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

Characterising AI workload performance on modern HPC systems requires understanding both their scalability in isolation and their behaviour under concurrent execution. However, the interplay among parallelisation strategies, network congestion, compute capability, and interconnect technologies remains poorly understood...

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