"Holistic Resource Allocation under Federated Scheduling for Parallel R" by Lanshun Nie, Chenghao Fan et al.
 

Holistic Resource Allocation under Federated Scheduling for Parallel Real-time Tasks

Document Type

Article

Publication Date

1-1-2022

Abstract

With the technology trend of hardware and workload consolidation for embedded systems and the rapid development of edge computing, there has been increasing interest in supporting parallel real-time tasks to better utilize the multi-core platforms while meeting the stringent real-time constraints. For parallel real-time tasks, the federated scheduling paradigm, which assigns each parallel task a set of dedicated cores, achieves good theoretical bounds by ensuring exclusive use of processing resources to reduce interferences. However, because cores share the last-level cache and memory bandwidth resources, in practice tasks may still interfere with each other despite executing on dedicated cores. Such resource interferences due to concurrent accesses can be even more severe for embedded platforms or edge servers, where the computing power and cache/memory space are limited. To tackle this issue, in this work, we present a holistic resource allocation framework for parallel real-time tasks under federated scheduling. Under our proposed framework, in addition to dedicated cores, each parallel task is also assigned with dedicated cache and memory bandwidth resources. Further, we propose a holistic resource allocation algorithm that well balances the allocation between different resources to achieve good schedulability. Additionally, we provide a full implementation of our framework by extending the federated scheduling system with Intel's Cache Allocation Technology and MemGuard. Finally, we demonstrate the practicality of our proposed framework via extensive numerical evaluations and empirical experiments using real benchmark programs.

Identifier

85124790636 (Scopus)

Publication Title

ACM Transactions on Embedded Computing Systems

External Full Text Location

https://doi.org/10.1145/3489467

e-ISSN

15583465

ISSN

15399087

Issue

1

Volume

21

Grant

1948457

Fund Ref

National Science Foundation

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