Meet Dell And CSIRO's Large-Scale Artificial Intelligence Computer

Image: Supplied

Ronald N Bracewell is 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.

Bracewell is also the namesake for a new large-scale scientific computing system built by Dell, expanding the CSIRO's capability in deep learning and artificial intelligence.

The system was installed by Dell five days across May and June 2017, and now it is live.

Image: Dell

The Bracewell system is built on Dell EMC's PowerEdge platform, with partner technology including GPUs for computation and InfiniBand networking, which pieces all the compute nodes together in a low latency and high bandwidth solution faster than traditional networking.

Dell EMC ANZ High Performance Computing Lead, Andrew Underwood, said the installation process was streamlined and optimised for deep learning applications, with Bright Cluster Manager technology helping put these frameworks in place faster than ever before.

The system includes 114 x PowerEdge C4130 with NVIDIA Tesla P100 GPUs, NVLINK, dual Intel Xeon processors and 100Gbps Mellanox EDR InfiniBand.

This is a total of 1,634,304 CUDA Compute Cores, 3,192 Xeon Compute Cores and 29TB RAM. There's also 13 x 100Gbps 36p EDR InfiniBand switch fabric and Bright Cluster Manager Software 8.0.

CSIRO Deputy Chief Information Officer, and Head of Scientific Computing, Angus Macoustra, said the system is crucial to the organisation's work in identifying and solving emerging science problems.

"This is a critical enabler for CSIRO science, engineering and innovation. As a leading global research organisation, it’s important to sustain our global competitiveness by maintaining the currency and performance of our computing and data infrastructures," Macoustra said.

"The power of this new system is that it allows our researchers to tackle challenging workloads and ultimately enable CSIRO research to solve real-world issues. The system will nearly double the aggregate computational power available to CSIRO researchers, and will help transform the way we do scientific research and development," Macoustra said.

One of the first research teams to benefit from the new processing power will be Data61's Computer Vision group, led by Associate Professor Nick Barnes. His team develops the software for a bionic vision solution that aims 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.

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.

"When we conducted our first human trial, participants had to be fully supervised and were mostly limited to the laboratory, but for our next trial we’re aiming to get participants out of the lab and into the real world, controlling the whole system themselves," Barnes said.

With access to this new computing capability, Barnes and his 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.

"To make this a reality, we need to build vision processing systems that show accurate visualisations of the world in a broad variety of scenarios. These will enable people to the world through their bionic vision in a way that enables them to safely and effectively interact in challenging visual environments." Barnes said.

"This new system will provide greater scale and processing power we need to build our computer vision systems by optimisation of processing over broader scenarios, represented by much larger sets of images, to help train the software to understand and represent the world. We'll be able to take our computer vision research to the next level, solving problems through leveraging large scale image data that most labs around the world aren't able to."

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