AVid: Annotation driven video decoding for hybrid memories

Abstract

Adopting emerging non-volatile memory (NVM) technologies is a viable solution to minimize the increasing memory leakage power in today's embedded systems. However, in order to take advantage of the many benefits in NVMs, software must account for their high write overheads. This paper presents AVid, an annotation driven video decoding technique for hybrid memory subsystems. AVid exploits the physical characteristics of NVMs by extracting video decoder access patterns and uses this meta-information to minimize write overheads, thereby improving energy savings and performance. Our experimental results on an annotation-aware H.264 codec show that our technique is able to achieve execution time and energy reduction by up to 40.8% and 39.7% respectively when applied to H.264 decoding.