Author

H. Astsatryan

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Open access Oct 2026

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...

H. Baghdasaryan, H. Astsatryan · Scientific Reports · 0 citations

Open access Oct 2026

Outcome-as-a-service for multi-objective Dask-based Earth Observation processing

This paper presents an outcome-as-a-service framework for Dask-based EO processing that jointly optimises all four objectives, and matches a biggest-tier oracle on execution time, cost, and energy while running up to roughly twice as fast as naive small-cluster and default provisioning.

Arthur Lalayan, Grégory Giuliani, H. Astsatryan · Discover Environment · 0 citations