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ARTful: A model for user‐defined schedulers targeting multiple high‐performance computing runtime systems
Author(s) -
Santana Alexandre,
Freitas Vinicius,
Castro Márcio,
Pilla Laércio L.,
Méhaut JeanFrançois
Publication year - 2021
Publication title -
software: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.437
H-Index - 70
eISSN - 1097-024X
pISSN - 0038-0644
DOI - 10.1002/spe.2977
Subject(s) - computer science , scheduling (production processes) , workload , operating system , reuse , runtime system , overhead (engineering) , distributed computing , computer architecture , ecology , operations management , economics , biology
Global schedulers are components in parallel runtime libraries that distribute the application's workload across physical resources. More often than not, applications showcase dynamic load imbalance and require customized scheduling solutions to avoid wasting resources. Some libraries lack support for user‐defined schedulers and developers resort to unofficial extensions that are harder to reuse and maintain. We propose a global scheduler software design, entitled ARTful model , to create user‐defined solutions with minimal alterations in the runtime library. Our model uses a component‐based design to separate components from the runtime library and the scheduling policy implementation. The ARTful model describes the interface of a portable scheduler library, allowing policies to operate on different runtime libraries. We study the overhead induced by our design through our ARTful library implementation metaprogramming‐oriented global scheduling library using workload‐aware scheduling policies. We experiment with two different policies from OpenMP and Charm++ runtime systems, also presenting evaluations of the policies outside of their original library context. We observe that our portable schedulers can sometimes perform decisions faster than their native counterparts with negligible overhead in the execution times of synthetic applications and molecular dynamics kernels.