# Memory and time requirements of the scipy sparse spsolve

I have a system of fairly large set of linear equations (approximately 30K equations). I am using scipy.sparse.spsolve to solve these equations. Initially, I tried with 10K equations, but my program got killed due to memory issue. In general, I would like to know the memory and time requirements of the spsolve algorithm and exactly how the algorithm solves the system of equations. Is it based on factorization? Anyone can help me?

NB* - system of equations does not have a predefined structure like symmetricity etc, only thing is it is very sparse.

• I have solved systems with ~ 10M systems of equations in a laptop with 8 GB of RAM. – nicoguaro Dec 28 '18 at 17:33
• @nicoguaro using numpy/scipy ? I am very much surprised. I find it difficult to run mine with 10K equations on a server with 32GB RAM. You care to give some tips ? – Shew Dec 30 '18 at 11:42
• My matrices come from finite elements and I use COOrdinate list (COO) for the assembly and turn it into Compressed Sparse Row (CSR) for the solution phase. – nicoguaro Dec 30 '18 at 15:12