Monte Carlo methods provide enormous scope for realistic statistical modeling and simulation. The implementation of large-scale Monte Carlo applications on the grid benefits from state-of-the-art approaches to accessing resources in a computational grid. Workflow techniques allow one to describe and enact his simulation processes in a structured, manageable, and verifiable way. We developed the Grid-Computing Infrastructure for Monte Carlo Applications (GCIMCA) based on the Globus toolkit and the SPRNG library. The Globus toolkit facilitates the creation and utilization of a computational grid for large distributed computational jobs and the Scalable Parallel Random Number Generators (SPRNG) library is designed to generate practically infin...
Monte Carlo simulation is an effective way to analyze models of sophisticated problems, but often su...
International audienceEvaluating the performance of distributed systems through real experimentation...
International audienceThis paper introduces an end-to-end framework for efficient computing and merg...
The implementation of large-scale Monte Carlo computation on the grid benefits from state-of-the-art...
Abstract. Monte Carlo applications are widely perceived as computationally intensive but naturally p...
International audienceThis paper presents an end-to-end SimGrid-based simulation of a Monte-Carlo co...
Reservoir simulators are computationally costly and produce diverse, voluminous results. These featu...
he objective of this work is to improve the performance of Monte Carlo codes on Grid production infr...
Monte Carlo simulations needing many replicates to obtain good statistical results can be easily exe...
Abstracts — In this paper, we extend the techniques used in Grid-based Monte Carlo applications to G...
Internet computing and Grid technologies change the way we tackle complex problems. Grid computing c...
présenté par C. Thiam, transparents, résumé, pas de proceedingsThe Monte Carlo platform GATE (Geant4...
Particle-tracking Monte-Carlo applications are easily parallelizable, but efficient parallelization ...
The BABAR Collaboration, based at Stanford Linear Accelerator Center (SLAC), Stanford, US, has been ...
Monte Carlo production in CMS has received a major boost in performance and scale since the past CHE...
Monte Carlo simulation is an effective way to analyze models of sophisticated problems, but often su...
International audienceEvaluating the performance of distributed systems through real experimentation...
International audienceThis paper introduces an end-to-end framework for efficient computing and merg...
The implementation of large-scale Monte Carlo computation on the grid benefits from state-of-the-art...
Abstract. Monte Carlo applications are widely perceived as computationally intensive but naturally p...
International audienceThis paper presents an end-to-end SimGrid-based simulation of a Monte-Carlo co...
Reservoir simulators are computationally costly and produce diverse, voluminous results. These featu...
he objective of this work is to improve the performance of Monte Carlo codes on Grid production infr...
Monte Carlo simulations needing many replicates to obtain good statistical results can be easily exe...
Abstracts — In this paper, we extend the techniques used in Grid-based Monte Carlo applications to G...
Internet computing and Grid technologies change the way we tackle complex problems. Grid computing c...
présenté par C. Thiam, transparents, résumé, pas de proceedingsThe Monte Carlo platform GATE (Geant4...
Particle-tracking Monte-Carlo applications are easily parallelizable, but efficient parallelization ...
The BABAR Collaboration, based at Stanford Linear Accelerator Center (SLAC), Stanford, US, has been ...
Monte Carlo production in CMS has received a major boost in performance and scale since the past CHE...
Monte Carlo simulation is an effective way to analyze models of sophisticated problems, but often su...
International audienceEvaluating the performance of distributed systems through real experimentation...
International audienceThis paper introduces an end-to-end framework for efficient computing and merg...