IEEE International Conference on Cluster Computing, Taipei, Taiwan

Abbrevation

Cluster

Link

http://www.ieeecluster2016.org

City

Taipei

Country

Taiwan

Deadline Paper

2016-03-25

Start Date

2016-09-12

End Date

2016-09-16

Abstract

lusters are the primary architecture for building today′s rapidly evolving cloud and HPC infrastructures, and are used to solve some of the most complex problems. The challenge to make them scalable, efficient, and more functional requires a community effort in the areas of cluster system design, management and monitoring, at the hardware, system, middleware and application levels. Following the successes of previous IEEE Cluster conferences, for 2016 we again solicit high–quality original work that advances the state–of–the–art in clusters and closely related fields. All papers will be rigorously peer–reviewed for their originality, technical depth and correctness, potential impact, relevance to the conference, and quality of presentation. Research papers must clearly demonstrate novel research contributions while papers reporting experiences must clearly describe lessons learned and impact, along with the utility of the approach compared to previous ones. Authors must indicate the primary area of preference out of the four areas below. They may optionally rank the other areas. The paper may be accepted as a full paper, or the committee might decide to accept it as a short paper with 4 pages in the proceedings. Area 1: Application, Algorithms, and Libraries * HPC applications on clusters * Performance modeling and measurement * Novel algorithms on clusters * Hybrid programming techniques (e.g., MPI+OpenMP) * Cluster benchmarks * Application–level libraries on clusters * Effective use of clusters in novel applications * Performance evaluation tools Area 2: Architecture, Network/Communications, and Management * Energy–efficient cluster architectures * Node and system architecture * Packaging, power and cooling * GPU/ManyCore and heterogeneous clusters * Interconnect/memory architectures * Single system image clusters * Administration and maintenance tools Area 3: Programming and System Software * Cluster system software/operating systems * Cloud–enabling cluster technologies and virtualization * Energy–efficient middleware * Cluster system–level protocols and APIs * Cluster security * Resource and job management * Programming and software development environments on clusters * Fault tolerance and high–availability Area 4: Data, Storage, and Visualization * Cluster architectures for big data storage and processing * Middleware for big data management * Cluster–based cloud architectures for big data * File systems and I/O libraries * Support and integration of non–volatile memory * Visualization clusters and tiled displays * Big data visualization tools * Programming models for big data processing * Big data application studies on cluster architectures