Posts
Dec, 18
Leveraging Parallelism with CUDA and OpenCL
Graphics processing units (GPUs), originally designed for computing and manipulating pixels, have become general-purpose processors capable of executing in excess of trillion calculations per second. Taking advantage of GPU’s compute power and commodity popularity, the field of computing systems is exhibiting a trend toward heterogeneous platforms consisting of a central processor integrated with graphics hardware. […]
Dec, 18
Efficient Computational Methods for Uncertainty Quantification of Large Systems
The quest to design environment-friendly and sustainable engineering systems has witnessed more and more fervent efforts in recent years. With the growth of affordable large-capacity computing resources, predictive, science-based computational models have become instrumental in this pursuit. The present work develops efficient computational methods for the uncertainty analysis of large dynamical and mechanical systems with […]
Dec, 18
Real-Time Implementation of a Full Hyperspectral Unmixing Chain on Graphics Processing Units
Hyperspectral unmixing is a very important task for remotely sensed hyperspectral data exploitation. It amounts at estimating the abundance of pure spectral signatures (called endmembers) in each mixed pixel of the original hyperspectral image, where mixed pixels arise due to insufficient spatial resolution and other phenomena. The full spectral unmixing chain comprises three main steps: […]
Dec, 18
Efficient data structures for piecewise-smooth video processing
A number of useful image and video processing techniques, ranging from low level operations such as denoising and detail enhancement to higher level methods such as object manipulation and special effects, rely on piecewise-smooth functions computed from the input data. In this thesis, we present two computationally efficient data structures for representing piecewise-smooth visual information […]
Dec, 18
The MOSIX Cluster Operating System for High-Performance Computing on Linux Clusters, Multi-Clusters, GPU Clusters and Clouds
MOSIX is a cluster operating system targeted for HighPerformance Computing (HPC) on Linux platforms, including clusters, multi-clusters, GPU clusters and Clouds. The unique features of MOSIX provide users and applications with the impression of running on a single computer with multiple processors, without changing the interface and the run-time environment of their respective login nodes. […]
Dec, 18
Parallel paradigms in optimal structural design
Modern-day processors are not getting any faster. Due to the power consumption limit of frequency scaling, parallel processing is increasingly being used to decrease computation time. In this thesis, several parallel paradigms are used to improve the performance of commonly serial SAO programs. Four novelties are discussed: First, replacing double precision solvers with single precision […]
Dec, 17
Massively Parallel Logic Simulation with GPUs
In this article, we developed a massively parallel gate-level logical simulator to address the ever-increasing computing demand for VLSI verification. To the best of the authors’ knowledge, this work is the first one to leverage the power of modern GPUs to successfully unleash the massive parallelism of a conservative discrete event-driven algorithm, CMB algorithm. A […]
Dec, 17
Extendable pattern-oriented optimization directives
Current programming models and compiler technologies for multi-core processors do not exploit well the performance benefits obtainable by applying algorithm-specific, i.e., semantic-specific optimizations to a particular application. In this work, we propose a pattern-making methodology that allows algorithm-specific optimizations to be encapsulated into "optimization patterns" that are expressed in terms of pre-processor directives so that […]
Dec, 17
Quartile and Outlier Detection on Heterogeneous Clusters Using Distributed Radix Sort
In the past few years, performance improvements in CPUs and memory technologies have outpaced those of storage systems. When extrapolated to the exascale, this trend places strict limits on the amount of data that can be written to disk for full analysis, resulting in an increased reliance on characterizing in-memory data. Many of these characterizations […]
Dec, 17
Parallel Mining of Neuronal Spike Streams on Graphics Processing Units
Multi-electrode arrays (MEAs) provide dynamic and spatial perspectives into brain function by capturing the temporal behavior of spikes recorded from cultures and living tissue. Understanding the firing patterns of neurons implicit in these spike trains is crucial to gaining insight into cellular activity. We present a solution involving a massively parallel graphics processing unit (GPU) […]
Dec, 17
GPU implementation of JPEG2000 for hyperspectral image compression
Hyperspectral image compression has received considerable interest in recent years due to the enormous data volumes collected by imaging spectrometers for Earth Observation. JPEG2000 is an important technique for data compression which has been successfully used in the context of hyperspectral image compression, either in lossless and lossy fashion. Due to the increasing spatial, spectral […]
Dec, 17
Code Optimization Techniques for Graphics Processing Units
Books on parallel programming theory often talk about such weird beasts like the PRAM model, a hypothetical hardware that would provide the programmer with a number of processors that is proportional to the input size of the problem at hand. Modern general purpose computers afford only a few processing units; four is currently a reasonable […]