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20162022
most citedMany Sequential Iterative Algorithms Can Be Parallel and (Nearly) Work-efficient

5 citations · 13 across the 7 of their papers we have counts for

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cs.DS20225 cited

Many Sequential Iterative Algorithms Can Be Parallel and (Nearly) Work-efficient

Zheqi Shen, Zijin Wan, Yan Gu +1

To design efficient parallel algorithms, some recent papers showed that many sequential iterative algorithms can be directly parallelized but there are still challenges in achievin…

cs.DS20222 cited

PaC-trees: Supporting Parallel and Compressed Purely-Functional Collections

Laxman Dhulipala, Guy E. Blelloch, Yan Gu +1

Many modern programming languages are shifting toward a functional style for collection interfaces such as sets, maps, and sequences. Functional interfaces offer many advantages, i…

cs.DS2021

Analysis of Work-Stealing and Parallel Cache Complexity

Yan Gu, Zachary Napier, Yihan Sun

Parallelism has become extremely popular over the past decade, and there have been a lot of new parallel algorithms and software. The randomized work-stealing (RWS) scheduler plays…

cs.DS20212 cited

Fast Parallel Algorithms for Euclidean Minimum Spanning Tree and Hierarchical Spatial Clustering

Yiqiu Wang, Shangdi Yu, Yan Gu +1

This paper presents new parallel algorithms for generating Euclidean minimum spanning trees and spatial clustering hierarchies (known as HDBSCAN). Our approach is based on gene…

cs.DS2020

A Parallel Batch-Dynamic Data Structure for the Closest Pair Problem

Yiqiu Wang, Shangdi Yu, Yan Gu +1

We propose a theoretically-efficient and practical parallel batch-dynamic data structure for the closest pair problem. Our solution is based on a serial dynamic closest pair data s…

cs.DS2019

Theoretically-Efficient and Practical Parallel DBSCAN

Yiqiu Wang, Yan Gu, Julian Shun

The DBSCAN method for spatial clustering has received significant attention due to its applicability in a variety of data analysis tasks. There are fast sequential algorithms for D…