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Scheduling Multi-Rate Real-Time Applications on Clustered Many-Core Architectures with Memory Constraints



Publication Type:

Conference/Workshop Paper


23rd Asia and South Pacific Design Automation Conference


Access to shared memory is one of the main chal- lenges for many-core processors. One group of scheduling strategies for such platforms focuses on the division of tasks’ access to shared memory and code execution. This allows to orchestrate the access to shared local and off-chip memory in a way such that access contention between different compute cores is avoided by design. In this work, an execution framework is introduced that leverages local memory by statically allocating a subset of tasks to cores. This reduces the access times to shared memory, as off-chip memory access is avoided, and in turn improves the schedulability of such systems. A Constrained Programming (CP) formulation is presented to selects the statically allocated tasks and generates the complete system schedule. Evaluations show that the pro- posed approach yields an up to 21% higher schedulability ratio than related work, and a case study demonstrates its applicability to industrial problems.


author = {Matthias Becker and Saad Mubeen and Dakshina Dasari and Moris Behnam and Thomas Nolte},
title = {Scheduling Multi-Rate Real-Time Applications on Clustered Many-Core Architectures with Memory Constraints},
month = {January},
year = {2018},
booktitle = {23rd Asia and South Pacific Design Automation Conference},
url = {}