Hey Deb, sorry for the late answer, I've been travelling and don't have much time yet until in a few days.
To be precise, it's not me who has to solve the problem, but a person I know well and who I'd like to help with a possibly faster method. I'll try to state the facts as well as I know them, but forgive me if something does not make sense. The matrix to be solved represents a certain state in a hydrological transport model. It usually has about 1000 rows and columns, therefore about a million unknowns. This sparse matrix is symmetric, with values only on the main and secondary diagonals. After solving this matrix, we get a new state of the model. The matrix represents a system of linear equations which are currently solved iteratively with some defined termination criterion (usually a difference of less than 10^-5 between two iterations). The data is discretized using a finite difference method and is usually solved on a single workstation using a PCG solver implemented in Fortran. Does this help you and would your code be suited for this purpose? Best regards, Simon -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/Solving-Systems-of-Linear-Equations-Using-Spark-tp13674p14856.html Sent from the Apache Spark User List mailing list archive at Nabble.com. --------------------------------------------------------------------- To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional commands, e-mail: user-h...@spark.apache.org
