[hpc-announce] HPBDC 2019 Call for Papers

[Xiaoyi Lu]

==============================================================

                          The 5th IEEE International Workshop on 
             High-Performance Big Data and Cloud Computing (HPBDC)
                     http://web.cse.ohio-state.edu/~luxi/hpbdc2019

                                In conjunction with the 33rd IEEE
 International Parallel and Distributed Processing Symposium (IPDPS 2019)

                    Rio de Janeiro, Brazil, Monday, May 20th, 2019

==============================================================


WORKSHOP DESCRIPTION 
---------------------------------------

Managing and processing large volumes of data, or Big Data, and gaining
meaningful insights is a significant challenge facing the parallel and
distributed computing community. This has significant impact in a wide range of
domains including health care, bio-medical research, Internet search, finance
and business informatics, and scientific computing. As data-gathering
technologies and data sources witness an explosion in the amount of input data,
it is expected that in the future massive quantities of data in the order of
hundreds or thousands of petabytes will need to be processed. Thus, it is
critical that data-intensive computing middleware (such as Hadoop, Spark,
Flink, etc.) to process such data are diligently designed, with high
performance and scalability, in order to meet the growing demands of such Big
Data applications.

The explosive growth of Big Data has caused many industrial firms to adopt High
Performance Computing (HPC) technologies to meet the requirements of huge
amount of data to be processed and stored. The convergence of HPC, Big Data,
and Deep Learning is becoming the next game-changing business opportunity.
Apache Hadoop, Spark, gRPC/TensorFlow, and Memcached are becoming standard
building blocks in handling Big Data oriented processing and mining.

Modern HPC bare-metal systems and Cloud Computing platforms have been fueled
with the advances in multi-/many-core architectures, RDMA-enabled networking,
NVRAMs, and NVMe-SSDs during the last decade. However, Big Data and Deep
Learning middleware (such as Hadoop, Spark, Flink, and gRPC) have not embraced
such technologies fully. These disparities are taking HPC, Big Data, and Deep
Learning into divergent trajectories.

International Workshop on High-Performance Big Data, Deep Learning, and Cloud
Computing (HPBDC), aims to bring HPC, Big Data processing, Deep Learning, and
Cloud Computing into a convergent trajectory. The workshop provides a forum for
scientists and engineers in academia and industry to present their latest
research findings in major and emerging topics for 'HPC + Big Data + Deep
Learning over HPC Clusters and Clouds'.

HPBDC 2019 will be held in conjunction with the 33rd IEEE International
Parallel and Distributed Processing Symposium (IPDPS 2019), Rio de Janeiro,
Brazil, Monday, May 20th, 2019.

HPBDC 2019 welcomes original submissions in a range of areas, including but not
limited to:

 * High-Performance Big Data analytics, Deep Learning, and Cloud Computing
   frameworks, programming models, and tools

 * Performance optimizations for Big Data, Deep Learning, and Cloud Computing
   systems and applications with HPC technologies

 * High-Performance in-memory computing technologies and abstractions

 * Performance modeling and evaluation for emerging Big Data processing, Deep
   Learning, and Coud Computing technologies

 * Big Data processing and Deep Learning on HPC, Cloud, and Grid computing
   infrastructures

 * Fault tolerance, reliability, and availability for high-performance Big
   Data computing, Deep Learning, and Cloud Computing

 * Green Big Data computing, Deep Learning, and HPC Clouds

 * Scheduling and provisioning data analytics on HPC and Cloud infrastructures

 * Scientific computing with Big Data and Deep Learning on HPC Clusters and/or
   Clouds

 * Case studies of Big Data and Deep Learning applications on HPC systems and
   Clouds

 * High-Performance streaming data processing architectures and technologies

 * High-Performance graph processing with Big Data

 * High-Performance SQL and NoSQL data management technologies


Papers should present original research. As the fields of Big Data, Deep
Learning, and Cloud Computing span many disciplines, papers should provide
sufficient background material to make them accessible to the broader
community. One outstanding paper will be selected for the Best Paper Award.


SUBMISSION INFORMATION 
----------------------------------------

All submissions should follow the IEEE standard 8.5x11 two-column
format. The workshop will accept traditional research papers (8-10
pages) for in-depth topics and short papers (4 pages) for works in
progress on hot topics.

- Long papers: 8-10 pages, with a full problem description,
  background and related work, design, and evaluation.

- Short papers: 4 pages, for works in progress on hot topics. 

All the papers should be submitted through
https://easychair.org/conferences/?conf=hpbdc2019.

All papers will be carefully reviewed by at least three reviewers.
Papers should not be submitted in parallel to any other conference or
journal.

The proceedings of this workshop will be published together with the
proceedings of other IPDPS 2019 workshops by the IEEE Computer Society Press.
Proceedings of the workshops are distributed at the conference and are
submitted for inclusion in the IEEE Xplore Digital Library after the
conference. At least one of the authors of each accepted paper must register as
a participant of the workshop and present the paper at the workshop, in order
to have the paper published in the proceedings.


IMPORTANT DATES
----------------------------

- Abstract submission deadline (optional): January 15th, 2019 (Anywhere on Earth)
- Paper submission deadline (extended): February 1st, 2019 (Anywhere on Earth)
- Acceptance notification: March 1st, 2019
- Camera-ready deadline: March 15th, 2019
- Workshop: May 20th, 2019


WORKSHOP ORGANIZERS 
--------------------------------------

Xiaoyi Lu, The Ohio State University
Jianfeng Zhan, Institute of Computing Technology, Chinese Academy of
              Sciences, China 
Dhabaleswar K. (DK) Panda, The Ohio State University


PROGRAM COMMITTEE (Confirmed So far)
------------------------------------------------------------

Luiz F. Bittencourt, University of Campinas, Brazil
Yong Chen, Texas Tech University
Ada Gavrilovska, Georgia Tech
Shadi Ibrahim, Inria, France
Zengxiang Li, Institute Of High Performance Computing, Singapore
Suzanne McIntosh, New York University
Sergey Maidanov, Intel
Raghunath Nambiar, AMD
Manoj Nambiar, Tata Consultancy Services Ltd., India
Juan Touriño, University of A Coruña, Spain
Li Zha, Institute of Computing Technology, Chinese Academy of Sciences, China
Yunquan Zhang, Institute of Computing Technology, Chinese Academy of 
              Sciences, China