Sparse matrix computation is a key aspect of scientific computing. The creators of Julia made the smart decision to rely on SuiteSparse, high-quality free C++ software that carries out most of the common sparse matrix factorizations and related operations very efficiently.
The issue that concerns me is that the wrappers in Julia, namely, cholmod.jl, spqr.jl and umfpack.jl, expose only a small fraction of SuiteSparse's capabilities. Furthermore, the exposed APIs give the Julia programmer significantly fewer capabilities than the sparse matrix suite of Matlab. And the reason for this limitation has become clear to me over the past few days as I tried to develop a routine to find a right null vector of a sparse matrix using SuiteSparse: it is difficult and tedious to write Julia wrappers for the routines in SuiteSparse. Even figuring out whether a particular variable is an Int32 or Int64 requires poring over SuiteSparse's nested header files full of conditional platform-dependent compilation directives. And my resulting wrapper works only on one platform for one version of Julia and one version of SuiteSparse. It is clear that whoever wrote cholmod.jl, spqr.jl and umfpack.jl put a lot of time and painstaking effort into getting these interfaces correct. And this raises a question: will Julia ever fully incorporate SuiteSparse? Will its sparse matrix capabilities ever approach Matlab's? Who will take the time to write, test and maintain cross-platform Julia wrappers for SuiteSparse? This is a tedious job that carries little glory - I certainly would not want to do it! And yet sparse matrix computation is so important.
