Workshop 23rd September 2013 9 a.m. Timisoara, Romania
Workshop on HPC for Scientific Problems
- Web page
- http://host.hpc.uvt.ro/events/hpcsp/
- Categories
- Computer Science, Condor, e-Research, Emerald, GPU, HECToR, HPC, HPCx, Iridis, Jaguar, Lyceum, Monte Carlo, Multi-core, Multi-scale, NGS, Optimisation, Scientific Computing, Software Engineering, Spitfire, Visualisation
- Submitter
- Jess Jones
in conjunction with SYNASC 2013
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.
Topics:
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