CarbonPATH: Carbon-aware pathfinding and architecture optimization for chiplet-based AI systems

TL;DR

CarbonPATH is a framework that co-optimizes AI chiplet-based systems for performance, cost, and environmental sustainability by exploring a complex design space with simulated annealing.

Contribution

It introduces a multi-objective co-design approach that incorporates sustainability as a core constraint in optimizing heterogeneous integration systems.

Findings

Identifies system configurations balancing performance and carbon footprint.

Reveals interactions across application, architecture, and packaging that affect sustainability.

Demonstrates the effectiveness of simulated annealing in high-dimensional design space exploration.

Abstract

The exponential growth of AI has created unprecedented demand for computational resources, pushing chip designs to the limit while simultaneously escalating the environmental footprint of computing. As the industry transitions toward heterogeneous integration (HI) to address the yield and cost challenges of monolithic scaling, minimizing the carbon cost of these complex HI systems becomes critical. To fully exploit HI, a co-design approach spanning application, architecture, chip, and packaging is essential. However, this creates a vast design space with competing objectives, specifically the trade-offs between performance, cost, and carbon footprint (CFP) for sustainability. CarbonPATH is an early-stage pathfinding framework designed to address this multi-objective challenge. It identifies optimized HI systems by co-designing workload mapping, architectural parameters, and packaging technologies, while treating sustainability as a first-class design constraint. The framework accounts for a wide range of factors, including compute and memory sizes, chiplet technology nodes, communication protocols, integration style (2D, 2.5D, 3D), operational CFP, embodied CFP, and interconnect type. Using simulated annealing, CarbonPATH explores this high-dimensional space to identify solutions that balance traditional metrics against environmental impact. By capturing interactions across applications, architectures, chiplets, and packaging, CarbonPATH uncovers system-level solutions that traditional methods often miss due to restrictive assumptions or limited scope.