Open AccessReal-Time Scheduling Parallel Tasks on Multicore Platforms
Author(s) -
Zhenyang Lei,
Xiangdong Lei,
Jun Long
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1673/1/012002
Subject(s) - computer science , multi core processor , parallel computing , scheduling (production processes) , cache , directed acyclic graph , distributed computing , worst case execution time , dynamic priority scheduling , computer architecture , execution time , operating system , schedule , algorithm , economics , operations management
Shared resources on the multicore chip, such as main memory, are increasingly becoming a point of contention. Traditional real-time task scheduling strategies focus on solely on the CPU, and do not take in account memory access and cache effects. In this paper, we propose real-time parallel scheduling (PRTTS) strategy on multicore platforms. Each task is represented as a directed acyclic graph (DAG). Tasks priorities are assigned according to task periods. In PRTTS scheduling strategy priorities of tasks which access memory are promoted over priorities of tasks not accessing memory. Tasks which read/write data in cache dynamically have their priority increased above all tasks. The results of simulation experiment show that proposed new scheduling strategy offers better performance in terms of core utilization and schedulability rate of tasks.