Title :
Novel algebras for advanced analytics in Julia
Author :
Shah, Vivek B. ; Edelman, A. ; Karpinski, Stefan ; Bezanson, Jeff ; Kepner, Jeremy
Abstract :
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.
Keywords :
high level languages; linear algebra; mathematics computing; Julia; Julia language system; advanced analytics; graph algorithms; high level languages; linear algebra techniques; linear algebraic approach; linear algebraic methodologies; matrix multiplication; novel algebras; sparse adjacency matrix representation; vector multiplication; Electronic mail; Matrices; Sparse matrices; Standards; Syntactics;
Conference_Titel :
High Performance Extreme Computing Conference (HPEC), 2013 IEEE
Conference_Location :
Waltham, MA
Print_ISBN :
978-1-4799-1364-0
DOI :
10.1109/HPEC.2013.6670347
