Bringing together Machine Learning (ML) tools, libraries, and access to data, across large Graphic Processing Unit (GPU) deployments nationally to provide a consolidated platform for ML-based research, deployed at Monash University and University of Queensland.
The confluence of big data, Machine Learning (ML) techniques and parallel computing is making AI useful across a range of research areas. There is increasing sophistication, insight and accuracy which is driving a strong and growing appetite across research groups for access to ML capacity, services, libraries, expertise and training.
The environment developed for Machine Learning will support core ML tools for preprocessing, annotating, training, and validation, and integrate with software development environments. A national outreach and training program will engage the researcher community and increase knowledge.
Who is this project for?
- Researchers who require access to machine learning tools and computing, and are interested in upskilling their machine learning expertise across a wide range of domains including life sciences, engineering, computer science, and increasingly the humanities and social sciences.
- Infrastructure providers
What does this project enable?
The project will enable ML researchers and users from a variety of research areas to do their research efficiently and effectively with available reference data and tools, which will greatly facilitate new discoveries. It will also enable infrastructure providers to provide better data and computing infrastructure for supporting ML researchers.
View the report of the 2019 ARDC project ‘Machine learning infrastructure deployed at scale: understanding requirements, demand, impact and international best practice.’
Visit the high-performance data processing facility, MASSIVE
Visit the high performance computer at the University of Queensland, Wiener
Visit the Data science and AI platform at Monash University, DSAI