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HPCSP 2013 : Workshop on HPC for Scientific Problems


When Sep 23, 2013 - Sep 23, 2013
Where Timisoara
Submission Deadline Jul 31, 2013
Notification Due Aug 19, 2013
Final Version Due Sep 1, 2013
Categories    parallel computing

Call For Papers



Workshop on HPC for scientific problems

September 23-26, 2013, Timisoara, Romania
in conjunction with SYNASC 2013 (


Full paper submissions: 31 July 2013
Notifications: 19 August 2013
Revised papers and registrations: 1 Sept 2013
Event: 23-26 Sept 2013
Publication in IEEE proceedings of SYNASC 2013: Jan 2014
Extended version of selected papers for SCPE: Feb 2014
Notifications: March 2014
Publication of selected papers in SCPE: April 2014

The purpose of this workshop is to present and discuss the state-of-the-art
in high-performance scientific computing with applications and various fields,
like environment, chemistry, physics etc.
Thus, the presentations will focus on applications needing high-performance computing,
physical modeling of large-scale problems, and the development of scalable algorithms
for solving large scale problems on modern parallel
and distributed high-performance computing platforms,
including multicore architectures, GPGPUs/GPUs, and clusters.
Furthermore, during the workshop the participants will have the opportunity
to discuss and share the latest research in parallel and distributed
high performance computing systems applied to scientific problems.
The emphasis of this workshop will be on running complex realistic applications
at sustained performance in production-grade HPC environments.
Scalability studies of complex computing codes on HPC platforms and the tools
and development environments facilitating improved scalability are among the expected contributions.

Specific topics for this workshop include, but are not limited to, the following:

Interactive HPC applications
Multi-Scale / Multi- Physics HPC applications
Exploration of large data sets on HPC systems
Multicore/manycore architectures in scientific applications
GPU support for applications
Cluster, Grid and Cloud Computing in scientific applications
Parallelization of compute or data-intensive tasks in scientific applications
Data handling, integration and visualization in scientific applications
Distributed infrastructures for scientific applications
Programming paradigms for high performance computing in scientific applications
Tools and programming environments supporting high performance computing in scientific applications
Scheduling in high performance computing for scientific applications
Workflow management and remote collaboration in scientific applications
System level support for high performance computing in scientific applications
Fault tolerance of distributed scientific applications
Scalability of infrastructures and applications in scientific applications

Ralf-Peter Mundani – Technische Universität München, Germany

Dana Petcu – West University of Timisoara, Romania

Adrian Jackson- EPCC, UK
Elda Rossi – CINECA, Italy
Jorge Sevilla Cedillo – University of Extremadura, Spain
Emil Slusanschi – University “Politehnica” of Bucharest, Romania
Ioan Lucian Muntean – Technical University of Cluj-Napoca, Romania

Up to 8 pages IEEE CS Format – follow the links from SYNASC Workshops 2013.

Related Resources

PASC 2018   Platform for Advanced Scientific Computing
OPODIS 2018   22nd International Conference on Principles of Distributed Systems
ICPP 2018   International Conference on Parallel Processing
VECPAR 2018   13th International Meeting on High Performance Computing for Computational Science
ISC HPC 2018   ISC High Performance 2018
CANDAR 2018   The Sixth International Symposium on Computing and Networking
EAs for Problems with Uncertainty 2018   Workshop on Evolutionary Algorithms for Problems with Uncertainty
PDAA 2018   10th International Workshop on Parallel and Distributed Algorithms and Applications
SSDBM 2018   30th International Conference on Scientific and Statistical Database Management
LCPC 2018   The 31st International Workshop on Languages and Compilers for Parallel Computing