Asynchronous Computation of PageRank computation in an interactive multithreading environment

Numerical Linear Algebra has become almost indispensable in Web Information Retrieval. In this presentation we suggest that the asynchronous computation model is an attractive paradigm for organizing concurrent computations spanning data on Web scale. This suggestion is supported by experiments which highlight some interesting characteristics of this model as applied to 'page ranking' methods. After an introduction on asynchronous computing in general and 'page ranking' in particular, we present results from the asynchronous compution of PageRank using typical combinations of execution units (processes, threads) and communication mechanisms (message passing, shared memory). Sound convergence properties predicted by theory are numerically verified and interesting patterns of behavior are unveiled. Our experiments were performed on Jylab, an evolving environment enabling interactive multithreading and multiprocessing computations. This work is supported by a Pythagoras-EPEAEK-II grant and is conducted in collaboration with Daniel Szyld.