Energy Idle Aware Stochastic Lexicographic Local Searches for Precedence-Constraint Task List Scheduling on Heterogeneous Systems

Alejandro Santiago, Mirna Ponce-Flores, J. David Terán-Villanueva, Fausto Balderas, Salvador Ibarra Martínez, José Antonio Castan Rocha, Julio Laria Menchaca and Mayra Guadalupe Treviño Berrones
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Alejandro Santiago: Information Technology Engineering, Polytechnic University of Altamira, Altamira 89602, Mexico
Mirna Ponce-Flores: División de Estudios de Posgrado, Tecnológico Nacional de México/Instituto Tecnológico de Ciudad Madero, Ciudad Madero 89440, Mexico
J. David Terán-Villanueva: Facultad de Ingeniería Arturo Narro Siller, Universidad Autónoma de Tamaulipas, Tampico 89140, México
Fausto Balderas: División de Estudios de Posgrado, Tecnológico Nacional de México/Instituto Tecnológico de Ciudad Madero, Ciudad Madero 89440, Mexico
Salvador Ibarra Martínez: Facultad de Ingeniería Arturo Narro Siller, Universidad Autónoma de Tamaulipas, Tampico 89140, México
José Antonio Castan Rocha: Facultad de Ingeniería Arturo Narro Siller, Universidad Autónoma de Tamaulipas, Tampico 89140, México
Julio Laria Menchaca: Facultad de Ingeniería Arturo Narro Siller, Universidad Autónoma de Tamaulipas, Tampico 89140, México
Mayra Guadalupe Treviño Berrones: Facultad de Ingeniería Arturo Narro Siller, Universidad Autónoma de Tamaulipas, Tampico 89140, México

Energies, 2021, vol. 14, issue 12, 1-22

Abstract: The use of parallel applications in High-Performance Computing (HPC) demands high computing times and energy resources. Inadequate scheduling produces longer computing times which, in turn, increases energy consumption and monetary cost. Task scheduling is an NP-Hard problem; thus, several heuristics methods appear in the literature. The main approaches can be grouped into the following categories: fast heuristics, metaheuristics, and local search. Fast heuristics and metaheuristics are used when pre-scheduling times are short and long, respectively. The third is commonly used when pre-scheduling time is limited by CPU seconds or by objective function evaluations. This paper focuses on optimizing the scheduling of parallel applications, considering the energy consumption during the idle time while no tasks are executing. Additionally, we detail a comparative literature study of the performance of lexicographic variants with local searches adapted to be stochastic and aware of idle energy consumption.

Keywords: directed acyclic graph (DAG); scheduling; makespan; energy aware; energy idle; local search (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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