Page History

...

Main Topics	Schedule	Speaker	Affiliation	Type of presentation	Title (tentative)	Download
	Sunday June 8th
Dinner Before the Workshop	7:30 PM	Only people registered for the dinner (included)			Mercure Hotel

Workshop Day 1	Monday June 9th
					TITLES ARE TEMPORARY (except if in bold font)
Registration	08:00	At Inria Sophia Antipolis
Welcome and Introduction Amphitheatre	08:30	Franck Cappello + Marc Snir + Yves Robert + Bill Kramer + Jesus Labarta	INRIA&UIUC&ANL&BSC	Background	Welcome, Workshop objectives and organization
Plenary Amphitheatre Chair: Franck Cappello	09:00	Jesus Labarta	BSC	Background	Presentation of BSC activities
Mini Workshop Math app. Room 1
Chair: Paul Hovland	09:30	Bill Gropp	UIUC
	10:00	Jed Brown	ANL
	10:30	Break
	11:00	Ian Masliah	Inria		Automatic generation of dense linear system solvers on CPU/GPU architectures
	11:30	Luke Olson	UIUC
	12:00	Lunch
Chair: Bill Gropp	13:30	Vincent Baudoui	Inria
	14:00	Paul Hovland	ANL
	14:30	Stephane Lanteri	Inria		C2S@Exa: a multi-disciplinary initiative for high performance computing in computational sciences
Mini Workshop I/O and BigData Room 1
Chair: Rob Ross	15:00	Wolfgang Frings	JSC
	15:30	Break
	16:00	Jonathan Jenkins	ANL
	16:30	Matthieu Dorier	Inria		Omnisc'IO: A Grammar-Based Approach to Spatial and Temporal I/O Patterns Prediction
	17:00	Kenton Guadron McHenry,	NCSA		The NCSA Image and Spatial Data Analysis Division
	17:30	Adjourn
	18:30	Bus for dinner (dinner included)

Mini Workshop Runtime Room 2
Chair: Sanjay Kale	9:30	Pavan Balaji	ANL
	10:00	Augustin Degomme	Inria		Status Report on the Simulation of MPI Applications with SMPI/SimGrid
	10:30	Break
	11:00	Ronak Buch	UIUC
	11:30	Victor Lopez	BSC
	12:00	Lunch
Chair: Rajeev Thakur	13:30	Xin Zhao	ANL
	14:00	Brice Videau	Inria
	14:30	Pieter Bellens	BSC
	15:00	Martin Quinson	Inria
	15:30	Break
Chair: Jesus Labarta	16:00	Francois Tessier	Inria
	16:30	Jean-François Mehaud	Inria
	17:00	Luka Nussbaum	Inria		Evaluating exascale HPC runtimes through emulation with Distem
	17:30	Adjourn
	18:30	Bus for dinner (dinner included)

Workshop Day 2	Tuesday June 10th

Formal opening Amphitheatre Chair: Bill Kramer	08:30	Marc Snir + Franck Cappello	INRIA&UIUC&ANL	Background
	08:40	Claude Kirchner	Inria	Background	Inria updates and vision of the collaboration	TBD
	08:50	Marc Snir	ANL	Background	ANL updates vision of the collaboration	TBD
Plenary Amphitheatre	09:00	Wolfgan Frings	JSC	Background	JSC activities in HPC	TBD
Mini Workshop I/O and Big Data Room 1
Chair: Gabriel Antoniu	09:30	Rob Ross	ANL		Understanding and Reproducing I/O Workloads
	10:00	Guillaume Aupy	Inria		Scheduling the I/O of HPC applications under congestion
	10:30	Break
	11:00	Lokman Rahmani	Inria
	11:30	Anthony Simonet	Inria		Using Active Data to Provide Smart Data Surveillance to E-Science Users
	12:00	Lunch
Mini Workshop Runtime Room 2
Chair: Jean François Mehaud	09:30	Sanjay Kale	UIUC
	10:00	Florentino Sainz	BSC		DEEP Collective offload
	10:30	Break	Inria
	11:00	Arnaud Legrand	Inria		Modeling and Simulation of a Dynamic Task-Based Runtime System for Heterogeneous Multi-Core Architectures
	11:30	Grigori Fursin	Inria
	12:00	Lunch
Formal encouragments Amphitheatre Chair: Franck Cappello	13:45	Ed Seidel	UIUC	Background	NCSA updates and vision of the collaboration
Plenary Amphitheatre Chair: Wolfgan Frings	14:00	Yves Robert	Inria
	14:30	Marc Snir	ANL
	15:00	Break
Mini Workshop Resilience Room 1
Chair: Franck Cappello	15:30	Luc Jaulmes	BSC		Checkpointless exact recovery techniques for Krylov-based iterative methods
	16:00	Ana Gainaru	UIUC
	16:30	Tatiana Martsinkevich	Inria
	17:00	Adjourn
Mini Workshop Cloud & Cyber-infrastructure Room 2
Chair: Kate Keahey	15:30	Justin Wozniak	ANL
	16:00	Shaowen Wang	UIUC		CyberGIS @ Scale
	16:30	Christine Morin	Inria
	17:00	Adjourn
	18:30	Bus for Dinner (dinner included)

