Distilling the essence of raw video to reduce memory usage and energy at edge devices

Haibo Zhang, Shulin Zhao, Ashutosh Pattnaik, Mahmut T. Kandemir, Anand Sivasubramaniam, Chita R. Das

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Video broadcast and streaming are among the most widely used applications for edge devices. Roughly 82% of the mobile internet traffic is made up of video data. This is likely to worsen with the advent of 5G that will open up new opportunities for high resolution videos, virtual and augmented reality-based applications. The raw video data produced and consumed by edge devices is considerably higher than what is transmitted out of them. This leads to huge memory bandwidth and energy requirements from such edge devices. Therefore, optimizing the memory bandwidth and energy consumption needs is imperative for further improvements in energy efficiency of such edge devices. In this paper, we propose two mechanisms for on-the-fly compression and approximation of raw video data that is generated by the image sensors. The first mechanism, MidVB, performs lossless compression of the video frames coming out of the sensors and stores the compressed format into the memory. The second mechanism, Distill, builds on top of MidVB and further reduces memory consumption by approximating the video frame data. On an average, across 20 raw videos, MidVB and Distill are able to reduce the memory bandwidth by 43% and 72%, respectively, over the raw representation. They outperform a well known memory saving mechanism by 7% and 36%, respectively. Furthermore, MidVB and Distill reduce the energy consumption by 40% and 67%, respectively, over the baseline.

Original languageEnglish (US)
Title of host publicationMICRO 2019 - 52nd Annual IEEE/ACM International Symposium on Microarchitecture, Proceedings
PublisherIEEE Computer Society
Pages657-669
Number of pages13
ISBN (Electronic)9781450369381
DOIs
StatePublished - Oct 12 2019
Event52nd Annual IEEE/ACM International Symposium on Microarchitecture, MICRO 2019 - Columbus, United States
Duration: Oct 12 2019Oct 16 2019

Publication series

NameProceedings of the Annual International Symposium on Microarchitecture, MICRO
ISSN (Print)1072-4451

Conference

Conference52nd Annual IEEE/ACM International Symposium on Microarchitecture, MICRO 2019
CountryUnited States
CityColumbus
Period10/12/1910/16/19

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture

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    Zhang, H., Zhao, S., Pattnaik, A., Kandemir, M. T., Sivasubramaniam, A., & Das, C. R. (2019). Distilling the essence of raw video to reduce memory usage and energy at edge devices. In MICRO 2019 - 52nd Annual IEEE/ACM International Symposium on Microarchitecture, Proceedings (pp. 657-669). (Proceedings of the Annual International Symposium on Microarchitecture, MICRO). IEEE Computer Society. https://doi.org/10.1145/3352460.3358298