H. Baghdasaryan

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

Storage systems remain a significant bottleneck in large-scale deep learning training. Most evaluation studies rely on synthetic benchmarks that do not capture the I/O heterogeneity present in real training pipelines. Automated configuration methods often treat parameter selection as stateless, overlooking the tempor...