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 inProceedings / IEEE Real-Time and Embedded Technology and Applications Symposium pp. 267 - 280
Main Authors Osborne, Sims Hill, Bakita, Joshua, Chen, Jingyuan, Yandrofski, Tyler, Anderson, James H.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2022
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ISSN2642-7346
DOI10.1109/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.
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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StartPage 267
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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