUs are unclear. This paper presents a fault injection study to investigate the end-to-end reliability characteristics of GPGPU applications. The investigation showed […]

The aim of this project is to explore and test the new potential performance improvement that can be achieved by the use of GPU processing architecture for several different types of compression algorithms. The compression algorithms are the choice of focus on the data parallelism on the GPU device. The specific algorithms ported to the […]

This thesis proposes a way of simulating the continuous casting process of steel using Smoothed Particle Hydrodynamics (SPH). It deals with the SPH modeling of mass, momentum and the energy equations. The interpolation kernel functions required for the SPH modeling of these equations are calculated. Solidification is modeled by some particles are used to represent […]