Self-learning machines hunt for explosions in the universe and speed up innovations in industry and...
The National Science Agenda has awarded a 5 million euro grant to CORTEX – the Center for Optimal, Real-Time Machine Studies of the Explosive Universe. The CORTEX consortium of 12 partners from academia, industry and society will make self-learning machines faster, to figure out how massive cosmic explosions work, and to innovate wider applications.
Machine learning has rapidly become an integral part of society, in speech recognition or information retrieval. This is also the case in science, for detecting patterns in nature and the Universe. But the need is growing rapidly for such machines to respond quickly, in the application of self-driving cars and responsive manufacturing for example. On a more fundamental level, self-learning machines help us unveil a dynamical Universe we did not know existed up to recently. Bright explosions appear all over the radio and gravitational-wave sky. Many citizens and scientists are curious to understand where these come from.
The aim in CORTEX is to solve these open problems by bridging fundamental research to society.
The role of the Netherlands eScience center within the project:
The Netherlands eScience Center investigates how to create software with the help of AI that can make optimal use of the computing power of modern computers. The center then wants to apply this technology to implement software with which then can be observed explosive events in the universe.
The Netherlands eScience Center has a central role in CORTEX.The eScience center will be extending Kernel Tuner, a tool by Ben van Werkhoven, that uses machine learning algorithms to effectively speedup the optimization process of compute-intensive applications, with many new features and capabilities. The eScience Center then uses this technology to automatically optimize the real-time machine learning pipelines for observing the explosive universe developed within CORTEX.
The 5 million Euro grant from the Nationale Wetenschapsagenda: Onderzoek op Routes door Consortia (NWA-ORC) program thus funds research at partners ASTRON, Nikhef, SURF, Netherlands eScience Center, Universiteit van Amsterdam, Radboud Universiteit Nijmegen, Centrum Wiskunde & Informatica, IBM Nederland B.V., BrainCreators B.V., ABN AMRO N.V., NVIDIA, NOVA, and Stichting ILT; in cooperation with Rijksmuseum, Thermo Fisher B.V., and Leiden University.
Interpretable large scale deep generative models for Dark Matter searches
The intelligent Dark Matter survey
Modern big data front and backends in the hunt for Dark Matter
An eScience infrastructure for huge interferometric datasets
Kernel Tuner greatly simplifies the development of highly-optimized and auto-tuned CUDA, OpenCL, and C code, supporting many advanced use-cases and optimization strategies that speed up the auto-tuning process.