Carbon explorer: A holistic framework for designing carbon aware datacenters
Technology companies reduce their datacenters' carbon footprint by investing in renewable
energy generation and receiving credits from power purchase agreements. Annually …
energy generation and receiving credits from power purchase agreements. Annually …
Extended berkeley packet filter: An application perspective
H Sharaf, I Ahmad, T Dimitriou - IEEE Access, 2022 - ieeexplore.ieee.org
The extended Berkeley Packet Filter (eBPF) is a lightweight and fast 64-bit RISC-like virtual
machine (VM) inside the Linux kernel. eBPF has emerged as the most promising and de …
machine (VM) inside the Linux kernel. eBPF has emerged as the most promising and de …
Zeus: Understanding and optimizing {GPU} energy consumption of {DNN} training
Zeus: Understanding and Optimizing GPU Energy Consumption of DNN Training Page 1 This
paper is included in the Proceedings of the 20th USENIX Symposium on Networked Systems …
paper is included in the Proceedings of the 20th USENIX Symposium on Networked Systems …
Clover: Toward sustainable ai with carbon-aware machine learning inference service
This paper presents a solution to the challenge of mitigating carbon emissions from hosting
large-scale machine learning (ML) inference services. ML inference is critical to modern …
large-scale machine learning (ML) inference services. ML inference is critical to modern …
{EnvPipe}: Performance-preserving {DNN} training framework for saving energy
Energy saving is a crucial mission for data center providers. Among many services, DNN
training and inference are significant contributors to energy consumption. This work focuses …
training and inference are significant contributors to energy consumption. This work focuses …
Green federated learning
A Yousefpour, S Guo, A Shenoy, S Ghosh… - arXiv preprint arXiv …, 2023 - arxiv.org
The rapid progress of AI is fueled by increasingly large and computationally intensive
machine learning models and datasets. As a consequence, the amount of compute used in …
machine learning models and datasets. As a consequence, the amount of compute used in …
Memory disaggregation: advances and open challenges
H Al Maruf, M Chowdhury - ACM SIGOPS Operating Systems Review, 2023 - dl.acm.org
Compute and memory are tightly coupled within each server in traditional datacenters.
Large-scale datacenter operators have identified this coupling as a root cause behind …
Large-scale datacenter operators have identified this coupling as a root cause behind …
Challenges and opportunities in sustainable serverless computing
P Sharma - ACM SIGENERGY Energy Informatics Review, 2023 - dl.acm.org
Serverless computing has rapidly emerged as a popular deployment model. However, its
energy and carbon implications are unclear and require exploration. This paper takes a look …
energy and carbon implications are unclear and require exploration. This paper takes a look …
Toward sustainable genai using generation directives for carbon-friendly large language model inference
The rapid advancement of Generative Artificial Intelligence (GenAI) across diverse sectors
raises significant environmental concerns, notably the carbon emissions from their cloud …
raises significant environmental concerns, notably the carbon emissions from their cloud …
Software‐in‐the‐loop simulation for developing and testing carbon‐aware applications
P Wiesner, M Steinke, H Nickel… - Software: Practice and …, 2023 - Wiley Online Library
The growing electricity demand of IT infrastructure has raised significant concerns about its
carbon footprint. To mitigate the associated emissions of computing systems, current efforts …
carbon footprint. To mitigate the associated emissions of computing systems, current efforts …