Minimizing DAG Utilization by Exploiting SMT
Parallel workloads are commonly modeled as directed acyclic graphs (DAGs). While DAG scheduling is an important tool, it is plagued by capacity loss; it is not uncommon to see half of a platform go unused. Here this loss is attacked from a new direction: reducing per-DAG utilization prior to assigni...
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Published in | Proceedings / IEEE Real-Time and Embedded Technology and Applications Symposium pp. 267 - 280 |
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Main Authors | , , , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
01.05.2022
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Subjects | |
Online Access | Get full text |
ISSN | 2642-7346 |
DOI | 10.1109/RTAS54340.2022.00029 |
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Abstract | Parallel workloads are commonly modeled as directed acyclic graphs (DAGs). While DAG scheduling is an important tool, it is plagued by capacity loss; it is not uncommon to see half of a platform go unused. Here this loss is attacked from a new direction: reducing per-DAG utilization prior to assigning computing cores to a DAG. Specifically, simultaneous multithreading (SMT) is used to schedule individual nodes of a DAG task in parallel on the same physical computing core. An optimization program is given that applies SMT to a DAG in a way that minimizes total utilization without compromising correctness. Results for both individual DAGs and systems of DAGs are evaluated using both a large-scale study of synthetic DAGs and a case study. Optimal use of the program can reduce DAG utilization and required core counts by over 40% in the best cases and by 25% in nearly half of cases. Runtime requirements for the optimization program are considered, and a tunable parameter is provided to make tradeoffs between runtime and optimality, allowing even DAGs with 500 nodes to benefit. |
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AbstractList | Parallel workloads are commonly modeled as directed acyclic graphs (DAGs). While DAG scheduling is an important tool, it is plagued by capacity loss; it is not uncommon to see half of a platform go unused. Here this loss is attacked from a new direction: reducing per-DAG utilization prior to assigning computing cores to a DAG. Specifically, simultaneous multithreading (SMT) is used to schedule individual nodes of a DAG task in parallel on the same physical computing core. An optimization program is given that applies SMT to a DAG in a way that minimizes total utilization without compromising correctness. Results for both individual DAGs and systems of DAGs are evaluated using both a large-scale study of synthetic DAGs and a case study. Optimal use of the program can reduce DAG utilization and required core counts by over 40% in the best cases and by 25% in nearly half of cases. Runtime requirements for the optimization program are considered, and a tunable parameter is provided to make tradeoffs between runtime and optimality, allowing even DAGs with 500 nodes to benefit. |
Author | Bakita, Joshua Chen, Jingyuan Anderson, James H. Osborne, Sims Hill Yandrofski, Tyler |
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Snippet | Parallel workloads are commonly modeled as directed acyclic graphs (DAGs). While DAG scheduling is an important tool, it is plagued by capacity loss; it is not... |
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SubjectTerms | Computational modeling Directed acyclic graph directed acyclic graphs hard real-time Multithreading parallel scheduling algorithms precedence constraints Processor scheduling Real-time systems Runtime Schedules simultaneous multi-threading |
Title | Minimizing DAG Utilization by Exploiting SMT |
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