Implementing the Jaccard Index on the Migratory Memory-Side Processing Emu Architecture

We present an implementation of the Jaccard Index for graphs on the Migratory Memory-Side Processing Emu architecture. This index was designed to find similarities between different vertices in a graph, and is often used to identify communities. The Emu architecture is a parallel system based on a partitioned global address space, with threads automatically migrating inside the memory. We introduce the parallel programming model used to exploit it, detail our implementation of the algorithm, and analyze simulated performance results as well as early hardware tests. We discuss its application to large scale problems.