Evaluating Computing Platforms for Sustainability: A Comparative Analysis of FPGAs against ASICs, GPUs, and CPUs

2026-04-22

AI Summary

This work addresses the challenge of fairly evaluating the carbon footprints of FPGAs, ASICs, GPUs, and CPUs across their full life cycles to inform sustainable computing decisions. It introduces GreenFPGA, a novel tool that, for the first time, incorporates FPGA reconfigurability into a comprehensive life cycle carbon footprint model encompassing design, manufacturing, operation, reconfiguration, testing, recycling, and end-of-life disposal. Using life cycle assessment coupled with uncertainty analysis, the study performs cross-platform comparisons under equivalent performance conditions. Results demonstrate that, for workloads characterized by frequent changes, high diversity, and low batch sizes, FPGAs exhibit significantly lower total carbon emissions than conventional hardware platforms, highlighting their distinctive advantage in sustainable computing.

Technology Category

• Machine Learning: Hardware-aware ML
• Humans and AI: Other Foundations of Human Computation & AI
• Computer Vision: Bias, Fairness & Privacy

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Sustainability and carbon-aware systems for Web, mobile, and WoT
• Responsible Web: Sustainability and climate impact of web technologies
• Economics, Online Markets and Human Computation: Sustainability of Web economics

Abstract

Climate change concerns emphasize the need for sustainable computing. Modeling the carbon footprint (CFP), including operational and embodied CFP from semiconductor use, manufacture and design, is essential. Field programmable gate arrays (FPGAs) stand out as promising platforms due to their reconfigurability across various applications, enabling the amortization of embodied CFP across multiple applications. This paper introduces GreenFPGA, a tool estimating the total CFP of FPGAs over their lifespan, considering uncertainties in CFP modeling. It accounts for CFP during design, manufacturing, reconfigurability (reuse), operation, disposal, testing, and recycling. GreenFPGA identifies deployment regimes in which FPGAs can be more sustainable than ASICs, GPUs, and CPUs under the modeled iso-performance assumptions. Experimental results highlight the importance of analyzing applications across different computing platforms to assess their CFP while varying parameters such as application type, lifetime, usage time, and volume impact their total CFP. Across the evaluated pairwise iso-performance case studies with ASICs, GPUs, and CPUs, FPGAs can be more sustainable under specific deployment regimes involving frequently changing, diverse workloads and low-volume applications.

Problem

• sustainable computing
• carbon footprint
• FPGAs
• ASICs
• GPUs

Innovation

• GreenFPGA
• carbon footprint modeling
• reconfigurable computing
• sustainable computing
• embodied carbon