3 papers
cs.AI2026
SweetSpot: An Analytical Model for Predicting Energy Efficiency of LLM Inference
Hiari Pizzini Cavagna, Andrea Proia, Giacomo Madella +5
Large Language Models (LLMs) inference is central to modern AI applications, dominating worldwide datacenter workloads, making it critical to predict its energy footprint. Existing…
cs.AI2025
TabID: Automatic Identification and Tabulation of Subproblems in Constraint Models
Ãzgür Akgün, Ian P. Gent, Christopher Jefferson +5
The performance of a constraint model can often be improved by converting a subproblem into a single table constraint (referred to as tabulation). Finding subproblems to tabulate i…
cs.AI2024
Automatic Feature Learning for Essence: a Case Study on Car Sequencing
Alessio Pellegrino, Ãzgür Akgün, Nguyen Dang +2
Constraint modelling languages such as Essence offer a means to describe combinatorial problems at a high-level, i.e., without committing to detailed modelling decisions for a part…