S-HARP: A Parallel Dynamic Spectral Partitioner (A short summary)

Computational science problems with adaptive meshes involve dynamic load balancing when implemented on parallel machines. This dynamic load balancing requires fast partitioning of computational meshes at run time. We present in this report a scalable ...

Partitioning unstructured graphs is central to the parallel solution of computational science and engineering problems. Spectral partitioners, such as recursive spectral bisection (RSB), have proven effective in generating high-quality partitions of ...

We present HARP, a novel method for learning low dimensional embeddings of a graph's nodes which preserves higher-order structural features. Our proposed method achieves this by compressing the input graph prior to embedding it, effectively avoiding ...