Search results for "cud"

SAUCE: A web application for interactive teaching and learning of parallel programming

2017

Abstract Prevalent hardware trends towards parallel architectures and algorithms create a growing demand for graduate students familiar with the programming of concurrent software. However, learning parallel programming is challenging due to complex communication and memory access patterns as well as the avoidance of common pitfalls such as dead-locks and race conditions. Hence, the learning process has to be supported by adequate software solutions in order to enable future computer scientists and engineers to write robust and efficient code. This paper discusses a selection of well-known parallel algorithms based on C++11 threads, OpenMP, MPI, and CUDA that can be interactively embedded i…

High Precision Conservative Surface Mesh Generation for Swept Volumes

2015

We present a novel, efficient, and flexible scheme to generate a high-quality mesh that approximates the outer boundary of a swept volume. Our approach comes with two guarantees. First, the approximation is conservative, i.e., the swept volume is enclosed by the generated mesh. Second, the one-sided Hausdorff distance of the generated mesh to the swept volume is upper bounded by a user defined tolerance. Exploiting this tolerance the algorithm generates a mesh that is adapted to the local complexity of the swept volume boundary, keeping the overall output complexity remarkably low. The algorithm is two-phased: the actual sweep and the mesh generation. In the sweeping phase, we introduce a g…

Massively parallel computation of atmospheric neutrino oscillations on CUDA-enabled accelerators

2019

Abstract The computation of neutrino flavor transition amplitudes through inhomogeneous matter is a time-consuming step and thus could benefit from optimization and parallelization. Next to reliable parameter estimation of intrinsic physical quantities such as neutrino masses and mixing angles, these transition amplitudes are important in hypothesis testing of potential extensions of the standard model of elementary particle physics, such as additional neutrino flavors. Hence, fast yet precise implementations are of high importance to research. In the recent past, massively parallel accelerators such as CUDA-enabled GPUs featuring thousands of compute units have been widely adopted due to t…

GROMEX: A Scalable and Versatile Fast Multipole Method for Biomolecular Simulation

2020

Atomistic simulations of large biomolecular systems with chemical variability such as constant pH dynamic protonation offer multiple challenges in high performance computing. One of them is the correct treatment of the involved electrostatics in an efficient and highly scalable way. Here we review and assess two of the main building blocks that will permit such simulations: (1) An electrostatics library based on the Fast Multipole Method (FMM) that treats local alternative charge distributions with minimal overhead, and (2) A $λ$-dynamics module working in tandem with the FMM that enables various types of chemical transitions during the simulation. Our $λ$-dynamics and FMM implementations d…

The Sliced COO Format for Sparse Matrix-Vector Multiplication on CUDA-enabled GPUs

2012

Abstract Existing formats for Sparse Matrix-Vector Multiplication (SpMV) on the GPU are outperforming their corresponding implementations on multi-core CPUs. In this paper, we present a new format called Sliced COO (SCOO) and an effcient CUDA implementation to perform SpMV on the GPU. While previous work shows experiments on small to medium-sized sparse matrices, we perform evaluations on large sparse matrices. We compared SCOO performance to existing formats of the NVIDIA Cusp library. Our resutls on a Fermi GPU show that SCOO outperforms the COO and CSR format for all tested matrices and the HYB format for all tested unstructured matrices. Furthermore, comparison to a Sandy-Bridge CPU sho…

GPU-Based Occlusion Minimisation for Optimal Placement of Multiple 3D Cameras

2020

This paper presents a fast GPU-based solution to the 3D occlusion detection problem and the 3D camera placement optimisation problem. Occlusion detection is incorporated into the optimisation problem to return near-optimal positions for 3D cameras in environments containing occluding objects, which maximises the volume that is visible to the cameras. In addition, the authors’ previous work on 3D sensor placement optimisation is extended to include a model for a pyramid-shaped viewing frustum and to take the camera’s pose into account when computing the optimal position.

Three-dimensional Fuzzy Kernel Regression framework for registration of medical volume data

2013

Abstract In this work a general framework for non-rigid 3D medical image registration is presented. It relies on two pattern recognition techniques: kernel regression and fuzzy c-means clustering. The paper provides theoretic explanation, details the framework, and illustrates its application to implement three registration algorithms for CT/MR volumes as well as single 2D slices. The first two algorithms are landmark-based approaches, while the third one is an area-based technique. The last approach is based on iterative hierarchical volume subdivision, and maximization of mutual information. Moreover, a high performance Nvidia CUDA based implementation of the algorithm is presented. The f…

Connected-component identification and cluster update on graphics processing units.

2011

Cluster identification tasks occur in a multitude of contexts in physics and engineering such as, for instance, cluster algorithms for simulating spin models, percolation simulations, segmentation problems in image processing, or network analysis. While it has been shown that graphics processing units (GPUs) can result in speedups of two to three orders of magnitude as compared to serial codes on CPUs for the case of local and thus naturally parallelized problems such as single-spin flip update simulations of spin models, the situation is considerably more complicated for the nonlocal problem of cluster or connected component identification. I discuss the suitability of different approaches…

Figli di zingari. pratiche di accudimento tra povertà e discriminazione

2014

CUDA-Accelerated Alignment of Subsequences in Streamed Time Series Data

2014

Euclidean Distance (ED) and Dynamic Time Warping (DTW) are cornerstones in the field of time series data mining. Many high-level algorithms like kNN-classification, clustering or anomaly detection make excessive use of these distance measures as subroutines. Furthermore, the vast growth of recorded data produced by automated monitoring systems or integrated sensors establishes the need for efficient implementations. In this paper, we introduce linear memory parallelization schemes for the alignment of a given query Q in a stream of time series data S for both ED and DTW using CUDA-enabled accelerators. The ED parallelization features a log-linear calculation scheme in contrast to the naive …