Publication | Open Access
PShifter
22
Citations
29
References
2018
Year
Unknown Venue
Cluster ComputingPower-aware ComputingLoad Balancing (Computing)EngineeringEnergy ManagementEnergy EfficiencyFirst Exascale MachinesParallel Performance EvaluationUs DepartmentComputer ArchitectureComputer EngineeringSystems EngineeringParallel ProgrammingComputer ScienceWorkload CharacterizationParallel ComputingComputational Load ImbalancePower-efficient Computing
The US Department of Energy (DOE) has set a power target of 20-30MW on the first exascale machines. To achieve one exaFLOPS under this power constraint, it is necessary to manage power intelligently while maximizing performance. Most production-level parallel applications suffer from computational load imbalance across distributed processes due to non-uniform work decomposition. Other factors like manufacturing variation and thermal variation in the machine room may amplify this imbalance. As a result of this imbalance, some processes of a job reach the blocking calls, collectives or barriers earlier and wait for others to reach the same point. This waiting results in a wastage of energy and CPU cycles which degrades application efficiency and performance.
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