Design Space Exploration and Optimization for Carbon-Efficient Extended Reality Systems

TL;DR

This paper presents a data-driven, holistic design framework to optimize AI and XR hardware for reduced carbon emissions while maintaining performance, demonstrating significant efficiency improvements and lifecycle carbon savings.

Contribution

It introduces a comprehensive design exploration framework for carbon-efficient computing, addressing hardware and software jointly, and applies it to AI and XR systems for substantial carbon reduction.

Findings

10× carbon efficiency improvement in specialized AI and XR accelerators

Up to 21% lifecycle carbon savings in general-purpose hardware

7.86× carbon efficiency gain using 3D integration for XR systems

Abstract

As computing hardware becomes more specialized, designing environmentally sustainable computing systems requires accounting for both hardware and software parameters. Our goal is to design low carbon computing systems while maintaining a competitive level of performance and operational efficiency. Despite previous carbon modeling efforts for computing systems, there is a distinct lack of holistic design strategies to simultaneously optimize for carbon, performance, power and energy. In this work, we take a data-driven approach to characterize the carbon impact (quantified in units of CO2e) of various artificial intelligence (AI) and extended reality (XR) production-level hardware and application use-cases. We propose a holistic design exploration framework to optimize and design for carbon-efficient computing systems and hardware. Our frameworks identifies significant opportunities for carbon efficiency improvements in application-specific and general purpose hardware design and optimization. Using our framework, we demonstrate 10$\times$ carbon efficiency improvement for specialized AI and XR accelerators (quantified by a key metric, tCDP: the product of total CO2e and total application execution time), up to 21% total life cycle carbon savings for existing general-purpose hardware and applications due to hardware over-provisioning, and up to 7.86$\times$ carbon efficiency improvement using advanced 3D integration techniques for resource-constrained XR systems.