We design, implement, and evaluate GPU-based algorithms for the maximum cardinality
matching problem in bipartite graphs. Such algorithms have a variety of applications in
computer science, scientific computing, bioinformatics, and other areas. To the best of our
knowledge, ours is the first study which focuses on the GPU implementation of the maximum
cardinality matching algorithms. We compare the proposed algorithms with serial and
multicore implementations from the literature on a large set of real-life problems where in …

Proposed algorithms: BFS kernel function 1 Augmenting-path based GPU algorithm 2 for i
from 0 to process cnt− 1 do 3 col vertex i⇥ tot thread num+ tid; 4 if bfs array [col vertex]= bfs
level then 5 for j from cxadj [col vertex] to cxadj [col vertex+ 1] do 6 neighbor row cadj [j]; 7
col match rmatch [neighbor row]; 8 if col match>− 1 then 9 if bfs array [col match]= L0− 1 then
10 vertex inserted true; 11 bfs array [col match] bfs level+ 1; 12 predeccesor [neighbor row]
col vertex; 13 else 14 if col match=− 1 then 15 rmatch [neighbor row]− 2; 16 predeccesor …