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GTC ON-DEMAND

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Abstract:

The University of Queensland needed to solve problems at a scale that had never been contemplated before. Enormous challenges in the field of scientific research imaging, modeling and analysis on the path to cure diseases such as Alzheimer’s and increasingly demanding cases in machine vision for digital skin cancer pathology were all mounting up against traditional HPC infrastructure. UQ took a considered leap towards GPU. This is UQ's architectural journey – how it built one of the most successful supercomputing facilities the state had ever created, the ways in which key components and architectural choices play a pivotal role in artificial intelligence and inference solving performance and a “whole of system” balance approach to getting HPC “right” in the era of GPU. A presentation for C-level, AI practitioners and HPC professional attendees alike, this talk will provide something useful and refreshing for all that have the chance to attend.

The University of Queensland needed to solve problems at a scale that had never been contemplated before. Enormous challenges in the field of scientific research imaging, modeling and analysis on the path to cure diseases such as Alzheimer’s and increasingly demanding cases in machine vision for digital skin cancer pathology were all mounting up against traditional HPC infrastructure. UQ took a considered leap towards GPU. This is UQ's architectural journey – how it built one of the most successful supercomputing facilities the state had ever created, the ways in which key components and architectural choices play a pivotal role in artificial intelligence and inference solving performance and a “whole of system” balance approach to getting HPC “right” in the era of GPU. A presentation for C-level, AI practitioners and HPC professional attendees alike, this talk will provide something useful and refreshing for all that have the chance to attend.

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Topics:
Artificial Intelligence and Deep Learning
Type:
Talk
Event:
AI Conference Australia
Year:
2018
Session ID:
AUS8015
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