NPC: Network and Parallel Computing

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Past:   Proceedings on DBLP

Future:  Post a CFP for 2018 or later   |   Invite the Organizers Email

 
 

All CFPs on WikiCFP

Event When Where Deadline
NPC 2017 Network and Parallel Computing
Oct 20, 2017 - Oct 21, 2017 Hefei, China Jun 10, 2017
NPC 2016 Network and Parallel Computing
Oct 28, 2016 - Oct 29, 2016 Xian, China Jun 18, 2016
NPC 2015 12th IFIP International Conference on Network and Parallel Computing
Sep 17, 2015 - Sep 19, 2015 New York Mar 30, 2015
NPC 2014 The 11th IFIP International Conference on Network and Parallel Computing
Sep 18, 2014 - Sep 20, 2014 Ilan, Taiwan Apr 10, 2014
NPC 2013 The 10th IFIP International Conference on Network and Parallel Computing
Sep 19, 2013 - Sep 21, 2013 Guiyang China Apr 2, 2013
NPC 2011 the 8th IFIP International Conference on Network and Parallel Computing
Oct 21, 2011 - Oct 23, 2011 Changsha, Hunan, China Apr 28, 2011 (Mar 18, 2011)
NPC 2010 7th IFIP International Conference on Network and Parallel Computing
Sep 13, 2010 - Sep 15, 2010 Zhengzhou, China Apr 7, 2010
NPC 2009 IFIP International Conference on Network and Parallel Computing
Oct 19, 2009 - Oct 21, 2009 Gold Coast, Australia May 24, 2009
 
 

Present CFP : 2017

*****************************************************************************
CALL FOR PAPERS
NPC 2017

The 14th IFIP International Conference on Network and Parallel Computing
October 20th-21st 2017, Hefei, China
http://npc-china2017.org/
*****************************************************************************

IMPORTANT DATES
Paper Submissions Due: June 10th, 2017
Results notification: July 24th, 2017
Camera-ready version due: August 7th, 2017

High Performance Computing and Big Data are two main areas where NPC
2017 will provide a dynamic forum to explore, discuss and debate
state-of-the-art technology issues and challenges. High-performance
computers and big-data systems are tied inextricably to the broader
computing ecosystem and its designs and market adoption. They also
highlight information security needs and economic competitiveness in
ways that distinguish them from most other scientific instruments. We
strongly believe that the stake is high, and it is far beyond the
boundaries of nations and continents, and should strongly encourage a
broad international participation.

We share the view that, during the past decade, the tools and cultures
of high-performance computing and big data analytics are diverging to
the detriment of both, and the international community should find a
unified path that can best serve the need of a broad spectrum of major
application areas. Unlike other tools, which are limited to particular
scientific domains, computational modeling and data analytics are
applicable to all areas of science and engineering, as they breathe
life into the underlying mathematics of scientific models.

Parallel and distributed applications and algorithms:
* Parallel and distributed issues and opportunities on artificial
intelligence application.
* Parallel algorithms for computational and data-enabled scientific,
engineering, biological and medical applications
* Parallel algorithms for accelerators, neuromorphic architectures,
and other emerging architectures
* Parallel and distributed architectures and systems

Emerging architectures and systems at all scales, from embedded to cloud:
* Systems for enabling parallelism at an extreme scale
* Power-efficient and green computing systems
* Neuromorphic architectures and cognitive computing accelerators
* Heterogeneous multicore architectures and accelerators
* In-Memory and near-data computing
* Network and interconnect architectures
* Storage systems in novel big data architectures
* Parallel and distributed software environments and tools

Programming models and compilation for existing and emerging platforms:
* Dataflow programming models, frameworks, languages and environments for
data-enabled platforms
* Virtualization of machines, networks, and storage
* I/O, file systems, and data management
* Resource management, scheduling, and load balancing

NPC is in its 14th year and previous conferences have attracted high
quality papers and wide international participation.

Top ranked, reviewed papers in NPC 2017 will be published directly (without
further extension) by the International Journal of Parallel Programming (SCI
indexed). To qualify for publication in IJPP, all submissions must meet the
paper length and other requirements of IJPP. More information can be found:
http://www.springer.com/computer/theoretical+computer+science/journal/10766.
Other accepted papers will be published in the conference proceedings, by
LNCS, Springer (EI, Scopus).


ORGANIZING COMMITTEE
GENERAL CO-CHAIRS
Michael Gschwind, IBM, USA
Weisong Shi, Wayne State University, USA

ORGNIZATION CHAIR
Guohua Cheng, Hangzhou Jianpei Techlogy Co.,Ltd China

PROGRAM CO-CHAIRS
Hong An, University of Science and Technology of China, China
Mahmut Kandemir, Pennsylvania State University, USA

PUBLICATIONS CHAIR
Xuanhua Shi, Huazhong Univ. of Science & Technology, China

LOCAL ARRANGEMENTS CHAIRS
Yu Zhang, University of Science and Technology of China, China

PUBLICITY CO-CHAIRS
Yong Chen,Texas Tech University, USA
Guangzhong Sun, University of Science and Technology of China, China
Keiji Kimura, Waseda University
Stephane Zuckerman, Michigan Technological University

REGISTRATION CHAIR
Chao Wang, University of Science and Technology of China, China

WEB CHAIR
Hui Sun, Anhui University, China

STEERING COMMITTEE
Kemal Ebcioglu, Global Supercomputing USA (Chair)
Hai Jin, Huazhong Univ. of Science & Technology, China
Chen Ding, University of Rochester, USA
Jack Dongarra, Univ of Tennessee, USA
Guangrong Gao, Univ of Delaware, USA
Daniel Reed, University of Iowa, USA
Zhiwei Xu, Institute of Computing Technology, China
Yoichi Muraoka, Waseda University, Japan
Jean-Luc Gaudiot, University of California Irvine, USA
Guojie Li, Institute of Computing Technology, China
Ninghui Sun, Institute of Computing Technology, China
Viktor Prasanna, University of Southern California, USA
Weisong Shi, Wayne State University, USA
Tony Hey, Microsoft, USA
 

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