4 citations · 4 across the 5 of their papers we have counts for
6 papers
High-Performance Tensor Formulation of the Viterbi Algorithm for Hidden Semi-Markov Models
Lorenzo Piarulli, Elia Belli, Daniele De Sensi
Hidden Semi-Markov Models (HSMMs) are fundamental probabilistic models widely adopted across diverse domains, from computational biology to finance and signal processing. The Viter…
Characterizing the Scalability and Performance of Large-Scale AI Training Under Multi-Tenancy
Jacopo Raffi, Thomas Pasquali, Lorenzo Piarulli +6
Characterising AI workload performance on modern HPC systems requires understanding both their scalability in isolation and their behaviour under concurrent execution. However, the…
Stencil Computations on Tenstorrent Wormhole
Lorenzo Piarulli, Daniele De Sensi
As investment in AI-focused accelerators grows and their deployment in supercomputing facilities expands, understanding whether these architectures can efficiently support traditio…
Characterizing the Impact of Congestion in Modern HPC Interconnects
Lorenzo Piarulli, Marco Faltelli, Dirk Pleiter +7
High-performance computing (HPC) systems increasingly support both scalable AI training and large-scale simulation workloads. Both typically rely heavily on collective communicatio…
Bine Trees: Enhancing Collective Operations by Optimizing Communication Locality
Daniele De Sensi, Saverio Pasqualoni, Lorenzo Piarulli +5
Communication locality plays a key role in the performance of collective operations on large HPC systems, especially on oversubscribed networks where groups of nodes are fully conn…
PICO: Performance Insights for Collective Operations
Saverio Pasqualoni, Tommaso Bonato, Lorenzo Piarulli +3
Collective operations are cornerstones of both HPC applications and large-scale AI training and inference, yet benchmarking them in a systematic and reproducible way remains diffic…