Sparse linear algebra is an important kernel in many different applications. Among various
sparse general matrix-matrix multiplication (SpGEMM) algorithms, Gustavson's column-wise …

Dynamic (Temporal) graphs capture the valuable evolution of real-world systems, from the
continuously evolving patterns of social interactions and genetic pathways to the dynamic …

Finding cohesive subgraphs is a crucial graph analysis kernel widely used for social and
biological networks (graphs). There exist various approaches for discovering insightful …

Information-theoretic community discovery method (popularly known as Infomap) is known
for delivering better quality results in the Lancichinetti–Fortunat–Radicchi (LFR) benchmark …

Identifying Community structures is a fundamental problem in graph analysis. To detect
communities in massive contemporary graphs, researchers have extensively explored …

Large-scale social community networks, characterized by millions of interconnected nodes
and edges, present intricate challenges that demand robust optimization and polynomial …

Community detection plays an essential role in the domains of social, bioinformatics, and e-
commerce. The innovative structural information theory (SInfo, introduced by Li et al.) has …

Discovering motifs or structural patterns, such as communities, is a significant graph
application utilized for classifying groups in social and business networks, identifying similar …

Detecção de comunidades em grafos é um tipo de análise amplamente utilizada por
aplicações de diversas áreas do conhecimento. Com o crescente aumento do volume de …

CONTEXT: High Performance Computing (HPC) is one of the most interdisciplinary fields
within computer science. However, its significant complexity presents considerable …