Workshop Day 3	Wednesday June 11th
Plenary Amphitheatre Chair: Jesus Labarta	8:30	Bill Kramer	NCSA		Blue Waters - A year of results and insights
Mini Workshop Resilience Room 1
Chair: Yves Robert	9:00	Leonardo Bautista Gomez	ANL
	9:30	Slim Bougera	Inria
	10:00	Break
	10:30	Sheng Di	ANL		Round-off error propagation in large-scale applications
	11:00	Vincent Baudoui	ANL		Five open questions on Resilience for the Exascale era
Plenary Amphitheatre	11:30	Closing
	12:00	Lunch (included)
Mini Workshop Cloud & Cyber-infrastructure Room 2
Chair: Christine Morin	09:00	Kate Keahey	ANL
	09:30	Radu Tudoran	Inria		JetStream: Enabling High Performance Event Streaming across Cloud Data-Centers
	10:00	Break
	10:30	Sri Hari Krishna Narayanan	ANL
	11:00	Timothy Armstrong	ANL
Plenary Amphitheatre	11:30	Closing
	12:00	Lunch (included)

...

Vincent Baudoui

Round-off error propagation in large-scale applications

Round-off errors coming from numerical calculation finite precision can lead to catastrophic losses in significant numbers when they accumulate. They will become more and more overriding in the future as the problem size increases with the refinement of numerical simulations. Existing analytical bounds for round-off errors are known to be poorly scalable and they become quite useless for large problems. That is why the propagation of round-off errors throughout a computation needs to be better understood in order to ensure large-scale application results accuracy. We study here a round-off error estimation method based on first order derivatives computed thanks to algorithmic differentiation techniques. It can help following the error propagation through a computational graph and identifying the sensitive sections of a code. It has been experimented on well known LU decomposition algorithms that are widely used to solve linear systems. We will present some examples as well as challenges that need to be tackled as part of future research work in order to set up a strategy to analyze round-off error propagation in large-scale problems.

Luc Jaulmes

Checkpointless exact recovery techniques for Krylov-based iterative methods

By exploiting inherent redundancy in iterative solvers, especially Krylov-subspace methods, we can recover from non-silent errors in data without reverting to techniques like checkpointing. We implemented this recovery scheme for the Conjugate Gradient (CG) and its Preconditioned variant (PCG) and show near-zero overheads without faults, and fast recoveries that preserve all convergence properties of the solver. Using the asynchronous task-based programming model OmpSs, these overheads are even further minimized.

Lokman Rahmani

Smart In Situ Visualization for Climate Simulations

The increasing gap between computational power and I/O performance in new supercomputers has started to drive a shift from an offline approach to data analysis to an inline approach, termed in situ visualization (ISV). While most visualization software now provides ISV, they typically visualize large dumps of unstructured data, by rendering everything at the highest possible resolution. This often negatively impacts the performance of simulations that support ISV, in particular when ISV is performed interactively, as in situ visualization requires synchronization with the simulation. In this work, we advocate for a smarter method of performing ISV. Our approach is data-driven: it aims to detect potentially interesting regions in the generated dataset in order to feed ISV frameworks with “the interesting” subset of the data produced by the simulation. While this method mitigates the load on ISV frameworks by making them more efficient and more interactive, it also helps scientists focus on the relevant part of their data. We investigate smart ISV in the context of a climate simulation, with a set of generic filters derived from information theory, statistics and image processing, and show the tradeoff between performance and quality of visualization.

Lucas Nussbaum

Evaluating exascale HPC runtimes through emulation with Distem

The Exascale era will require the HPC software stack to face important challenges such as platform hetereogeneity and evolution during execution, or reliability issues. We propose a framework to evaluate key aspects of a central part of this software stack: the HPC runtimes. Starting from Distem, which is a versatile emulator for studying distributed systems, we designed an emulator suitable for the evaluation of HPC runtimes, enabling specifically: (1) emulation of a very large scale platform on top of a regular cluster; (2) introduction of heterogeneity and dynamic imbalance among the computing resources; (3) introduction of failures. Those features provide runtime designers with the ability to experiment their prototypes under a large range of conditions, to discover performance gaps, understand future bottlenecks, and evaluate fault tolerance and load balancing mechanisms. We validate the usefulness of this approach with experiments on two HPC runtimes: Charm++ and OpenMPI.

Child pages

Versions Compared

Old Version 40

New Version 41

Key

TITLES ARE TEMPORARY (except if in bold font)