high performance computing on graphics processing units: hgpu.org

In this paper, we propose a new very simple numerical method for solving liquid-gas compressible flows. Such flows are difficult to simulate because classic conservative finite volume schemes generate pressure oscillations at the liquid-gas interface. We extend to several dimensions the random choice scheme that we have constructed in [2]. The extension is performed through […]

The Ocean-Land-Atmosphere Model (OLAM) is an atmospheric model to simulate and cover all Earth surface. OLAM demands a great amount of processing in a simulation because of the large number of data structures used to represent the atmosphere. Because of this, we investigate in this paper how to increase performance using GPUs to compute the […]

The ability to predict the performance of applications in large-scale parallel systems is essential. One of the main incentives for this is the high cost of executing non-production tasks on these systems. An entity may also want to predict the performance in a system that does not yet exist. One popular alternative for increasing a […]

Compilers introduce a set of optimizations to speed-up source code. However due to the variety of computation platforms, algorithm complexity and problem sizes, general purpose compilers can fail to improve performance. The burden on library developers increases significantly to write optimized libraries since the user code relies on them for performance. This argument strengthens the […]

Graphic Processing Units are very prone to be corrupted by neutrons. Experimental results show that in the majority of the cases a typical application like matrix multiplication is affected by multiple output errors. In this paper we evaluate how different thread distributions impact the multiple output errors occurrence. The reported results and the performed architecture […]

Point processes constitute a natural extension of Markov Random Fields (MRF), designed to handle parametric objects. They have shown efficiency and competitiveness for tackling object extraction problems in vision. Simulating these stochastic models is however a difficult task. The performances of the existing samplers are limited in terms of computation time and convergence stability, especially […]

We present the open source Astrophysical Multi-purpose Software Environment (AMUSE, www.amusecode.org), a component library for performing astrophysical simulations involving different physical domains and scales. It couples existing codes within a Python framework based on a communication layer using MPI. The interfaces are standardized for each domain and their implementation based on MPI guarantees that the […]

This book covers the breadth of Haskell’s diverse selection of programming APIs for concurrent and parallel programming. It is split into two parts. The first part, on parallel programming, covers the techniques for using multiple processors to speed up CPU-intensive computations, including methods for using parallelism in both idiomatic Haskell and numerical array-based algorithms, and […]

The aim of the thesis is to implement and optimize chosen image processing algorithms used in digital holographic microscopy on the GPU. The algorithms are 2-D phase unwrapping and polynomial surface fitting. They are described and certain used optimizations are pointed out. The results chapter shows the performance and precision of the GPU implementation compared […]

Osteoporosis is a disease that affects a growing number of people by increasing the fragility of their bones. To improve the understanding of the bone, large scaled computer simulations are applied. A fast, scalable and memory efficient solver for such problems is ParOSol. It uses the preconditioned conjugate gradient algorithm with a multigrid preconditioner. A […]

The Intel Xeon Phi architecture from Intel Corporation features parallelism at the level of many x86-based cores, multiple threads per core, and vector processing units. Lattice Quantum Chromodynamics (LQCD) is currently the only known model independent, non perturbative computational method for calculations in theory of the strong interactions, and is of importance in studies of […]

This paper discusses issues related to GPU for Economic problems. It highlights new methodologies and resources that are available for solving and estimating economic models and emphasizes situations when they are useful and others where they are impractical. Two examples illustrate the different ways these GPU parallel methods can be employed to speed computation.