A systematic review of Green AI
With the ever‐growing adoption of artificial intelligence (AI)‐based systems, the carbon
footprint of AI is no longer negligible. AI researchers and practitioners are therefore urged to …
footprint of AI is no longer negligible. AI researchers and practitioners are therefore urged to …
Carburacy: summarization models tuning and comparison in eco-sustainable regimes with a novel carbon-aware accuracy
Generative transformer-based models have reached cutting-edge performance in long
document summarization. Nevertheless, this task is witnessing a paradigm shift in …
document summarization. Nevertheless, this task is witnessing a paradigm shift in …
Deep reinforcement learning for containerized edge intelligence inference request processing in IoT edge computing
L Nkenyereye, KJ Baeg… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Edge intelligence (EI) refers to a set of connected systems and devices for artificial
intelligence (AI) data collected and learned near the data collection site. The EI model …
intelligence (AI) data collected and learned near the data collection site. The EI model …
On the energy consumption and performance of webassembly binaries across programming languages and runtimes in iot
Context. WebAssembly (WASM) is a low-level bytecode format that is gaining traction
among Internet of Things (IoT) devices. Because of IoT devices' resources limitations, using …
among Internet of Things (IoT) devices. Because of IoT devices' resources limitations, using …
On the Impact of Black-box Deployment Strategies for Edge AI on Latency and Model Performance
Deciding what combination of operators to use across the Edge AI tiers to achieve specific
latency and model performance requirements is an open question for MLOps engineers …
latency and model performance requirements is an open question for MLOps engineers …
Energy-Efficient Offloading in Edge Slicing with Non-Linear Power Functions
We focus on energy-efficient offloading strategies in a slicing-enabled large-scale edge
network, or an" edge slicing" system, with different computing/storage components, on which …
network, or an" edge slicing" system, with different computing/storage components, on which …
GALOIS: A Hybrid and Platform-Agnostic Stream Processing Architecture
With the increasing prevalence of IoT environments, the demand for processing massive
distributed data streams has become a critical challenge. Data Stream Processing on the …
distributed data streams has become a critical challenge. Data Stream Processing on the …
Green AI Quotient: Assessing Greenness of AI-based software and the way forward
As the world takes cognizance of AI's growing role in greenhouse gas (GHG) and carbon
emissions, the focus of AI research & development is shifting towards inclusion of energy …
emissions, the focus of AI research & development is shifting towards inclusion of energy …
Identifying architectural design decisions for achieving green ML serving
The growing use of large machine learning models highlights concerns about their
increasing computational demands. While the energy consumption of their training phase …
increasing computational demands. While the energy consumption of their training phase …
Insights on Implementing a Metrics Baseline for Post-Deployment AI Container Monitoring
H Yasar, J Morales, L Antunes - … of the 2024 International Conference on …, 2024 - dl.acm.org
Post-deployment monitoring (PDM) occurs in the late stages of a DevSecOps (DSO)
pipeline. Its role in DSO is critical in providing feedback loops on system performance …
pipeline. Its role in DSO is critical in providing feedback loops on system performance …