International Workshop on High
Performance Data Intensive Computing
(HPDIC'2015)
|
In Conjunction with IEEE
IPDPS 2015, 29th IEEE International Parallel &
Distributed Processing Symposium, May 25-29 2015,
International Convention Centre, Hyderabad,
INDIA.
Important dates
- Workshop Paper Due: January
15th, 2015
- Author Notification: February 22th, 2015
- Camera-ready Paper Due: Feb 28th,
2015
Highlight of the 2015 edition
In cooperation with
the PREDON
group, we open the workshop topics to Data Preservation.
NEW:
a special issue for best papers is planned in cooperation with the
following
journals:
IJCSE or
IJHPCN. More
information will come soon.
If you participated in the
2014 workshop as a speaker or listener, please find some
photos HERE.
Past editions: HPDIC'2014,
HPDIC'2013,
HPDIC'2012
Acceptation rate:
HPDIC 2012 (Shanghai): 29/72=40.3%
HPDIC 2013 (Boston):20/46=43.4%
HPDIC 2014 (Phoenix): 7/15=46.7%
HPDIC 2015 (Hyderabad): 3/8=37.5%
Selected papers and program
The workshop day is Monday 25 and we are merging with HPBC
The following papers have been accepted:
- (HPDIC-04) Wes Bethel, David Camp, David Donofrio and Mark
Howison. Improving Performance of Structured-memory,
Data-Intensive Applications on Multi-core Platforms via a
Space-Filling Curve Memory Layout
- (HPDIC-05) Trupti Padiya, Minal Bhise and Bhavik Shah. Query
Execution for RDF Data using Structure Indexed Vertical
Partitioning
- (HPDIC-08) Medha Shah and Prof. Dr. D.B. Kulkarni. Storm
Pub-Sub: High Performance, Scalable Content Based Event
Matching System Using Storm
Description
There is no doubt in the industry and research community that the
importance of data intensive computing has been raising and will
continue to be the foremost fields of research. This raise brings up
many research issues, in forms of capturing and accessing data
effectively and fast, processing it while still achieving high
performance and high throughput, and storing it efficiently for future
use.
In a widely distributed environment, data is often not locally
accessible and has thus to be remotely retrieved and stored. While
traditional distributed systems work well for computation that requires
limited data handling, they may fail in unexpected ways when the
computation accesses, creates, and moves large amounts of data
especially over wide-area networks. Further, data accessed and created
is often poorly described, lacking both metadata and provenance.
Scientists, researchers, and application developers are often forced to
solve basic data-handling issues, such as physically locating data, how
to access it, and/or how to move it to visualization and/or compute
resources for further analysis.
This year, we open new directions related to the preservation
of data in cooperation with
the
PREDON
group. The preservation of scientific data remains
nevertheless a challenge due to the complexity of the data
structure, the fragility of the custom-made software
environments as well as the lack of rigorous approaches in
workflows and algorithms.
This workshop focuses on the challenges imposed by high performance
data-intensive applications on distributed systems, and on the different
state-of-the-art solutions proposed to overcome these challenges. It
brought together the collaborative and distributed computing community
and the data management community in an effort to generate productive
conversations on the planning, management, and scheduling of data
handling tasks and data storage resources.
After the success of HPDIC 2012, 2013 and 2014, the 2015 edition
(HPDIC2015) is a forum for professionals involved in data
intensive computing and high performance computing. The goal
of this workshop is to bridge the gap between theory and
practice in the field of high performance data intensive
computing and bring together researchers and practitioners
from academia and industry working on high performance data
intensive computing technologies. We believe that high
performance data intensive computing will benefit from close
interaction between researchers and industry practitioners, so
that the research can inform current deployments and
deployment challenges can inform new research. In support of
this, HPDIC2015 will provide a forum for both academics and
industry practitioners to share their ideas and experiences,
discuss challenges and recent advances, introduce developments
and tools, identify open issues, present applications and
enhancements for data intensive computing systems and report
state-of-the-art and in-progress research, leverage each
other's perspectives, and identify new/emerging trends in this
important area.
We therefore cordially invite contributions that investigate
these issues, introduce new execution environments, apply
performance evaluations and show the applicability to science
and enterprise applications. We welcome various different
kinds of papers that could formalize, simplify and optimize
all the aspects of existing data intensive applications in
science, engineering and business. We particularly encourage
the submission of position papers that describe novel research
directions and work that is in its formative stages, and
papers about practical experiences and lessons learned from
production systems.
Papers of applied research, industrial experience reports,
work-in-progress and vision papers with different criteria for
each category that describe recent advances and efforts in the
design and development of data intensive computing,
functionalities and capabilities that will benefit many
applications are also solicited.
We believe that our
workshop should act as a cross-fertilization of the opinions of
very different communities.
