Berlin Big Data Center Phase II

© BBDC team

Funded by the German Federal Ministry of Education and Research (BMBF) and established in 2014, the Berlin Big Data Center (BBDC) is a national big data competence center led by the Technische Universität Berlin (TUB). In 2018, the BBDC entered into a subsequent three-year period due to an additional funding award by the BMBF. more to: Berlin Big Data Center Phase II

Berlin Center for Machine Learning

The Berlin Center for Machine Learning (BZML, Berliner Zentrum für Maschinelles Lernen) investigates methods of machine learning (ML), new complex models and mathematical foundations. more to: Berlin Center for Machine Learning

FogGuru - Training the Next Generation of European Fog Computing Experts

© FogGuru project

FogGuru contributes to the rapidly emerging domain of fog computing with technologies for managing application resources, middlewares for easing the development of more to: FogGuru - Training the Next Generation of European Fog Computing Experts

Hawk - A Hardware Adaptive Query Compiler

© CoGaDB Team

The performance of modern processors is primarily bound by a fixed energy budget. This power wall forces processor vendors to specialize their processors to certain applications to provide the speedups users expect. more to: Hawk - A Hardware Adaptive Query Compiler

ADAM - Approximate Analysis of Massive Data Streams with Modern Hardware

© M. Kiefer

The Software Campus project ADAM addresses the connection between approximated analysis of data streams and the advantages of modern hardware architectures. more to: ADAM - Approximate Analysis of Massive Data Streams with Modern Hardware

LAPSE - A System Architecture for Communication-Efficient Distributed Machine Learning

© DIMA/Renz-Wieland

The Software Campus backed LAPSE aims to develop a system architecture that mitigates communication costs for distributed machine learning. more to: LAPSE - A System Architecture for Communication-Efficient Distributed Machine Learning

moreEVS

The moreEVS Project is part of a bilateral initiative for joint Sino-German research projects. The number of electric vehicles (EVs) in urban areas, and therefore also the need for charging stations is expected to increase rapidly in the following years. In this research project, DIMA will address the challenge of conducting large-scale data analysis efficiently and pair renewable energy power sources with EVs. more to: moreEVS

Rhino

Managing Very Large Distributed State for Scalable Stream Processing more to: Rhino

EDADS Software Campus Project

The EDADS Software Campus Project more to: EDADS Software Campus Project

ExDRa

more to: ExDRa