Vacancy for a PhD in Energy Labels for Digital Services

Back in July, I announced that our project proposal “Zero-Waste Computing: Energy Labels for Digital Services” was granted for the Science and Design PhD program at the University of Amsterdam. Now, the Parallel Computing Systems (PCS) group  is looking for a suitable PhD candidate for this project. Among other things, this involves modelling and monitoring to determine how energy is consumed in digital services whose computations are distributed over device, edge, and cloud.

Find a more detailed description of the vacancy, as well as instructions for how to apply here. The application period ends on October 18.

Project Proposal about Energy Labels for Digital Services Granted

It is my pleasure to announce our project proposal entitled “Zero-Waste Computing: Energy Labels for Digital Services” has been granted for the Science and Design PhD program at the University of Amsterdam. Ana Lucia Varbanescu is the main applicant for this project, with Anuj Pathania and myself as co-applicants. The project proposal was supported by Surf, ESI (TNO), Barcelona Supercomputing Center, and ASTRON.

The project addresses the issue that digital services are getting increasingly prevalent in society and are vital to the Dutch economy, already reaching 60% of GDP. However, they come with a significant, rapidly-increasing energy cost, raising sustainability concerns, since a mid-size datacenter alone consumes as much energy as a small town. However, datacenters are only the final link in a digital chain. Users interacting with devices — mobile phones, tablets, or laptops — trigger entire digital chains, combining multiple communicating computing layers and data transfers: from the device itself, through the edge, to the datacenter. Each layer has its own computing infrastructure (see figure). At each layer, decisions are made about how, where and when applications are running and/or data are transferred. These decisions have a significant impact on the user-perceived quality-of-service (QoS), but also on the energy consumption – per layer, and for the entire digital chain. The energy footprint of different devices along the chain might be known, but the actual energy consumed by the application is unknown, because it depends on infrastructure choices, and on user QoS requirements, and on mapping decisions made on the edge and in the datacenter. Thus, the energy efficiency, i.e., the amount of energy consumed to perform the actual task at hand, is largely unknown, for most digital chains.

We argue that the first step to reduce waste in computing is to quantify the energy efficiency of end-to-end digital chains. Our project focuses on designing an integrated framework (i.e., the methods, metrics, and tools) for this quantification effort. Specifically, we aim to define a reference architecture of digital chains, use it to define an analytical digital-chain energy-efficiency model that exposes the factors that impact energy efficiency along the chain, and support it with a high-level functional simulator to assess different operational scenarios and parameters that affect the energy efficiency of digital chains.

This is a small project funding only a single PhD student. More momentum is required to further advance this area and make a step from only monitoring the energy consumption of digital chains to also include actuation, e.g. energy minimization through workload redistribution, subject to performance constraints. We are currently looking for interested parties to collaborate with us on this topic in future project proposals.