Call for Papers
Big Data applications (e.g., data analytics, machine learning, artificial intelligence) are of extreme importance to a wide range of areas such as healthcare, e-commerce, industry and natural sciences. However, as these applications evolve, their demand for more powerful computational and storage resources is also increasing rapidly. This need raises new challenges for users, developers and providers (e.g., cloud computing and High-performance computing centers) of such services.
The main goal of the HPBD workshop is to provide a common forum where systems researchers can propose and debate new research ideas for the Big Data field. By gathering researchers and practitioners working on related research topics such as distributed systems, storage systems, databases, dependability, cloud computing, and high-performance computing, the workshop aims at discussing current state of the art, emerging challenges and trends, as well as, novel solutions for Big Data systems.
The workshop is looking for submissions in the form of short papers with a maximum of 6 pages (excluding references). These can include original contributions, experience reports, or work in progress reports (supported by a preliminary validation). The organization welcomes contributions from both academia and industry. All submissions will be reviewed by members of the workshop program committee, who will select the best submissions for presentation at the workshop.
Accepted papers will not be published in the proceedings but will be made available to the participants of the workshop. At least one author of each accepted submission is expected to present their work at the workshop, and to be available for discussions.
Topics of interest include, but are not limited to, the following:
- Data Analytics
- Machine Learning
- Artificial Intelligence
- Benchmarking
- Storage Systems
- Databases
- Cloud Computing
- High-Performance Computing
- Virtualization
- Monitoring