2 citations · 3 across the 6 of their papers we have counts for
3 papers · 1 filter
SpSYRK: Half the Work in Distributed Sparse Matrix Multiplication
Thomas McFarland, Julian Bellavita, Giulia Guidi
The symmetric rank- update (SYRK), , computes the dot product of each pair of rows of , producing the Gram matrix . Its sparse variant underpins similarity se…
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,…
Communication-Avoiding Linear Algebraic Kernel K-Means on GPUs
Julian Bellavita, Matthew Rubino, Nakul Iyer +4
Clustering is an important tool in data analysis, with K-means being popular for its simplicity and versatility. However, it cannot handle non-linearly separable clusters. Kernel K…