97 citations · 438 across the 36 of their papers we have counts for
13 papers · 1 filter
Parallel Algorithms for Hierarchical Nucleus Decomposition
Jessica Shi, Laxman Dhulipala, Julian Shun
Nucleus decompositions have been shown to be a useful tool for finding dense subgraphs. The coreness value of a clique represents its density based on the number of other cliques i…
Faster Parallel Exact Density Peaks Clustering
Yihao Huang, Shangdi Yu, Julian Shun
Clustering multidimensional points is a fundamental data mining task, with applications in many fields, such as astronomy, neuroscience, bioinformatics, and computer vision. The go…
Parallel Filtered Graphs for Hierarchical Clustering
Shangdi Yu, Julian Shun
Given all pairwise weights (distances) among a set of objects, filtered graphs provide a sparse representation by only keeping an important subset of weights. Such graphs can be pa…
Theoretically and Practically Efficient Parallel Nucleus Decomposition
Jessica Shi, Laxman Dhulipala, Julian Shun
This paper studies the nucleus decomposition problem, which has been shown to be useful in finding dense substructures in graphs. We present a novel parallel algorithm that is effi…
Parallel In-Place Algorithms: Theory and Practice
Yan Gu, Omar Obeya, Julian Shun
Many parallel algorithms use at least linear auxiliary space in the size of the input to enable computations to be done independently without conflicts. Unfortunately, this extra s…
Compilation Techniques for Graph Algorithms on GPUs
Ajay Brahmakshatriya, Yunming Zhang, Changwan Hong +3
The performance of graph programs depends highly on the algorithm, the size and structure of the input graphs, as well as the features of the underlying hardware. No single set of…
Exploring the Design Space of Static and Incremental Graph Connectivity Algorithms on GPUs
Changwan Hong, Laxman Dhulipala, Julian Shun
Connected components and spanning forest are fundamental graph algorithms due to their use in many important applications, such as graph clustering and image segmentation. GPUs are…
ConnectIt: A Framework for Static and Incremental Parallel Graph Connectivity Algorithms
Laxman Dhulipala, Changwan Hong, Julian Shun
Connected components is a fundamental kernel in graph applications. The fastest existing parallel multicore algorithms for connectivity are based on some form of edge sampling and/…
Sage: Parallel Semi-Asymmetric Graph Algorithms for NVRAMs
Laxman Dhulipala, Charlie McGuffey, Hongbo Kang +4
Non-volatile main memory (NVRAM) technologies provide an attractive set of features for large-scale graph analytics, including byte-addressability, low idle power, and improved mem…
Parallel Algorithms for Butterfly Computations
Jessica Shi, Julian Shun
Butterflies are the smallest non-trivial subgraph in bipartite graphs, and therefore having efficient computations for analyzing them is crucial to improving the quality of certain…
Low-Latency Graph Streaming Using Compressed Purely-Functional Trees
Laxman Dhulipala, Julian Shun, Guy Blelloch
Due to the dynamic nature of real-world graphs, there has been a growing interest in the graph-streaming setting where a continuous stream of graph updates is mixed with arbitrary…
The Parallel Persistent Memory Model
Guy E. Blelloch, Phillip B. Gibbons, Yan Gu +2
We consider a parallel computational model that consists of processors, each with a fast local ephemeral memory of limited size, and sharing a large persistent memory. The mode…
Improved Parallel Construction of Wavelet Trees and Rank/Select Structures
Julian Shun
Existing parallel algorithms for wavelet tree construction have a work complexity of . This paper presents parallel algorithms for the problem with improved work complex…