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Rcpp 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)

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.