Search Results - Graph algorithms and analysis

Skywalker: Efficient Alias-Method-Based Graph Sampling and Random Walk on GPUs by Wang, Pengyu, Li, Chao, Wang, Jing, Wang, Taolei, Zhang, Lu, Leng, Jingwen, Chen, Quan, Guo, Minyi

“…Graph sampling and random walk operations, capturing the structural properties of graphs, are playing an important role today as we cannot directly adopt computing-intensive algorithms on large-scale graphs…”
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BlasPart: A Deterministic Parallel Partitioner for Balanced Large-Scale Hypergraph Partitioning by Tong, Shengbo, Pei, Chunyan, Yu, Wenjian

“… Thus, fast and high-quality deterministic partitioning algorithms are largely in demand…”
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ParGNN: A Scalable Graph Neural Network Training Framework on multi-GPUs by Gu, Junyu, Li, Shunde, Cao, Rongqiang, Wang, Jue, Wang, Zijian, Liang, Zhiqiang, Liu, Fang, Li, Shigang, Zhou, Chunbao, Wang, Yangang, Chi, Xuebin

“…Full-batch Graph Neural Network (GNN) training is indispensable for interdisciplinary applications…”
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DS-GL: Advancing Graph Learning via Harnessing Nature's Power within Scalable Dynamical Systems by Song, Ruibing, Wu, Chunshu, Liu, Chuan, Li, Ang, Huang, Michael, Geng, Tony Tong

“…With the rapid digitization of the world, an increasing number of real-world applications are turning to non-Euclidean data, modeled as graphs…”
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PIMGCN: A ReRAM-Based PIM Design for Graph Convolutional Network Acceleration by Yang, Tao, Li, Dongyue, Han, Yibo, Zhao, Yilong, