4 papers
EnergyLens: Interpretable Closed-Form Energy Models for Multimodal LLM Inference Serving
Vittorio Palladino, Gianluca Palermo, Michael E. Papka +1
As large language models span dense, mixture-of-experts, and state-space architectures and are deployed on heterogeneous accelerators under increasingly diverse multimodal workload…
A Physically-Informed Subgraph Isomorphism Approach to Molecular Docking Using Quantum Annealers
Francesco Micucci, Matteo Barbieri, Gabriella Bettonte +6
Molecular docking is a crucial step in the development of new drugs as it guides the positioning of a small molecule (ligand) within the pocket of a target protein. In the literatu…
Towards High-Performance and Portable Molecular Docking on CPUs through Vectorization
Gianmarco Accordi, Jens Domke, Theresa Pollinger +2
Recent trends in the HPC field have introduced new CPU architectures with improved vectorization capabilities that require optimization to achieve peak performance and thus pose ch…
Molecular Docking via Weighted Subgraph Isomorphism on Quantum Annealers
Emanuele Triuzzi, Riccardo Mengoni, Francesco Micucci +4
Molecular docking is an essential step in the drug discovery process involving the detection of three-dimensional poses of a ligand inside the active site of the protein. In this p…