Intelligence in the Cloud is transforming the world and human life at a pace beyond imagination.
Whether it be recommender models for various businesses, or video analytics, or cloud-based services, applications are emerging at a rapid pace and designing hardware to efficiently support them on the cloud is important. Efficiently utilizing the hardware infrastructure to obtain high performance and energy-efficiency is important for sustainable computing.
Key Challenges
The emerging machine learning applications put exploding demands on cloud systems, and it is important to deliver high throughput, strong security, low latency and low energy consumption, in order to sustain the thriving development of a cognitive cloud. Designing efficient circuits and systems to enable, support, and harness the power of intelligence on the cloud is a timely problem to solve to keep the present momentum of intelligent systems.
Synergies
Numerous applications and edge systems are emerging, but an efficient smart cloud is necessary to support them, thus the cloud thrust is intertwined with edge and applications thrusts. We focus on workload-driven and workload-aware design of cloud systems.
Cloud Lead
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Lizy John
Cloud Lead
Professor, Texas ECE
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Derek Chiou
Professor, Texas ECE
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Mattan Erez
Professor, Texas ECE
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Andreas Gerstlauer
Professor, Texas ECE
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Jean Anne Incorvia
Assistant Professor, Texas ECE
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Jaydeep Kulkarni
Assistant Professor, Texas ECE
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Diana Marculescu
Founding Director
Professor, Texas ECE
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Michael Orshansky
Professor, Texas ECE
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David Z. Pan
Professor, Texas ECE
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Neeraja Yadwadkar
Assistant Professor, Texas ECE