Jason Quek
Global CTO - Devoteam G Cloud
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Jason Quek has been programming since he was 14. Fast forward through a computer science degree, working in electronic trading algorithms in Singapore and New York, and telecom least cost routing software in Stockholm, he is now the CTO for Devoteam G Cloud. Seeing the evolution of Google Cloud Platform, he loves building interesting new applications on it (going from zero to minimum viable product in under a week), and also advocating its ease of use and limitless possibilities. His interests lie in hybrid and multicloud where he contributes as Google Certified Fellow in Hybrid and Multi Cloud and also in the field of machine learning and how to use it to do the things that humans do not want to do, so that people are free to do more interesting things.
Green Software Pattern optimized GPU usage for Machine Learning Ops
Machine Learning resource consumption has exploded due to the Generative AI boom, with many companies racing to develop unique capabilities around foundational models to become the next big thing. One unfortunate by-product is the overconsumption of GPUs leading to stock-outs on many clouds as well as contributing to higher carbon footprint across on-premise and multi-cloud. This session is to show a way which complies with Green Software patterns of predictive power consumption to train models in a sustainable and cost-optimized way while leveraging Kubernetes for orchestration, scalability and high availability while avoiding unnecessary retraining and massive amounts of experiments.
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