2 citations · 2 across the 3 of their papers we have counts for
3 papers
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…
Communication-Avoiding SpGEMM via Trident Partitioning on Hierarchical GPU Interconnects
Julian Bellavita, Lorenzo Pichetti, Thomas Pasquali +2
The multiplication of two sparse matrices, known as SpGEMM, is a key kernel in scientific computing and large-scale data analytics, underpinning graph algorithms, machine learning,…
Popcorn: Accelerating Kernel K-means on GPUs through Sparse Linear Algebra
Julian Bellavita, Thomas Pasquali, Laura Del Rio Martin +2
K-means is a popular clustering algorithm with significant applications in numerous scientific and engineering areas. One drawback of K-means is its inability to identify non-linea…