Author

Lorenzo Piarulli

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#machine learning Preprint Sep 2026

High-Performance Tensor Formulation of the Viterbi Algorithm for Hidden Semi-Markov Models

This work presents a tensor-based formulation of the Viterbi algorithm for HSMMs, restructuring the inner loops into tensor operations that naturally map onto SIMD units and massively parallel architectures and provides optimized implementations spanning single- and multi-core CPUs, and, for the first time, GPU.

Lorenzo Piarulli, E. Belli, D. De Sensi · 0 citations

Preprint Sep 2026

Characterizing the Scalability and Performance of Large-Scale AI Training Under Multi-Tenancy

This work designs a benchmark suite of AI models to evaluate the performance of five distinct parallelisation strategies across different supercomputing clusters, including Alps, Leonardo, LUMI, JUPITER, NVL72 GB300, and DGX A100.

Jacopo Raffi, Thomas Pasquali, Lorenzo Piarulli et al. · 0 citations