3 papers
cs.DC2025
Distributed-Memory Parallel Algorithms for Fixed-Radius Near Neighbor Graph Construction
Gabriel Raulet, Dmitriy Morozov, Aydin Buluc +1
Computing fixed-radius near-neighbor graphs is an important first step for many data analysis algorithms. Near-neighbor graphs connect points that are close under some metric, endo…
cs.LG2025
Sparsity-Aware Communication for Distributed Graph Neural Network Training
Ujjaini Mukhodopadhyay, Alok Tripathy, Oguz Selvitopi +2
Graph Neural Networks (GNNs) are a computationally efficient method to learn embeddings and classifications on graph data. However, GNN training has low computational intensity, ma…
cs.LG2025
Scaling Graph Neural Networks for Particle Track Reconstruction
Alok Tripathy, Alina Lazar, Xiangyang Ju +3
Particle track reconstruction is an important problem in high-energy physics (HEP), necessary to study properties of subatomic particles. Traditional track reconstruction algorithm…