high performance computing on graphics processing units: hgpu.org

In "synchronous" PSO, positions and velocities of all particles are updated in turn in each "generation", after which each particle’s new fitness is evaluated. The value of the social attractor is only updated at the end of each generation, when the fitness values of all particles are known. The "asynchronous" version of PSO, instead, allows […]

Provides a thorough introduction and overview of existing technologies in grids, clouds and virtualization, including a brief history of the field. Examines both business and scientific applications of grids and clouds. Presents contributions from an international selection of experts in the field. Research into grid computing has been driven by the need to solve large-scale, […]

We present an efficient method for the simulation of laminar fluid flows with free surfaces including their interaction with moving rigid bodies, based on the two-dimensional shallow water equations and the Lattice-Boltzmann method. Our implementation targets multiple fundamentally different architectures such as commodity multicore CPUs with SSE, GPUs, the Cell BE and clusters. We show […]

With the computing industry trending towards multi- and many-core processors, we study how a standard visualization algorithm, ray-casting volume rendering, can benefit from a hybrid parallelism approach. Hybrid parallelism provides the best of both worlds: using distributed-memory parallelism across a large numbers of nodes increases available FLOPs and memory, while exploiting shared-memory parallelism among the […]

Numerical computations of incompressible flow equations with pressure-based algorithms necessitate the solution of an elliptic Poisson equation, for which multigrid methods are known to be very efficient. In our previous work we presented a dual-level (MPI-CUDA) parallel implementation of the Navier-Stokes equations to simulate buoyancy-driven incompressible fluid flows on GPU clusters with simple iterative methods […]

We consider the problem of implementing scalable three-dimensional fast Fourier transforms with an eye toward future exascale systems comprised of graphics co-processor (GPUs) or other similarly high-density compute units. We describe a new software implementation; derive and calibrate a suitable analytical performance model; and use this model to make predictions about potential outcomes at exascale, […]

The exponential increase in the generation and collection of data has led us in a new era of data analysis and information extraction. Conventional systems based on general-purpose processors are unable to keep pace with the heavy computational requirements of data mining techniques. High performance co-processors like GPUs and FPGAs have the potential to handle […]

The work presented in this paper consists in an adaptation of a Genetic Algorithm (GA) to perform variable selection in an heterogeneous cluster where the nodes are themselves clusters of GPUs. Due to this heterogeneity, several mechanisms to perform a load balance will be discussed as well as the optimization of the fitness function to […]

Three-dimensional (3D) reconstruction of electron tomography (ET) has emerged as a leading technique to elucidate the molecular structures of complex biological specimens. Blob-based iterative methods are advantageous reconstruction methods for 3D reconstruction of ET, but demand huge computational costs. Multiple Graphic processing units (multi-GPUs) offer an affordable platform to meet these demands, nevertheless, are not […]

The identification of genome-wide transcription factor binding sites is a fundamental and crucial problem to fully understand the transcriptional regulatory processes. However, the high computational cost of many motif discovery algorithms heavily constraints their application for large-scale datasets. The rapid growth of genomic sequences and gene transcription data further deteriorates the situation and establishes a […]

We present an implementation of the improved staggered quark action lattice QCD computation designed for execution on a GPU cluster. The parallelization strategy is based on dividing the space-time lattice along the time dimension and distributing the sub-lattices among the GPU cluster nodes. We provide a mixed-precision floating-point GPU implementation of the multi-mass conjugate gradient […]

Emerging accelerating architectures, such as GPUs, have proved successful in providing significant performance gains to various application domains. However, their viability to operate on general streaming data is still ambiguous. In this paper, we propose GStream, a general-purpose, scalable data streaming framework on GPUs. The contributions of GStream are as follows: (1) We provide powerful, […]