Implement basic sparse matrix support

[ViralBShah]

We have some preliminary work in sparse.j, but a long way to go. I feel that the right approach is to do all basic operations in Julia, so that we can have sparse arrays with all types.

Then, plug in most of SuiteSparse for sparse linear algebra.

http://www.cise.ufl.edu/research/sparse/SuiteSparse/

[ViralBShah]

We already have basic sparse matrix support - sparse, find, speye, spones, sprand, indexing (slow), matrix multiplication, and some arithmetic. This is a good start, and other specific sparse matrix issues can be tracked individually. This issue can be closed once SuiteSparse is built in, and sparse \ is possible.

[ViralBShah]

commit 64f2f8e adds basic suitesparse support, with capability to solve a linear system. Still some ways away from being usable.

[ViralBShah]

Sparse matrices need to use 32-bit ints or 64-bit ints systematically, and not have a mix of integer types. Currently, some sparse matrices get created with 32-bit ints and other with 64-bit ints, making it difficult to call libraries. The code in sparse.j needs to be cleaned up for this.

[ViralBShah]

As of commit 4865eb0 that implements A \ b for sparse, enough sparse functionality is now available to close this issue.