Search Results for author: David Irwin

Found 9 papers, 2 papers with code

CEFL: Carbon-Efficient Federated Learning

no code implementations27 Oct 2023 Talha Mehboob, Noman Bashir, Jesus Omana Iglesias, Michael Zink, David Irwin

Federated Learning (FL) distributes machine learning (ML) training across many edge devices to reduce data transfer overhead and protect data privacy.

Federated Learning

Sustainable Computing -- Without the Hot Air

no code implementations30 Jun 2022 Noman Bashir, David Irwin, Prashant Shenoy, Abel Souza

This growth will translate to exponential growth in computing's energy consumption unless improvements in its energy-efficiency can outpace increases in its demand.

WattScale: A Data-driven Approach for Energy Efficiency Analytics of Buildings at Scale

no code implementations2 Jul 2020 Srinivasan Iyengar, Stephen Lee, David Irwin, Prashant Shenoy, Benjamin Weil

In this paper, we present \texttt{WattScale}, a data-driven approach to identify the least energy-efficient buildings from a large population of buildings in a city or a region.

Bayesian Inference Fault Detection +1

SunDown: Model-driven Per-Panel Solar Anomaly Detection for Residential Arrays

no code implementations25 May 2020 Menghong Feng, Noman Bashir, Prashant Shenoy, David Irwin, Beka Kosanovic

There has been significant growth in both utility-scale and residential-scale solar installations in recent years, driven by rapid technology improvements and falling prices.

Anomaly Classification Anomaly Detection +1

Peak Forecasting for Battery-based Energy Optimizations in Campus Microgrids

no code implementations25 May 2020 Akhil Soman, Amee Trivedi, David Irwin, Beka Kosanovic, Benjamin McDaniel, Prashant Shenoy

Battery-based energy storage has emerged as an enabling technology for a variety of grid energy optimizations, such as peak shaving and cost arbitrage.

Load Forecasting

Finding a "Kneedle" in a Haystack: Detecting Knee Points in System Behavior

1 code implementation 2011 31st International Conference on Distributed Computing Systems Workshops 2011 Ville Satopaa, Jeannie Albrecht, David Irwin, Barath Raghavan

Computer systems often reach a point at which the relative cost to increase some tunable parameter is no longer worth the corresponding performance benefit.

Cannot find the paper you are looking for? You can Submit a new open access paper.