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Found 4 papers, 1 papers with code
A Reinforcement Learning Approach for Performance-aware Reduction in Power Consumption of Data Center Compute Nodes
Employing a Proximal Policy Optimization (PPO) agent to learn an optimal policy on a mathematical model of the compute nodes, we demonstrate and evaluate using the STREAM benchmark how a trained agent running on actual hardware can take actions by balancing power consumption and application performance.
Generative Anomaly Detection for Time Series Datasets
To this end, we propose a principled and comprehensive framework consisting of a data-driven generative approach that can perform tractable density estimation for detecting traffic anomalies.
Stratum: A Serverless Framework for Lifecycle Management of Machine Learning based Data Analytics Tasks
With the proliferation of machine learning (ML) libraries and frameworks, and the programming languages that they use, along with operations of data loading, transformation, preparation and mining, ML model development is becoming a daunting task.
BARISTA: Efficient and Scalable Serverless Serving System for Deep Learning Prediction Services
Third, we propose an efficient heuristic to identify suitable compute resource configurations.
