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Found 2 papers, 1 papers with code
RUAD: unsupervised anomaly detection in HPC systems
However, current state-of-the-art (SoA) approaches to anomaly detection are supervised and semi-supervised, so they require a human-labelled dataset with anomalies - this is often impractical to collect in production HPC systems.
COUNTDOWN - three, two, one, low power! A Run-time Library for Energy Saving in MPI Communication Primitives
Power consumption is a looming treat in today's computing progress.
Distributed, Parallel, and Cluster Computing
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