[hpc-announce] CFP: 29th HCW Workshop; collocated with IPDPS 2020

[Mohsen Amini]

*Call for Papers*
In conjunction with IPDPS 2020, May 18 2020, New Orleans, Louisiana USA

Sponsored by the IEEE Computer Society through the Technical Committee on
Parallel Processing (TCPP)


*SUMMARY*Most modern computing systems are heterogeneous, either for
organic reasons because components grew independently, as it is the case in
desktop grids, or by design to leverage the strength of specific hardware,
as it is the case in accelerated systems. In any case, all computing
systems have some form of hardware or software heterogeneity that must been
managed, leveraged, understood, and exploited. HCW is a venue to discuss
and innovate in all theoretical and practical aspects of heterogeneous
computing: design, programmability, efficient utilization, algorithms,
modeling, applications, etc. The 2020 HCW is the 29th annual gathering of
this workshop.

*TOPICS*
Topics of interest include but are not limited to the following areas:

!!! NEW SPECIAL TOPIC !!! Domain specific architectures (DSAs): Design,
programming, and exploration of domain specific computing architectures,
i.e., heterogeneous computing architectures that provide a significant
performance improvement for a specific application domain, such as  AI,
image processing, and audio processing. Well known examples are Google’s
TPU, Microsoft’s Catapult, and Intel’s Movidius.  Submissions in the
following areas are very welcome: Designing and programming of domain
specific computing architectures (e.g., ASIPs, DSPs, GPUs, FPGAs, or TPUs),
exploration and benchmarking of domain specific computing architectures.

Heterogeneous multicore systems and architectures: Design, exploration, and
experimental analysis of heterogeneous computing systems such as GPGPUs,
heterogeneous systems-on-chip (SoC), accelerator systems (e.g., Intel Xeon
Phi, AI chips such as Google’s TPUs), FPGAs, big.LITTLE, and
application-specific architectures.

Heterogeneous parallel and distributed systems: Design and analysis of
computing grids, cloud systems, hybrid clusters, datacenters,
geo-distributed computing systems, and supercomputers.

Deep-memory hierarchies: Design and analysis of memory hierarchies with
SRAM, DRAM, Flash/SSD, and HDD technologies; NUMA architectures; cache
coherence strategies; novel memory systems such as phase-change RAM,
magnetic (e.g., STT) RAM, 3D Xpoint/crossbars, and memristors.

On-chip, off-chip and heterogeneous network architectures: Network-on-chip
(NoC) architectures and protocols for heterogeneous multicore applications;
energy, latency, reliability, and security optimizations for NoCs; off-chip
(chip-to-chip) network architectures and optimizations; heterogeneous
networks (combination of NoC and off-chip) design, evaluation, and
optimizations; large scale parallel and distributed heterogeneous network
design, evaluation, and optimizations.

Programming models and tools: Programming paradigms and tools for
heterogeneous systems; middleware and runtime systems;
performance-abstraction tradeoff; interoperability of heterogeneous
software environments; workflows; dataflows.

Resource management and algorithms for heterogeneous systems: Parallel
algorithms for solving problems on heterogeneous systems (e.g., multicores,
hybrid clusters, grids or clouds); strategies for scheduling and allocation
on heterogeneous 2D and 3D multicore architectures; static and dynamic
scheduling and resource management for large-scale and parallel
heterogeneous systems.

Modeling, characterization, and optimizations: Performance models and their
use in the design of parallel and distributed algorithms for heterogeneous
platforms, characterizations and optimizations for improving the time to
solve a problem (e.g., throughput, latency, runtime), modeling and
optimizing electric consumption (e.g., power, energy); modeling for failure
management (e.g., fault tolerance, recovery, reliability); modeling for
security in heterogeneous platforms.

Applications on heterogeneous systems: Case studies; confluence of Big Data
systems and heterogeneous systems; data-intensive computing; deep learning;
scientific computing.


*IMPORTANT DATES*Paper submission: January 27, 2020
Author notification: March 2, 2020
Camera Ready: March 17, 2020

PAPER SUBMISSIONS
Papers are to be submitted through Linklings. Papers submitted to HCW 2020
should not have been previously published or be under review for a
different workshop, conference, or journal. It is also required that all
accepted papers will be presented at the workshop by one of the authors.


*WORKSHOP ORGANIZATION*
General Chair: John Antonio, University of Oklahoma, USA
Program Chair: Florina M. Ciorba, University of Basel, Switzerland (TPC
Chair)
Special Topic Session Chair: Diana Göhringer (Technische Universität
Dresden, Germany)
Publicity Chair: Mohsen Amini (University of Louisiana Lafayette, USA)


*Steering Committee:*Behrooz Shirazi, Washington State University, USA
(Chair)
H. J. Siegel, Colorado State University, USA (Past Chair)
John Antonio, University of Oklahoma, USA
David Bader, Georgia Tech, USA
Anne Benoit, École Normale Supérieure de Lyon, France
Jack Dongarra, University of Tennessee, USA
Alexey Lastovetsky, University College Dublin, UK
Sudeep Pasricha, Colorado State University, USA
Viktor K. Prasanna, University of Southern California, USA
Yves Robert, École Normale Supérieure de Lyon, France
Erik Saule, University of North Carolina at Charlotte, USA
Uwe Schwiegelshohn, TU Dortmund University, Germany


*Technical Program Committee:*Florina M. Ciorba, University of Basel,
Switzerland (TPC Chair)
Mohsen Amini, University of Louisiana Lafayette, USA
Ioana Banicescu, Mississippi State University, USA
Sunita Chandrasekaran, University of Delaware, USA
Louis-Claude Canon, Université de Franche-Comté, France
Daniel Cordeiro, University of São Paulo, Brazil
Matthias Diener, University of Illinois at Urbana-Champaign, USA
Ryan Friese, Pacific Northwest National Laboratory, USA
Diana Göhringer, Technische Universität Dresden, Germany
Nicolas Grounds, MSCI, Inc., USA
Krishna Kavi, University of North Texas, USA
Jong-Kook Kim, Korea University, Korea
Alexey Lastovetsky, University College Dublin, Ireland
Hatem Ltaief, KAUST, Saudi Arabia
Mahdi Nikdast, Colorado State University, USA
Dana Petcu, West University of Timisoara, Romania
Laercio Lima Pilla, CNRS, France
Sridhar Radhakrishnan, University of Oklahoma, USA
Srishti Srivastava, University of Southern Indiana, USA
Achim Streit, Karlsruhe Institute of Technology, Germany
Samuel Thibault, LaBRI, Université Bordeaux, France
Devesh Tiwari, Northeastern University, USA