Architecture-Based Energy Consumption Dataset (ABCD)

The Architecture-Based Consumption Dataset (ABCD) is a large-scale experimental dataset capturing power, current, and voltage measurements collected during the execution of deep neural network architectures under diverse configurations. The dataset was generated as part of a PhD thesis at Newcastle University and is intended to support research on power estimation, architectural generalisation, and continual learning for deep neural networks, particularly in resource-constrained or edge-computing settings.