high performance computing on graphics processing units: hgpu.org

In this paper, we present Patus, a code generation and auto-tuning framework for stencil computations targeted at multi- and manycore processors, such as multicore CPUs and graphics processing units. Patus, which stands for "Parallel Autotuned Stencils," generates a compute kernel from a specification of the stencil operation and a strategy which describes the parallelization and […]

The simulation of blood flow in the cardiac system has the potential to become an attractive diagnostic tool for many cardiovascular diseases, such as in the case of aneurysm. This potential could be reached if the simulations were to be completed in hours rather than days and without resorting to the use of expensive supercomputers. […]

We present a brief report on the collision search for the reduced SHA-1. With a few improvements to our previous work, directed at efficient parallelization on a GPU cluster, we managed to construct a new collision for 75-step reduced SHA-1 hash function.

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. […]

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 […]

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: […]

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 […]

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. […]

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 […]

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 […]

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 […]

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 […]