high performance computing on graphics processing units: hgpu.org

Solving dense linear systems of equations is a fundamental problem in scientific computing. Numerical sim- ulations involving complex systems represented in terms of unknown variables and relations between them often lead to linear systems of equations that must be solved as fast as possible. We describe current efforts toward the development of these critical solvers […]

In order to design cellular automata rules by means of evolutionary algorithms, high computational demands need to be met. This problem may be partially solved by parallelization. Since parallel supercomputers and server clusters are expensive and often overburdened, this paper proposes the evolution of cellular automata rules on small and inexpensive graphic processing units. The […]

An exciting development in the computing industry has been the emergence of graphics processing units (the GPU) as a fast general purpose co-processor. Initially designed for gaming applications, todays GPUs demonstrate impressive computing power and high levels of parallelism and are now being used for a variety of applications far removed from traditional graphics rendering […]

Algorithmic Trading has created an increasing demand for high performance computing solutions within financial organizations. The actors of portfolio management and risk assessment have the obligation to increase their computing resources in order to provide competitive models for financial management and pricing financial instruments. GPU Stands for “Graphic Processing Unit”. GPU processing (or Stream Processing) […]

Stream reduction is the process of removing unwanted elements from a stream of outputs. It is a key component of many GPGPU algorithms, especially in multi-pass algorithms: the stream reduction is used to remove unwanted elements from the output of a previous pass before sending it as input for the next pass. In this paper, […]

The Fast Multipole Method (FMM) is specially suitable for applications in which it is necessary to predict the acoustic scattering, e.g., aircraft noise control. This accelerated iterative method has two main parts, far interactions and near interactions. Near interactions are computationally intensive and they fit properly in the Single Instruction Multiple Threads paradigm. In this […]

Our contribution deals with fast computation of dense two-component (2C) PIV vector fields using Graphics Processing Units (GPUs). We show that iterative gradient-based cross-correlation optimization is an accurate and efficient alternative to multi-pass processing with FFT-based cross-correlation. Density is meant here from the sampling point of view (we obtain one vector per pixel), since the […]

This paper compares an implementation of a Bayesian inference algorithm across several FPGAs and GPGPUs, while embracing both the execution model and high-level architecture of a GPGPU. Our study is motivated by recent work in template-based programming and architectural models for FPGA computing. The comparison we present is meant to demonstrate the FPGA’s potential, while […]

Reproducibility of an experiment is a commonly used metric to determine its validity. Within scientific computing, this can become difficult due to the accumulation of floating point rounding errors in the numerical computation, greatly reducing the accuracy of the computation. Matrix multiplication is particularly susceptible to these rounding errors which is why there exist so […]

We have combined graphics processing unit-accelerated all-atom molecular dynamics with parallel tempering to explore the folding properties of small peptides in implicit solvent on the time scale of microseconds. We applied this methodology to the synthetic beta-hairpin, trpzip2, and one of its sequence variants, W2W9. Each simulation consisted of over 8 ms of aggregated virtual […]

We present a general framework for computing two-dimensional Voronoi diagrams of different classes of sites under various distance functions. The framework is sufficiently general to support diagrams embedded on a family of two-dimensional parametric surfaces in $R^3$. The computation of the diagrams is carried out through the construction of envelopes of surfaces in 3-space provided […]

We present a general framework for computing Voronoi diagrams of different classes of sites under various distance functions in $R^3$. Most diagrams mentioned in the paper are in the plane. However, the framework is sufficiently general to support diagrams embedded on a family of two-dimensional parametric surfaces in three-dimensions. The computation of the diagrams is […]