Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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Materials Map under construction

The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (5/5 displayed)

  • 2020Pufferscale: Rescaling HPC Data Services for High Energy Physics Applications5citations
  • 2020How fast can one resize a distributed file system?1citations
  • 2018Pufferbench: Evaluating and Optimizing Malleability of Distributed Storage3citations
  • 2018A Lower Bound for the Commission Times in Replication-Based Distributed Storage Systemscitations
  • 2017How Fast Can One Scale Down a Distributed File System?3citations

Places of action

Chart of shared publication
Ross, Robert
1 / 2 shared
Wild, Stefan M.
1 / 1 shared
Leyffer, Sven
1 / 1 shared
Dorier, Matthieu
4 / 4 shared
Cheriere, Nathanaël
3 / 4 shared
Chart of publication period
2020
2018
2017

Co-Authors (by relevance)

  • Ross, Robert
  • Wild, Stefan M.
  • Leyffer, Sven
  • Dorier, Matthieu
  • Cheriere, Nathanaël
OrganizationsLocationPeople

article

How fast can one resize a distributed file system?

  • Dorier, Matthieu
  • Antoniu, Gabriel
Abstract

Efficient resource utilization becomes a major concern as large-scale distributed computing infrastructures keep growing in size. Malleability, the possibility for resource managers to dynamically increase or decrease the amount of resources allocated to a job, is a promising way to save energy and costs.However, state-of-the-art parallel and distributed storage systems have not been designed with malleability in mind. The reason is mainly the supposedly high cost of data transfers required by resizing operations. Nevertheless, as network and storage technologies evolve, old assumptions about potential bottlenecks can be revisited.In this study, we evaluate the viability of malleability as a design principle for a distributed storage system. We specifically model the minimal duration of the commission and decommission operations. To show how our models can be used in practice, we evaluate the performance of these operations in HDFS, a relevant state-of-the-art distributed file system. We show that the existing decommission mechanism of HDFS is good when the network is the bottleneck, but can be accelerated by up to a factor 3 when storage is the limiting factor. We also show that the commission in HDFS can be substantially accelerated. With the highlights provided by our model, we suggest improvements to speed both operations in HDFS. We discuss how the proposed models can be generalized for distributed file systems with different assumptions and what perspectives are open for the design of efficient malleable distributed file systems.

Topics
  • impedance spectroscopy