H. Baghdasaryan

Adaptive storage optimization for deep learning workloads in converged HPC-cloud environments: a reinforcement learning approach

A deep reinforcement learning framework is introduced that combines Proximal Policy Optimization and Soft Actor-Critic with a Transformer-based state encoder to predict workload phase transitions rather than merely respond to them and indicates that temporally aware storage control can improve the efficiency of distrib...