Year: 2025
Type: conference-paper
Abstract: Breadth First Search (BFS) plays a key role in computational science, networking, and artificial intelligence applications. Although the BFS approach has been extensively studied, particularly in its direction-optimized form, existing implementations still present three main issues: (1) high memory footprint; (2) the under-realized lightweight representations using bitmaps; and (3) the underuse of modern hardware such as Tensor Cores Units (TCUs).
Authors: Yuyao Niu, Marc Casas
Language: English
Topic: Graph Theory and Algorithms
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Awards: G1175115578, G121809054, G1599646647, G1855990336, G2064873908, G2262748287, G2309174360, G252646220, G2660406951, G279363373, G294895050, G3005324705, G300979063, G34346518, G3480869486, G3690828678, G425668148, G430777504, G5080475149, G5421974903, G546199279, G6006988010, G6218905885, G6641934258, G6833763678, G69051668, G7084143925, G7127239378, G7425137858, G787121397, G8684520763, G8796179060, G8888022036, G897484643, G99296377
OpenAlex ID: W4408029507