USENIX ATC '24 and OSDI '24

Carole-Jean Wu, Meta

The past 50 years has seen a dramatic increase in the amount of compute per person, in particular, those enabled by AI. Despite the positive societal benefits, AI technologies come with significant environmental implications. I will talk about the scaling trend and the operational carbon footprint of AI computing by examining the model development cycle, spanning data, algorithms, and system hardware. At the same time, we will consider the life cycle of system hardware from the perspective of hardware architectures and manufacturing technologies. I will highlight key efficiency optimization opportunities for cutting-edge AI technologies, from deep learning recommendation models to multi-modal generative AI tasks. To scale AI sustainably, we need to make AI and computing more broadly efficient and flexible. We must also go beyond efficiency and optimize across the life cycle of computing infrastructures, from hardware manufacturing to datacenter operation and end-of-life processing for the hardware. Based on the industry experience and lessons learned, my talk will conclude with important development and research directions to advance the field of computing in an environmentally responsible and sustainable manner.

https://www.usenix.org/conference/atc24/presentation/wu-joint-keynote