Novel algebras for advanced analytics in Julia
Viral B. Shah, Alan S. Edelman, Stefan Karpinski, Jeff Bezanson, Jeremy Kepner · 2013
A linear algebraic approach to graph algorithms that exploits the sparse adjacency matrix representation of graphs can provide a variety of benefits. These benefits include syntactic simplicity, easier implementation, and higher performance. One way to employ linear algebra techniques for graph algorithms is to use a broader definition of matrix and vector multiplication. We demonstrate through the use of the Julia language system how easy it is to explore semirings using linear algebraic methodologies.