Bilge Acun - Designing Sustainable Datacenters with and for AI

Machine learning has witnessed exponential growth over the recent years. In this talk, we will first explore the environmental implications of the super-linear growth trend of AI from a holistic perspective, spanning data, algorithms, and system hardware. System efficiency optimizations can significantly help reducing the carbon footprint of AI systems. However, predictions show that the efficiency improvements will not be enough to reduce the overall resource needs of AI as Jevon's Paradox suggests "efficiency increases consumption". Therefore, we need to design our datacenters with sustainability in mind, using renewable energy every hour of every day. Relying on wind and solar energy 24/7 is challenging due to their intermittent nature. To cope with the fluctuations of renewable energy generation, multiple solutions can be applied such as energy storage and carbon aware scheduling for the workloads. In this talk, I will introduce a framework to analyze the multi-dimensional solution space by taking into account the operational and embodided footprint of the solutions and further how AI can be a part of the solution.