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The convex hull is a fundamental geometrical structure for many applications where groups of points must be enclosed or represented by a convex polygon. Although efficient sequential convex hull algorithms exist, and are constantly being…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-09-27 Alan Keith , Héctor Ferrada , Cristóbal A. Navarro

Recently, considerable efforts have been devoted to approximately computing the global and local (i.e., incident to each node) triangle counts of a large graph stream represented as a sequence of edges. Existing approximate triangle…

Data Structures and Algorithms · Computer Science 2018-11-27 Pinghui Wang , Peng Jia , Yiyan Qi , Yu Sun , Jing Tao , Xiaohong Guan

One area of Computing applications which poses significant challenge of performance scalability on Chip Multiprocessors(CMP's) are Irregular applications. Such applications have very little computation and unpredictable memory access…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-03-09 Varun Nagpal

The problem of computing the Betweenness Centrality (BC) is important in analyzing graphs in many practical applications like social networks, biological networks, transportation networks, electrical circuits, etc. Since this problem is…

Social and Information Networks · Computer Science 2014-09-30 Saad Quader

Graph analytics for large scale graphs has gained interest in recent years. Many graph algorithms have been designed for vertex-centric distributed graph processing frameworks to operate on large graphs with 100 M vertices and edges, using…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-05-21 Diptanshu Kakwani , Yogesh Simmhan

Graph processing at scale presents many challenges, including the irregular structure of graphs, the latency-bound nature of graph algorithms, and the overhead associated with distributed execution. While existing frameworks such as Spark…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-03-06 Karame Mohammadiporshokooh , Panagiotis Syskakis , Andrew Lumsdaine , Hartmut Kaiser

Not only with the large host memory for supporting large scale graph processing, GPU-accelerated heterogeneous architecture can also provide a great potential for high-performance computing. However, few existing heterogeneous systems can…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-06-05 Xianliang Li

Counting k-cliques in a graph is an important problem in graph analysis with many applications such as community detection and graph partitioning. Counting k-cliques is typically done by traversing search trees starting at each vertex in…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-06-07 Mohammad Almasri , Izzat El Hajj , Rakesh Nagi , Jinjun Xiong , Wen-mei Hwu

A $k$-truss is an edge-induced subgraph $H$ such that each of its edges belongs to at least $k-2$ triangles of $H$. This notion has been introduced around ten years ago in social network analysis and security, as a form of cohesive subgraph…

Data Structures and Algorithms · Computer Science 2020-10-05 Alessio Conte , Roberto Grossi , Andrea Marino , Luca Versari

In this paper we present improved results on the problem of counting triangles in edge streamed graphs. For graphs with $m$ edges and at least $T$ triangles, we show that an extra look over the stream yields a two-pass treaming algorithm…

Data Structures and Algorithms · Computer Science 2016-03-10 Graham Cormode , Hossein Jowhari

Edge-centric distributed computations have appeared as a recent technique to improve the shortcomings of think-like-a-vertex algorithms on large scale-free networks. In order to increase parallelism on this model, edge partitioning -…

Data Structures and Algorithms · Computer Science 2018-10-12 Sebastian Schlag , Christian Schulz , Daniel Seemaier , Darren Strash

Breadth-First Search (BFS) is a fundamental graph kernel that underpins a wide range of applications. While modern GPUs provide specialised Matrix-Multiply-Accumulate (MMA) units, e.g., Tensor Cores (TC), with extremely high throughput,…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-12-29 Deniz Elbek , Kamer Kaya

Hypergraph partitioning is a pervasive NP-hard problem, and accelerating its computation on GPU can both slice time-to-solution and raise quality of results. In this work, we implement a multi-level hypergraph partitioning algorithm on GPU…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-04-17 Marco Ronzani , Cristina Silvano

Modern graphics computing units (GPUs) are designed and optimized to perform highly parallel numerical calculations. This parallelism has enabled (and promises) significant advantages, both in terms of energy performance and calculation. In…

Hardware Architecture · Computer Science 2021-10-26 Quentin Gallouédec

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 an ideal platform for graph algorithms due to their high…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-08-28 Changwan Hong , Laxman Dhulipala , Julian Shun

Ray tracing (RT) is a 3D graphics technique that offers highly realistic visuals. It is becoming prominent and accessible as GPU vendors have integrated dedicated ray tracing acceleration hardware. However, tracing millions of rays through…

Hardware Architecture · Computer Science 2026-05-18 Yavuz Selim Tozlu , Anshul Naithani , Huiyang Zhou

The number of triangles (hereafter denoted by $\Delta$) is an important metric to analyze massive graphs. It is also used to compute clustering coefficient in networks. This paper proposes a new algorithm called PES (Priority Edge Sampling)…

Social and Information Networks · Computer Science 2020-08-20 Roohollah Etemadi , Jianguo Lu

Triangle counting is a key algorithm for large graph analysis. The Graphulo library provides a framework for implementing graph algorithms on the Apache Accumulo distributed database. In this work we adapt two algorithms for counting…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-11-09 Dylan Hutchison

The number of cores on graphical computing units (GPUs) is reaching thousands nowadays, whereas the clock speed of processors stagnates. Unfortunately, constraint programming solvers do not take advantage yet of GPU parallelism. One reason…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-07-26 Pierre Talbot , Frédéric Pinel , Pascal Bouvry

Listing all triangles is a fundamental graph operation. Triangles can have important interpretations in real-world graphs, especially social and other interaction networks. Despite the lack of provably efficient (linear, or slightly…

Social and Information Networks · Computer Science 2014-07-07 Jonathan W. Berry , Luke A. Fostvedt , Daniel J. Nordman , Cynthia A. Phillips , C. Seshadhri , Alyson G. Wilson