HPBDC 2020 - 2020 The 6th IEEE International Workshop on High-Performance Big Data and Cloud Computing

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