11 papers
A Vertical Approach to Designing and Managing Sustainable Heterogeneous Edge Data Centers
Aikaterini Maria Panteleaki, Varatheepan Paramanayakam, Vasileios Pentsos +3
The increasing demand for Artificial Intelligence (AI) computing poses significant environmental challenges, with both operational and embodied carbon emissions becoming major cont…
Carbon-Efficient 3D DNN Acceleration: Optimizing Performance and Sustainability
Aikaterini Maria Panteleaki, Konstantinos Balaskas, Georgios Zervakis +2
As Deep Neural Networks (DNNs) continue to drive advancements in artificial intelligence, the design of hardware accelerators faces growing concerns over embodied carbon footprint…
Sponge Attacks on Sensing AI: Energy-Latency Vulnerabilities and Defense via Model Pruning
Syed Mhamudul Hasan, Hussein Zangoti, Iraklis Anagnostopoulos +1
Recent studies have shown that sponge attacks can significantly increase the energy consumption and inference latency of deep neural networks (DNNs). However, prior work has focuse…
CarbonCall: Sustainability-Aware Function Calling for Large Language Models on Edge Devices
Varatheepan Paramanayakam, Andreas Karatzas, Iraklis Anagnostopoulos +1
Large Language Models (LLMs) enable real-time function calling in edge AI systems but introduce significant computational overhead, leading to high power consumption and carbon emi…
Ecomap: Sustainability-Driven Optimization of Multi-Tenant DNN Execution on Edge Servers
Varatheepan Paramanayakam, Andreas Karatzas, Dimitrios Stamoulis +1
Edge computing systems struggle to efficiently manage multiple concurrent deep neural network (DNN) workloads while meeting strict latency requirements, minimizing power consumptio…
Late Breaking Results: Leveraging Approximate Computing for Carbon-Aware DNN Accelerators
Aikaterini Maria Panteleaki, Konstantinos Balaskas, Georgios Zervakis +2
The rapid growth of Machine Learning (ML) has increased demand for DNN hardware accelerators, but their embodied carbon footprint poses significant environmental challenges. This p…