PolarisProfiler groups historical workloads by runtime behavior and classifies new workloads by static metadata, estimating resource usage with reported normalized error below 50% for 93% of tested Alibaba workloads.
L., Wang, C., and Youssef, A.{AI4DL}: Mining behaviors of deep learning workloads for resource management
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Formal and Empirical Study of Metadata-Based Profiling for Resource Management in the Computing Continuum
PolarisProfiler groups historical workloads by runtime behavior and classifies new workloads by static metadata, estimating resource usage with reported normalized error below 50% for 93% of tested Alibaba workloads.