On Mon, Dec 20, 2010 at 8:16 PM, Peng, Wei <[email protected]> wrote:
> ... My question is really about what is the efficient way for graph > computation, matrix computation, algorithms that need many iterations to > converge (with intermediate results). > Large graph computations usually assume a sparse graph for historical reasons. A key property of scalable algorithms is that the time and space are linear in the input size. Most all path algorithms are not linear because the result is n x n and is dense. Some graph path computations can be done indirectly by spectral methods. With good random projection algorithms for sparse matrix decomposition, approximate versions of some of these algorithms can be phrased in a scalable fashion. It isn't an easy task, however. > HAMA looks like a very good solution, but can we use it now and how to > use it? > > I don't think that Hama has produced any usable software yet.
