N
Nathalie Furmento
Researcher at Imperial College London
Publications - 36
Citations - 1529
Nathalie Furmento is an academic researcher from Imperial College London. The author has contributed to research in topics: Runtime system & Grid. The author has an hindex of 19, co-authored 34 publications receiving 1460 citations. Previous affiliations of Nathalie Furmento include University of Bordeaux & L'Abri.
Papers
More filters
Proceedings ArticleDOI
hwloc: A Generic Framework for Managing Hardware Affinities in HPC Applications
François Broquedis,Jérôme Clet-Ortega,Stéphanie Moreaud,Nathalie Furmento,Brice Goglin,Guillaume Mercier,Samuel Thibault,Raymond Namyst +7 more
TL;DR: The Hardware Locality (hwloc) software is introduced which gathers hardware information about processors, caches, memory nodes and more, and exposes it to applications and runtime systems in a abstracted and portable hierarchical manner.
Journal ArticleDOI
ICENI: optimisation of component applications within a Grid environment
TL;DR: Imperial College e-Science Networked Infrastructure (ICENI), a Grid middleware framework developed within the London e- science Centre, is described and the effectiveness of this architecture is demonstrated through the high-level specification and solution of a set of linear equations by automatic and selection of optimal resources and implementations.
Proceedings ArticleDOI
ICENI: An Open Grid Service Architecture Implemented with Jini
TL;DR: The adoption within ICENI of web services to enable interoperability with the recently proposed Open Grid Services Architecture is described.
Journal ArticleDOI
ForestGOMP: An Efficient OpenMP Environment for NUMA Architectures
TL;DR: The runtime, which is based on a multi-level thread scheduler combined with a NUMA-aware memory manager, converts this information into scheduling hints related to thread-memory affinity issues that enable dynamic load distribution guided by application structure and hardware topology, thus helping to achieve performance portability.
Journal ArticleDOI
Achieving High Performance on Supercomputers with a Sequential Task-based Programming Model
Emmanuel Agullo,Olivier Aumage,Mathieu Faverge,Nathalie Furmento,Florent Pruvost,Marc Sergent,Samuel Thibault +6 more
TL;DR: This paper has extended the StarPU runtime system with an advanced inter-node data management layer that supports the sequential task-based programming model, and shows that this paradigm can also be employed to achieve high performance on modern supercomputers composed of multiple such nodes, with extremely limited changes in the user code.