Unlocking the Full Potential of Datacenter ML Accelerators with Platform-Aware Neural Architecture Search

Posted by Sheng Li, Staff Software Engineer and Norman P. Jouppi, Google Fellow, Google Research

Continuing advances in the design and implementation of datacenter (DC) accelerators for machine learning (ML), such as TPUs and GPUs, have been critical for powering modern ML models and applications at scale. These improved accelerators exhibit peak performance (e.g., FLOPs) that is orders of magnitude better than traditional computing systems. However, there is a fast-widening gap between the available peak performance offered …

architecture computer vision datacenter ml neural architecture search platform search tpu