Energy-efficient DNN Inference on Approximate Accelerators Through Formal Property Exploration

Ourania Spantidi, Georgios Zervakis, Iraklis Anagnostopoulos +1

Deep Neural Networks (DNNs) are being heavily utilized in modern applications and are putting energy-constraint devices to the test. To bypass high energy consumption issues, appro…