SustainML has successfully integrated FPGA-based hardware estimation into its AI sustainability evaluation pipeline, enabling more accurate energy and carbon footprint analysis for CNN models deployed on FPGA platforms. By combining hardware-level latency and power prediction with automated carbon intensity calculation, the framework now supports end-to-end sustainability assessment for both Hugging Face transformer models and ONNX-based CNN models targeting FPGA devices. This integration strengthens SustainML’s ability to evaluate AI models across heterogeneous hardware environments and brings hardware-aware carbon estimation closer to real-world deployment scenarios.
This project has received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement No 101070408.