English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

This paper presents \pandora, a novel parallel algorithm for efficientlyconstructing dendrograms for single-linkage hierarchical clustering, including\hdbscan. Traditional dendrogram construction methods from a minimum spanningtree (MST), such as agglomerative or divisive techniques, often fail toefficiently parallelize, especially with skewed dendrograms common inreal-world data.  \pandora addresses these challenges through a unique recursive treecontraction method, which simplifies the tree for initial dendrogramconstruction and then progressively reconstructs the complete dendrogram. Thisprocess makes \pandora asymptotically work-optimal, independent of dendrogramskewness. All steps in \pandora are fully parallel and suitable for massivelythreaded accelerators such as GPUs.  Our implementation is written in Kokkos, providing support for both CPUs andmulti-vendor GPUs (e.g., Nvidia, AMD). The multithreaded version of \pandora is2.2$\times$ faster than the current best-multithreaded implementation, whilethe GPU \pandora implementation achieved 6-20$\times$ on \amdgpu and10-37$\times$ on \nvidiagpu speed-up over multithreaded \pandora. Theseadvancements lead to up to a 6-fold speedup for \hdbscan on GPUs over thecurrent best, which only offload MST construction to GPUs and performmultithreaded dendrogram construction.

PANDORA: A Parallel Dendrogram Construction Algorithm for Single Linkage Clustering on GPU