Invasive Compute Balancing for Applications with Hybrid Parallelization

Schreiber, Martin; Riesinger, Christoph; Neckel, Tobias; Bungartz, Hans‐Joachim

doi:10.1109/sbac-pad.2013.20

Cited by 2 publications

(1 citation statement)

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“…This is the case with MPI libraries or PGAS run-time systems. There has been active research in both shared-memory [30] and distributed-memory [33,19,23,17,24] malleable systems.…”

Section: Malleability Supportmentioning

confidence: 99%

On the Convergence of Malleability and the HPC PowerStack: Exploiting Dynamism in Over-Provisioned and Power-Constrained HPC Systems

Arima

Comprés

Schulz

2022

Lecture Notes in Computer Science

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Recent High-Performance Computing (HPC) systems are suffering from severe problems, such as massive power consumption, while at the same time significantly under-utilized system resources. Given the power consumption trends, future systems will be deployed in an over-provisioned manner where more resources are installed than they can afford to power simultaneously. In such a scenario, maximizing resource utilization and energy efficiency, while keeping a given power constraint, is pivotal. Driven by this observation, in this position paper we first highlight the recent trends of resource management techniques, with a particular focus on malleability support (i.e., dynamically scaling resource allocations/requirements for a job), co-scheduling (i.e., colocating multiple jobs within a node), and power management. Second, we consider putting them together, assess their relationships/synergies, and discuss the functionality requirements in each software component for future over-provisioned and power-constrained HPC systems. Third, we briefly introduce our ongoing efforts on the integration of software tools, which will ultimately lead to the convergence of malleability and power management, as it is designed in the HPC PowerStack initiative.

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“…This is the case with MPI libraries or PGAS run-time systems. There has been active research in both shared-memory [30] and distributed-memory [33,19,23,17,24] malleable systems.…”

Section: Malleability Supportmentioning

confidence: 99%