Feb 17, 2023 · We present a new approach that exploits the elasticity of batch workloads in the cloud to optimize their carbon emissions.

This work develops a greedy algorithm for minimizing a job's carbon emissions via carbon scaling that is based on the well-known problem of marginal resource ...

Duration: 3:42
Posted: Jun 13, 2024

Feb 17, 2023 · We present an optimal greedy algorithm for minimizing a job's emissions through carbon scaling and implement a prototype of our CarbonScaler ...

We implement a CarbonScaler prototype in Kubernetes using its autoscaling capabilities and an analytic tool to guide the carbon-efficient deployment of batch ...

CarbonScaler enables batch applications to decrease their carbon footprint by scaling at low carbon periods and stopping/slowing down at high carbon periods.

CarbonScaler: Leveraging Cloud Workload Elasticity for Optimizing Carbon-Efficiency. WA Hanafy, Q Liang, N Bashir, D Irwin, P Shenoy. SIGMETRICS'24, 2024. 36 ...

Jun 10, 2024 · I am excited to be in Venice, Italy to present our paper "CarbonScaler: Leveraging Cloud Workload Elasticity for Optimizing ...

CarbonScaler: Leveraging Cloud Workload Elasticity for Optimizing Carbon-Efficiency. 10 Jun 2024Abstracts of the 2024 ACM SIGMETRICS/IFIP PERFORMANCE Joint ...

CarbonScaler: Leveraging Cloud Workload Elasticity for Optimizing Carbon-Efficiency. Hanafy, Walid, Liang, Qianlin, Bashir, Noman, Irwin, David, and Shenoy ...