Fast Matlab compatible sparse assembly on multicore computers

• A novel algorithm for fast general assembly of sparse matrices is proposed.
• Modifications for efficient parallelization on multicore platforms are detailed.
• An open source implementation and benchmark tests show noticeable performance.
• A Matlab interface and scripts are provided for full reproducibility.

We develop and implement in this paper a fast sparse assembly algorithm, the fundamental operation which creates a compressed matrix from raw index data. Since it is often a quite demanding and sometimes critical operation, it is of interest to design a highly efficient implementation. We show how to do this, and moreover, we show how our implementation can be parallelized to utilize the power of modern multicore computers. Our freely available code, fully Matlab compatible, achieves about a factor of 5 × in speedup on a typical 6-core machine and 10 × on a dual-socket 16-core machine compared to the built-in serial implementation.