The challenge
Deep learning research is increasing
Deep learning uses algorithms based on the biological neurons that power the human brain to make predictions based on vast quantities of data.
Like the neurons in our brain, deep learning systems need to process many thousands of pieces of data in parallel.
As a research organisation that's on the cutting edge developing and applying deep learning techniques, we need high performance deep learning computing systems to power that innovation.
Our response
We built a new high performance deep learning system
We worked with Dell EMC to build a high performance scientific computer, Bracewell, to expand our computational capability in deep learning.
The system is named after Ronald N Bracewell, an Australian astronomer and engineer who worked in the CSIRO Radiophysics Laboratory during World War II, and whose work led to fundamental advances in medical imaging.
In addition to deep learning, the system provides capability for research in areas as diverse as virtual screening for therapeutic treatments, traffic and logistics optimisation, modelling of new material structures and compositions, machine learning for image recognition and pattern analysis.
With our researchers focused on solving problems on a scale never seen before, we're giving them the power to tackle new even larger problems, and to deliver their results quicker than ever before.
One of the first research teams to benefit from the new processing power was our Data61 Computer Vision group, who developed the software for a bionic vision solution. They aim to restore sight for those with profound vision loss through new computer vision processing that uses large scale image datasets to optimise and learn more effective processing.
With access to this new computing capability, the team will be able to use much larger data sets to help train the software to recognise and process more images, helping deliver a greater contextual meaning to the recipient.
Bracewell will help the research team scale their software to tackle new and more advanced challenges, and deliver a richer and more robust visual experience for the profoundly vision impaired.