Using GPGPU accelerated interpolation algorithms for marine bathymetry processing with on-premises and cloud based computational resources
Data crowdsourcing is one of most remarkable results of pervasive and internet connected
low-power devices making diverse and different “things” as a world wide distributed system …
low-power devices making diverse and different “things” as a world wide distributed system …
Towards a parallel component in a GPU–CUDA environment: a case study with the L-BFGS Harwell routine
Modern graphics processing units (GPUs) have been at the leading edge of increasing
parallelism over the last 10 years. This fact has encouraged the use of GPUs in a broader …
parallelism over the last 10 years. This fact has encouraged the use of GPUs in a broader …
An adaptive algorithm for high‐dimensional integrals on heterogeneous CPU‐GPU systems
In this paper, we introduce an adaptive procedure for the numerical computation of a high‐
dimensional integrals on HPC systems with heterogeneous nodes composed of multi‐core …
dimensional integrals on HPC systems with heterogeneous nodes composed of multi‐core …
The high performance internet of things: using GVirtuS to share high-end GPUs with ARM based cluster computing nodes
G Laccetti, R Montella, C Palmieri… - … Conference on Parallel …, 2013 - Springer
The availability of computing resources and the need for high quality services are rapidly
evolving the vision about the acceleration of knowledge development, improvement and …
evolving the vision about the acceleration of knowledge development, improvement and …
Performance evaluation for a PETSc parallel-in-time solver based on the MGRIT algorithm
We herein describe the performance evaluation of a modular implementation of the MGRIT
(MultiGrid-In-Time) algorithm within the context of the PETSc (the Portable, Extensible …
(MultiGrid-In-Time) algorithm within the context of the PETSc (the Portable, Extensible …
QCG-OMPI: MPI applications on grids
Computational grids present promising computational and storage capacities. They can be
made by punctual aggregation of smaller resources (ie, clusters) to obtain a large-scale …
made by punctual aggregation of smaller resources (ie, clusters) to obtain a large-scale …
An Adaptive Strategy for Dynamic Data Clustering with the K-Means Algorithm
K-means algorithm is one of the most widely used methods in data mining and statistical
data analysis to partition several objects in K distinct groups, called clusters, on the basis of …
data analysis to partition several objects in K distinct groups, called clusters, on the basis of …
A high performance modified K-means algorithm for dynamic data clustering in multi-core CPUs based environments
K-means algorithm is one of the most widely used methods in data mining and statistical
data analysis to partition several objects in K distinct groups, called clusters, on the basis of …
data analysis to partition several objects in K distinct groups, called clusters, on the basis of …
Um ambiente de monitoramento de recursos e escalonamento cooperativo de aplicações paralelas em grades computacionais.
NC Paula - 2009 - teses.usp.br
Grade computacional é uma alternativa para melhorar o desempenho de aplicações
paralelas, por permitir o uso simultâneo de vários recursos distribuídos. Entretanto, para …
paralelas, por permitir o uso simultâneo de vários recursos distribuídos. Entretanto, para …
[PDF][PDF] Performance Evaluation for a PETSc Parallel-in-Time Solver Based on the MGRIT Algorithm
L Carracciuolo, L D'Amore - academia.edu
We herein describe the performance evaluation of a modular implementation of the MGRIT
(MultiGrid-In-Time) algorithm within the context of the PETSc (the Portable, Extensible …
(MultiGrid-In-Time) algorithm within the context of the PETSc (the Portable, Extensible …