List of topics
Topics of interests include, but are not limited to:
- Architectural aspects:
- Data Clouds, Data Grids, and Data Centers;
- High performance data transfer and ingestion;
- Security and protection of sensitive data in collaborative
environments;
- Storage and file systems; From disks to NVRAM supports;
- NoSQL data store;
- Networking support for data-intensive computing;
- Software and middleware:
- Data-aware toolkits and middleware;
- Service oriented architectures for data-intensive computing;
- Accountability, QoS, and SLAs;
- Performance measurement, analytic modeling, simulation;
- Data capturing, management, and scheduling techniques;
- Applications:
- Data-intensive applications and their challenges;
- Data intensive computing in science, commerce,
entertainment and medicine
- Capturing scalability, reliability and availability;
- Data-intensive scientific discovery;
- Machine Learning, new paradigms:
- Algorithms for Big Data;
- Remote and distributed visualization of large scale data;
- Programming models, abstractions for data intensive computing (large-scale MapReduce, Spark...)
- Distributed Ensemble Classifier;
- Preservation:
- Scientific data-sets analysis;
- Data archives, digital libraries, and preservation;
- Algorithms and Workflows suited for data and workflow
preservation;
- Data- and process-based workflows and mining techniques
to be used in a multi-disciplinary environment towards long
term data preservation
- Data formats and interfaces to serve scientific communities;
Submission Instructions
Please submit full papers in PDF or doc format via the submission
system. Do not email submissions. Papers must be written in English.
The complete submission must be no longer than ten (10) pages. It should
be typeset in two-column format in 10 point type on 12 point
(single-spaced) leading. References should not be set in a smaller font.
Submissions that violate any of these restrictions may not be reviewed.
The limits will be interpreted fairly strictly, and no extensions will
be given for reformatting. Final author manuscripts will be 8.5" x 11"
(two columns IEEE format), not exceeding 10 pages; max 2 extra pages
allowed at additional cost.
The names of authors and their affiliations should be included on the
first page of the submission.
Simultaneous submission of the same work to multiple venues, submission
of previously published work, or plagiarism constitutes dishonesty or
fraud.
Reviewing of full papers will be done by the program committee, assisted
by outside referees. Accepted papers will be shepherded through an
editorial review process by a member of the program committee.
By submitting a paper, you agree that at least one of the authors will
attend the workshop to present it. Otherwise, the paper will be excluded
from the digital library of IEEE.
Please submit papers via EasyChair
for HPDIC2015 (in case of problems, please send
emails to the workshop chairs)
General Chairs
- Christophe Cérin, Professor, University of Paris XIII, France
E-mail: christophe.cerin@lipn.univ-paris13.fr
- R.K. Shyamasundar, Tata Institute of Fundamental Research, India
E-mail: shyam[AT]tcs.tifr.res.in
Program Chairs
- Yuqing Gao, IEEE Fellow, IBM T. J. Watson Research, USA
E-mail: yuqing@us.ibm.com
- Cong-Feng Jiang, PhD, Hangzhou Dianzi University, China
E-mail: cjiang@hdu.edu.cn
Program Committee Members (to be confirmed)
- Walter Binder, University of Lugano, Switzerland
- Guoray Cai, Pennsylvania State University, USA
- Jiannong Cao, Hong Kong Polytechnic University, Hong Kong
- Amit Dvir, Budapest University of Technology and Economics, Hungary
- Daniel Chateigner, CRISMAT, ENSI Caen, France
- Gilles Fedak,INRIA Rhone-Alpes, Lyon, France
- Vatche Ishakian, Boston University, USA
- Woosung Jung, Chungbuk National University, Korea
- Mustapha Lebbah, Paris University XIII, France
- Chunlei Liu, Valdosta State University, USA
- Audun Nordal, University of Tromsoe, Norway
- Kumiko Tadano,NEC Corporation,Japan
- Hong-Linh Truong, Vienna University of Technology, Austria
- Xiaofei Zhang, Hong Kong University of Science and Technology, Hong
Kong
- Brian Vinter , Copenhagen University, Denmark
- Naixue Xiong, Colorado Technical University
- Bin Xiao, Hong Kong Polytechnic University, Hong Kong
- Jue Wang, supercomputing center of CAS, China
- Tingwei Chen, Liaoning University, China
- Hui Ma, Victoria University of Wellington, New Zealand
- Dr. Qing Liu, ICT Centre, CSIRO, Australia
- Cristinel Diaconu, IN2P3/CNRS, France
- Luis Veiga, Technical University of Lisbon, Portugal>/li>
- Qiang Guan, Ph.D., Ultra-scale System Research Center, Los Alamos National Laboratory, USA
- Fang Zheng, IBM Watson, USA