Navigator: Dynamic multi-kernel scheduling to improve GPU performance

Jiho Kim, John Kim, Yongjun Park

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

2 Citations (Scopus)


Efficient GPU resource-sharing between multiple kernels has recently been a critical factor on overall performance. While previous works mainly focused on how to allocate resources to two kernels, there has been limited amount of work on determining which workloads to concurrently execute among multiple workloads. Therefore, we first demonstrate on a real GPU system how the selection of concurrent workloads can have significant impact on overall performance. We then propose GPU Navigator - a lookup-table-based dynamic multi-kernel scheduler that maximizes overall performance through online profiling. Our evaluation shows that GPU Navigator outperforms a greedy policy by 29.3% on average.

Original languageEnglish
Title of host publication2020 57th ACM/IEEE Design Automation Conference, DAC 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781450367257
Publication statusPublished - 2020 Jul
Event57th ACM/IEEE Design Automation Conference, DAC 2020 - Virtual, San Francisco, United States
Duration: 2020 Jul 202020 Jul 24

Publication series

NameProceedings - Design Automation Conference
ISSN (Print)0738-100X


Conference57th ACM/IEEE Design Automation Conference, DAC 2020
Country/TerritoryUnited States
CityVirtual, San Francisco

Bibliographical note

Funding Information:
We would like to thank to Jason Jong Kyu Park for his valuable feedback. This work was supported in part by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP)(No.2018R1D1A1B07050609, No.2015M3C4A7065647, No.2020R1A2B5B01001687), ICT R&D program of MSIP/IITP (No.2017-0-00142), and the R&D program of MOTIE/KEIT (No.10077609). Yongjun Park is the corresponding author.

Publisher Copyright:
© 2020 IEEE.

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Modelling and Simulation


Dive into the research topics of 'Navigator: Dynamic multi-kernel scheduling to improve GPU performance'. Together they form a unique fingerprint.

Cite this