README.md
In rmumps: Wrapper for MUMPS Library

MUMPS stands for "a MUltifrontal Massively Parallel sparse direct Solver" see more on their official site http://mumps.enseeiht.fr/. Currently, it is one of the most competitive direct solvers for sparse matrices. On my CPU (Xenon E5-2609 v2 @ 2.50GHz) I have a speedup ranging from 3 to 16 compared to the default solver from Matrix package. In addition, the precision of the solution is equal or even better than with Matrix.

Example of use:

   # prepare random sparse matrix
   library(Matrix)
   library(rmumps)
   n=2000
   a=Matrix(0, n, n)
   set.seed(7)
   ij=sample(1:(n*n), 15*n)
   a[ij]=runif(ij)
   diag(a)=0
   diag(a)=-rowSums(a)
   a[1,1]=a[1,1]-1
   am=Rmumps$new(a)
   b=as.double(a%*%(1:n)) # rhs for an exact solution vector 1:n
   # following time includes symbolic analysis, LU factorization and system solving
   system.time(x<-am$solve(b))
   bb=2*b
   # this second time should be much shorter
   # as symbolic analysis and LU factorization are already done
   system.time(xx<-am$solve(bb))
   # compare to Matrix corresponding times
   system.time(xm<-solve(a, b))
   system.time(xxm<-solve(a, bb))
   # compare to Matrix precision
   range(x-1:n)  # mumps
   range(xm-1:n) # Matrix

   # matrix inversion
   system.time(aminv <- am$inv())
   system.time(ainv <- solve(a)) # the same in Matrix

   # clean up by hand to avoid possible interference between gc() and
   # Rcpp object destructor after unloading this namespace
   rm(am)