[hpc-announce] [CFP] 8th international workshop on data flow models for extreme-scale computing

Stéphane Zuckerman stephane.zuckerman at u-cergy.fr
Sun Apr 7 08:50:18 CDT 2019


		8th IEEE International Workshop
	on Data Flow Models and Extreme-Scale Computing (DFM 2019)

This workshop is organized as part of the activities of the IEEE
Computer Society Dataflow STC.

	The eighth installment of the international workshop on Data Flow
Models (DFM) for extreme-scale computing is held this year in
conjunction with the COMPSAC conference. The purpose of DFM continues to
being to bring together those researchers interested in novel
computational models based on dataflow principles of execution. The
switch to multi-core systems, at both the high-performance and embedded
levels, has raised concurrency to the level of a major issue, with the
trend of increasing the core count on a chip continuing, as well as
energy and resiliency issues coming to the fore of major issues to tackle.

	Computer systems, both for high-performance and embedded computing,
have now fully embraced parallelism at the hardware and software levels.
>From the HPC systems viewpoint, new challenges have arisen, which are
common issues in the embedded world: power and energy efficiency are now
major issues to be overcome when considering building efficient
supercomputers. Conversely, harnessing true parallel systems is now
necessary to efficiently exploit embedded systems equipped with multiple
cores. Moreover, fault-tolerance and resiliency must also be taken into
consideration, at both the hardware and software level. Finally, many
such systems (both embedded and HPC) are networked together, forming
extremely large distributed and parallel systems. Dataflow-inspired
models of computation, once discarded by the sequential programming
crowd, are again considered serious contenders to help increase
programmability, performance, and scalability in highly parallel and
extreme scale systems. By their very nature, dataflow and event-driven
inspired models tend to naturally solve (if only partially) some of the
newer problems related to power and energy efficiency, or provide
fertile ground to help with implementing efficient fault-tolerance and
resiliency mechanisms, as many of the required properties are enmeshed
in the models themselves. Yet, to achieve high scalability and
performance, modern computing systems, both HPC and embedded, rely on
heterogeneous means to carry out computations: GPUs, FPGAs, etc.
Meanwhile, legacy programming and execution models, such as MPI and
OpenMP, add asynchronous and data-driven constructs to their models, all
the while trying to take into account the very complex hardware targeted
by parallel applications. Consequently, programming and execution
models, trying to combine both legacy control flow-based and data
flow-based aspects of computing, have also become increasingly complex
to handle. Developing new models and their implementation, from the
application programmer level, to the system level, down to the hardware
level is key to provide better data- and event-driven systems which can
efficiently exploit the wealth of diversity that composes current
high-performance systems, for extreme scale parallel computing. To this
end, the whole stack, from the application programming interface down to
the hardware must be investigated for programmability, performance,
scalability, energy and power efficiency, as well as resiliency and
fault-tolerance. All these aspects may have a different impact on
high-performance computing and embedded systems.

	Researchers and practitioners all over the world, from both academia
and industry, working in the areas of language, system software, and
hardware design, parallel computing, execution models, and resiliency
modeling are invited to discuss state of the art solutions, novel
issues, recent developments, applications, methodologies, techniques,
experience reports, and tools for the development and use of data flow
models of computation. Topics of interest include, but are not limited
to, the following:

DFM 2019 solicits novel papers that include but are not limited to:
•	Programming languages and compilers for existing and new languages —
in particular single-assigned and functional languages
•	System software: Operating systems, runtime systems
•	Hardware design: ASICs and reconfigurable computing (FPGAs)
•	Resiliency and fault-tolerance for parallel and distributed systems
•	New data flow inspired execution models — in particular strict and
non-strict models
•	Hybrid system design for control-flow and data-flow based systems
•	Position papers on the future of data flow in the era of parallel and
distributed many-core systems, and beyond, including heterogeneous systems

SUBMISSION INFORMATION
DFM 2019 will accept both full (6 pages) and short papers (4 pages).
Full page papers may go up to 8 pages for a fee. Papers should be
prepared using the IEEE Proceedings format; Short Papers could be
submitted in the form of extended abstracts. All accepted papers will
appear in the Computer Society Digital Library. Submission site
https://easychair.org/my/conference.cgi?welcome=1;conf=compsac2019.

IMPORTANT DATES

Submission deadline: 	May 1st, 2019, AOE
Authors notification:	May 15th, 2019
Camera ready due:	June 1st, 2019


PROGRAM COMMITTEE:

Stéphane Zuckerman, Chair, Univ. of Cergy-Pontoise
Skevos Evripidou, University of Cyprus
Guang Gao, University of Delaware
Jean-Luc Gaudiot, University of California at Irvine
Vivek Sarkar, Rice University
Ian Watson, University of Manchester
Kei Hiraki, University of Tokyo
David Abramson, Monash University
Costas Kyriacou, Frederic University
Kyriacos Stavrou, Intel Labs Barcelona, SP
John Feo, Pacific Northwest National Laboratory
Bob Iannucci, CMU, Silicon Valley, USA
Wallid Najjar, University of California, Riverside
Wolfgang Karl, Karlsruhe Institute of Technology
Mark Oskin, University of Washington
Andrew Sohn, NJIT, USA
Reiner Hartenstein, TU Kaiserslautern
Kevin Hammond, University of St Andrews
Roberto Giorgi, University of Sienna
Robert Clay, Sandia National Labs
Sven-Bodo Scholz, Heriot-Watt University
Krisha Kavi, Univerity Of North Texas
Yong Meng Teo, National Univ. of Singapore



-- 
Maître de Conférences / IUT GEII (site de Neuville)
Laboratoire ETIS — Université Paris-Seine
UMR 8051, Université de Cergy-Pontoise, ENSEA, CNRS
F-95000, Cergy, France



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