Hyppää sisältöön
    • FI
    • ENG
  • FI
  • /
  • EN
OuluREPO – Oulun yliopiston julkaisuarkisto / University of Oulu repository
Näytä viite 
  •   OuluREPO etusivu
  • Oulun yliopisto
  • Avoin saatavuus
  • Näytä viite
  •   OuluREPO etusivu
  • Oulun yliopisto
  • Avoin saatavuus
  • Näytä viite
JavaScript is disabled for your browser. Some features of this site may not work without it.

Interoperable GPU kernels as latency improver for MEC

Haavisto, Juuso; Riekki, Jukka (2020-05-04)

 
Avaa tiedosto
nbnfi-fe2020050725516.pdf (190.2Kt)
nbnfi-fe2020050725516_meta.xml (28.57Kt)
nbnfi-fe2020050725516_solr.xml (26.26Kt)
Lataukset: 

URL:
https://doi.org/10.1109/6GSUMMIT49458.2020.9083751

Haavisto, Juuso
Riekki, Jukka
Institute of Electrical and Electronics Engineers
04.05.2020

J. Haavisto and J. Riekki, "Interoperable GPU Kernels as Latency Improver for MEC," 2020 2nd 6G Wireless Summit (6G SUMMIT), Levi, Finland, 2020, pp. 1-5, doi: 10.1109/6GSUMMIT49458.2020.9083751

https://rightsstatements.org/vocab/InC/1.0/
© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
https://rightsstatements.org/vocab/InC/1.0/
doi:https://doi.org/10.1109/6GSUMMIT49458.2020.9083751
Näytä kaikki kuvailutiedot
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi-fe2020050725516
Tiivistelmä

Abstract

Mixed reality (MR) applications are expected to become common when 5G goes mainstream. However, the latency requirements are challenging to meet due to the resources required by video-based remoting of graphics, that is, decoding video codecs. We propose an approach towards tackling this challenge: a client-server implementation for transacting intermediate representation (IR) between a mobile UE and a MEC server instead of video codecs and this way avoiding video decoding. We demonstrate the ability to address latency bottlenecks on edge computing workloads that transact graphics. We select SPIR-V compatible GPU kernels as the intermediate representation. Our approach requires know-how in GPU architecture and GPU domain-specific languages (DSLs), but compared to video-based edge graphics, it decreases UE device delay by sevenfold. Further, we find that due to low cold-start times on both UEs and MEC servers, application migration can happen in milliseconds. We imply that graphics-based location-aware applications, such as MR, can benefit from this kind of approach.

Kokoelmat
  • Avoin saatavuus [41246]
oulurepo@oulu.fiOulun yliopiston kirjastoOuluCRISLaturiMuuntaja
SaavutettavuusselosteTietosuojailmoitusYlläpidon kirjautuminen
 

Selaa kokoelmaa

NimekkeetTekijätJulkaisuajatAsiasanatUusimmatSivukartta

Omat tiedot

Kirjaudu sisäänRekisteröidy
oulurepo@oulu.fiOulun yliopiston kirjastoOuluCRISLaturiMuuntaja
SaavutettavuusselosteTietosuojailmoitusYlläpidon kirjautuminen