Category: talk

Talk by Laercio LIMA PILLA (LRI)

On November 4th, Laercio LIME PILLA, CNRS researcher at LRI (Paris) will present us his recent works about load-balancing in distributed environments. The talk will take place in room Grace Hopper 2 at 4pm.   Slides of the talks can be found here: Scalable Scheduling Distributed Algorithms & the Packing Model Seminaire Bordeaux – 2019

Talk by Alexandre Denis (TADaaM) on May 2nd

On May 2nd, Alexandre Denis, INRIA researcher in TADaaM team, will present us his recent works on scalabiily of NewMadeleine Communication library. The talk will take place at 2pm in Room Grace Hopper 2. ——————————————————————————————————————— Title : Scalability of the NewMadeleine Communication Library for Large Numbers of MPI Point-to-Point Requests Abstract : New kinds of …

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Talk by Francieli Zanon Boito (Corse Team, Inria Grenoble/LIG) on January 23rd

January 23rd at 2pm in room Grace Hopper2 (4th floor), Francieli Zanon Boito (post-doc in Corse Team), will present her recent works on data management Title: Data management to promote near-data processing Abstract: Motivated by a case study of instrumental data management at the CEA, this project aims at providing near-data processing (NDP) for tasks …

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Talk by Navjot Kukreja (Imperial College) on June 28th, 2018

High-level abstractions for checkpointing in PDE-constrained optimisation Gradient-based methods for PDE-constrained optimization problems often rely on solving a pair of forward and adjoint equations to calculate the gradient. This requires storing large amounts of intermediate data, limiting the largest problem that might be solved with a given amount of memory. Checkpointing is an approach that …

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Talk by Jan Hückelheim (Imperial College) on June 28th, 2018

Algorithmic differentiation in high-performance computing: challenges and opportunities in optimisation,uncertainty quantification, and machine learning Gradients are useful in countless applications, e.g. gradient-based shape optimisation in structural dynamics, adjoint methods in weather forecasting, or the training of neural networks. Algorithmic differentiation (AD) is a technique to efficiently compute gradients of computer programs, and has undergone decades …

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Talk by Yves Robert on March 12th, 2018

Optimal Cooperative Checkpointing for Shared High-Performance Computing Platforms joint work with Dorian Arnold, George Bosilca, Aurelien Bouteiller, Jack Dongarra, Kurt Ferreira and Thomas Hérault Abstract: In high-performance computing environments, input/output (I/O) from various sources often contend for scarce available bandwidth. Adding to the I/O operations inherent to the failure-free execution of an application, I/O from …

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Talk by Jalil Boukhobza on Feb 27, 2018

Titre: Vers une approche orthogonale pour l’optimisation des (nouveaux) systèmes de stockage Résumé: Aujourd’hui, en une minute, plus de 3 millions de posts sont écrits sur Facebook , plus de 40 000 photos sont déposées sur Instagram, et plus de 120 heures de vidéos sont chargées sur YouTube. Ce ne sont ici que des exemples …

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Talk by Francieli Zanon Boito on Feb 15, 2018

Francieli Zanon Boito (postdoc dans l’équipe Inria Corse à Grenoble) vient nous parler de ses travaux de recherche. Title: I/O scheduling for HPC: finding the right access pattern and mitigating interference Abstract: Scientific applications are executed in a high performance computing (HPC) environment, where a parallel file system (PFS) provides access to a shared storage …

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Talk by Bruno Raffin on Jan 30, 2018

Title: High Performance Data Analysis for Parallel Numerical Simulations. Author: Bruno Raffin, Director of Research, DataMove Team, Inria Grenoble Abstract: Large scale numerical simulations are producing an ever growing amount of data that include the simulation results as well as execution traces and logs. These data represent a double challenge. First, these amounts of data …

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Talk by Amelie Zhou on Jun 15, 2017

Amelie Zhou, postdoc in the Ascola research team will talk about On Achieving Efficient Data Transfer for Graph Processing in Geo-Distributed Datacenters. Graph partitioning, which distributes graph processing workloads to multiple machines for better parallelism, is an important problem for optimizing the performance and communication cost of graph processing jobs. Recently, many graph applications such …

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