HPBDC 2020

Welcome to HPBDC 2020

News: Due to COVID-19, HPBDC 2020 will be held online on May 18th, 9:00 AM EST. You can join the online event through this link. The program can be found here.

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 2020 will be held in conjunction with the 34th IEEE International Parallel and Distributed Processing Symposium (IPDPS 2020), New Orleans, Louisiana USA, May 2020.

Call For Papers

HPBDC 2020 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.

Keynote Speakers

Prof. Gagan Agrawal, School of Computer and Cyber Sciences at Augusta University

Achieving Programmability and Performance for Data-Intensive Computations Using Reduction Based APIs

Submission Info

All submissions should follow the IEEE standard 8.5” x 11” two-column format. The workshop will accept traditional research papers (8-10 pages) for in-depth topics and short papers (4-8 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 HPBDC@Linklings.

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 2020 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.

Camera-Ready Submission

Please check the main conference website.

Important Dates

Abstract submission (optional) deadline :

Paper submission deadline :

Acceptance notification :

Camera-Ready deadline :

Workshop :

January 16th, 2020 Anywhere on Earth

February 1st, 2020
February 14th, 2020 Anywhere on Earth

March 5th, 2020

March 15th, 2020

May 2020

Organizing Committee

Program Chairs

Xiaoyi Lu, The Ohio State University
Jianfeng Zhan, Institute of Computing Technology, Chinese Academy of Sciences, China

Publicity Chair

Haiyang Shi, The Ohio State University

Program Committee

Luiz F. Bittencourt, University of Campinas, Brazil
Yong Chen, Texas Tech University
Jong Youl Choi, Oak Ridge National Laboratory
Shadi Ibrahim, Inria, France
Hyun-Wook Jin, Konkuk University, Korea
Jithin Jose, Microsoft
Zengxiang Li, Institute Of High Performance Computing, Singapore
Mingzhe Li, Facebook
Suzanne McIntosh, New York University
Manoj Nambiar, Tata Consultancy Services Ltd., India
Md. Wasi-ur Rahman, Intel
Juan Touriño, University of A Coruña, Spain
Yunquan Zhang, Institute of Computing Technology, Chinese Academy of Sciences, China

Registration and Hotel

The workshop does not have a separate registration. All attendees need to register with the main conference. Details about registration and hotel can be found on the main conference website.

VISA