collaborators

5 papers

cs.DC2026

How Accurately Can the Energy Use of Spark Applications Be Estimated Based on Resource Utilisation?

Youssef Moawad, Kathleen West, Vasilis Bountris +3

Distributed batch data processing applications are widely executed on cloud-based resources where restricted user access to node-level hardware energy counters hinders transparent…

cs.DC2026

Ichnos+: Estimating the Carbon Footprint of Scientific Workflows Using Fitted Power Models

Kathleen West, Youssef Moawad, Philipp Thamm +5

As data-intensive scientific workflows scale to facilitate the automation of analysis of increasing amounts of data, their resource-intensive and long-running execution incurs sign…

cs.DC2026

A Systematic Evaluation of the Potential of Carbon-Aware Execution for Scientific Workflows

Kathleen West, Youssef Moawad, Fabian Lehmann +4

Scientific workflows are critical to scientific data analysis and often involve computationally intensive processing of large datasets on compute clusters. As such, their execution…

cs.DC2026

Spatio-Temporal Shifting to Reduce Carbon, Water, and Land-Use Footprints of Cloud Workloads

Giulio Attenni, Youssef Moawad, Novella Bartolini +1

In this paper, we investigate the potential of spatial and temporal cloud workload shifting to reduce carbon, water, and land use footprints. Specifically, we perform a simulation…

quant-ph2024

Optimising Iteration Scheduling for Full-State Vector Simulation of Quantum Circuits on FPGAs

Youssef Moawad, Andrew Brown, René Steijl +1

As the field of quantum computing grows, novel algorithms which take advantage of quantum phenomena need to be developed. As we are currently in the NISQ (noisy intermediate scale…