An analytical comparison of nearest neighbor algorithms for load balancing in parallel computers

With nearest neighbor load balancing algorithms, a processor makes balancing decisions based on its local information and manages work load migrations within its neighborhood. This paper compares a couple of fairly well-known nearest neighbor algorithms, the dimension exchange and the diffusion methods and their variants in terms of their performances in both one-port and all-port communication architectures. It turns out that the dimension exchange method outperforms the diffusion method in the one-port communication model, and that the strength of the diffusion method is in asynchronous implementations in the all-port communication model. The underlying communication networks considered assume the most popular topologies, the mesh and the torus and their special cases: the hypercube and the k-ary n-cube