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SynergAI: Edge-to-Cloud Synergy for Architecture-Driven High-Performance Orchestration for AI Inference
Foteini Stathopoulou, Aggelos Ferikoglou, Manolis Katsaragakis +3
The rapid evolution of Artificial Intelligence (AI) and Machine Learning (ML) has significantly heightened computational demands, particularly for inference-serving workloads. Whil…
SLO-aware GPU Frequency Scaling for Energy Efficient LLM Inference Serving
Andreas Kosmas Kakolyris, Dimosthenis Masouros, Petros Vavaroutsos +2
As Large Language Models (LLMs) gain traction, their reliance on power-hungry GPUs places ever-increasing energy demands, raising environmental and monetary concerns. Inference dom…
Leveraging Core and Uncore Frequency Scaling for Power-Efficient Serverless Workflows
Achilleas Tzenetopoulos, Dimosthenis Masouros, Sotirios Xydis +1
Serverless workflows have emerged in Function-as-a-Service (FaaS) platforms to represent the operational structure of traditional applications. With latency propagation effects bec…