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Idempotence-Based Preemptive GPU Kernel Scheduling for Embedded Systems.

Authors :
Lee, Hyeonsu
Kim, Hyunjun
Kim, Cheolgi
Han, Hwansoo
Seo, Euiseong
Source :
IEEE Transactions on Computers; Mar2021, Vol. 70 Issue 3, p332-346, 15p
Publication Year :
2021

Abstract

Mission-critical embedded systems simultaneously run multiple graphics-processing-unit (GPU) computing tasks with different criticality and timeliness requirements. Considerable research effort has been dedicated to supporting the preemptive priority scheduling of GPU kernels. However, hardware-supported preemption leads to lengthy scheduling delays and complicated designs, and most software approaches depend on the voluntary yielding of GPU resources from restructured kernels. We propose a preemptive GPU kernel scheduling scheme that harnesses the idempotence property of kernels. The proposed scheme distinguishes idempotent kernels through static source code analysis. If a kernel is not idempotent, then GPU kernels are transactionized at the operating system (OS) level. Both idempotent and transactionized kernels can be aborted at any point during their execution and rolled back to their initial state for reexecution. Therefore, low-priority kernel instances can be preempted for high-priority kernel instances and reexecuted after the GPU becomes available again. Our evaluation using the Rodinia benchmark suite showed that the proposed approach limits the preemption delay to 18 $\mu$ μ s in the 99.9th percentile, with an average delay in execution time of less than 10 percent for high-priority tasks under a heavy load in most cases. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00189340
Volume :
70
Issue :
3
Database :
Complementary Index
Journal :
IEEE Transactions on Computers
Publication Type :
Academic Journal
Accession number :
148745585
Full Text :
https://doi.org/10.1109/TC.2020.2988251