TY - GEN
T1 - Strict Partitioning for Sporadic Rigid Gang Tasks
AU - Sun, Binqi
AU - Kloda, Tomasz
AU - Caccamo, Marco
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - The rigid gang task model is based on the idea of executing multiple threads simultaneously on a fixed number of processors to increase efficiency and performance. Although there is extensive literature on global rigid gang scheduling, partitioned approaches have several practical advantages (e.g., task isolation and reduced scheduling overheads). In this paper, we propose a new partitioned scheduling strategy for rigid gang tasks, named strict partitioning. The method creates disjoint partitions of tasks and processors to avoid inter-partition interference. Moreover, it tries to assign tasks with similar volumes (i.e., parallelisms) to the same partition so that the intra-partition interference can be reduced. Within each partition, the tasks can be scheduled using any type of scheduler, which allows the use of a less pessimistic schedulability test. Extensive synthetic experiments and a case study based on Edge TPU benchmarks show that strict partitioning achieves better schedulability performance than state-of-The-Art global gang schedulability analyses for both preemptive and non-preemptive rigid gang task sets.
AB - The rigid gang task model is based on the idea of executing multiple threads simultaneously on a fixed number of processors to increase efficiency and performance. Although there is extensive literature on global rigid gang scheduling, partitioned approaches have several practical advantages (e.g., task isolation and reduced scheduling overheads). In this paper, we propose a new partitioned scheduling strategy for rigid gang tasks, named strict partitioning. The method creates disjoint partitions of tasks and processors to avoid inter-partition interference. Moreover, it tries to assign tasks with similar volumes (i.e., parallelisms) to the same partition so that the intra-partition interference can be reduced. Within each partition, the tasks can be scheduled using any type of scheduler, which allows the use of a less pessimistic schedulability test. Extensive synthetic experiments and a case study based on Edge TPU benchmarks show that strict partitioning achieves better schedulability performance than state-of-The-Art global gang schedulability analyses for both preemptive and non-preemptive rigid gang task sets.
KW - Gang parallel task model
KW - Partitioned scheduling
KW - Real-Time scheduling
KW - Tensor processing unit
UR - http://www.scopus.com/inward/record.url?scp=85197692363&partnerID=8YFLogxK
U2 - 10.1109/RTAS61025.2024.00028
DO - 10.1109/RTAS61025.2024.00028
M3 - Conference contribution
AN - SCOPUS:85197692363
T3 - Proceedings of the IEEE Real-Time and Embedded Technology and Applications Symposium, RTAS
SP - 252
EP - 264
BT - Proceedings - 2024 IEEE 30th Real-Time and Embedded Technology and Applications Symposium, RTAS 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 30th IEEE Real-Time and Embedded Technology and Applications Symposium, RTAS 2024
Y2 - 13 May 2024 through 16 May 2024
ER -