Smart Resource Management for Data Streaming using an Online Bin-packing Strategy

The stream processing framework HarmonicIO is a prototype that addresses the needs for processing streams based on relatively large individual objects. In this regard, it is a specialized streaming framework well-suited for scientific workflows. Salman Toor and Oliver Stein presented this work, and our latest publication  Smart Resource Management for Data Streaming using an Online […]

Challenges

The practical problems that arise when going from simple models to big models include: Most simulation algorithms do not scale well to high dimensions. Simulation can becomes prohibitively expensive due to the multiscale nature of systems. Failure of traditional engineering methodology such as sensitivity analysis and optimization due to high dimensionality, non-linearities and stochasticity…. … […]

Highly Scalable Federated Machine Learning

Artificial intelligence is rapidly transforming our society. Machine learning models will soon be in every digital system we use. For this reason, there is an urgent need for methods and software that allows for development of state-of-the art ML models while protecting the integrity of data owners . In this project we work on algorithms, […]

“Ten simple rules” for establishing a national scale OpenStack cloud e-infrastructure for science

The SNIC Science Cloud (SSC) team has published a paper in the 2017 conference on IEEE eScience.¬† SNIC Science cloud has been an infrastructure project run by the¬†Swedish National Infrastructure for Computing (SNIC) with the purpose to assess if and how SNIC should offer cloud infrastructure to the scientific community. The project is now coming […]