high performance computing on graphics processing units: hgpu.org

In this paper we review two different numerical methods for Vlasov-Maxwell simulations. The first method is based on a coupling between a Discontinuous Galerkin (DG) Maxwell solver and a Particle-In-Cell (PIC) Vlasov solver. The second method only uses a DG approach for the Vlasov and Maxwell equations. The Vlasov equation is first reduced to a […]

Genetic Programming (GP) may dramatically increase the performance of software written by domain experts. GP and autotuning are used to optimise and refactor legacy GPGPU C code for modern parallel graphics hardware and software. Speed ups of more than six times on recent nVidia GPU cards are reported compared to the original kernel on the […]

We present a performance analysis of a parallel implementation of both conjugate gradient and preconditioned conjugate gradient solvers using graphic processing units with CUDA parallel programming model. The solvers were optimized for a fast solution of sparse systems of equations arising from Finite Element Analysis (FEA) of electromagnetic phenomena. The preconditioners were Incomplete Cholesky factorization […]

Exact short read mapping to whole genomes with the Smith-Waterman algorithm is computationally expensive yet highly accurate when aligning reads with mismatches and gaps. We introduce a GPU program called MaxSSmap with the aim of achieving comparable accuracy to Smith-Waterman but with faster runtimes. Similar to mainstream approaches MaxSSmap identifies a local region of the […]

The number of space objects such as satellites, spacecraft, and debris are increasing significantly, and so is the need for tracking them for security and collision avoidance purposes. In this context, as parallelism is becoming a new paradigm, the need of implementing high performance propagators remain unmet. For this, we implemented Simplified General Perturbations No. […]

GPU architecture has traditionally been used in graphics application because of its enormous computing capability. Moreover, GPU architecture has also been used for general purpose computing in these days. Most of the current scheduling frameworks that are developed to handle GPGPU workload operate sequentially. This is problematic since this sequential approach may not be scalable […]

We present PEANUT (ParallEl AligNment UTility), a highly parallel GPU-based read mapper with several distinguishing features, including a novel q-gram index (called the q-group index) with small memory footprint built on-the-fly over the reads and the possibility to output both the best hits or all hits of a read. Designing the algorithm particularly for the […]

We discuss the development, verification, and performance of a GPU accelerated discontinuous Galerkin method for the solutions of two dimensional nonlinear shallow water equations. The shallow water equations are hyperbolic partial differential equations and are widely used in the simulation of tsunami wave propagations. Our algorithms are tailored to take advantage of the single instruction […]

We present an efficient, robust and fully GPU-accelerated aggregation-based algebraic multigrid preconditioning technique for the solution of large sparse linear systems. These linear systems arise from the discretization of elliptic PDEs. The method involves two stages, setup and solve. In the setup stage, hierarchical coarse grids are constructed through aggregation of the fine grid nodes. […]

This white paper reports on ours efforts to optimize a 2D/3D astrophysical (magento-)hydrodynamics Fortran code for XeonPhi. The code is parallelized with OpenMP and is suitable for execution on a shared memory system. Due to complexity of the code combined with immaturity of compiler we were unable to stay within the boundaries of Intel Compiler […]

The ultrasound videos are mainly contaminated by multiplicative noises but also contaminated with additive noises. As the past few decades, there are some studies to remove the noises from ultrasound images as in the JY model [1] and the variational model which removes both types of noises. However, denoising these noises from the ultrasound video […]

This paper describes the new release of RASR – the open source version of the well-proven speech recognition toolkit developed and used at RWTH Aachen University. The focus is put on the implementation of the NN module for training neural network acoustic models. We describe code design, configuration, and features of the NN module. The […]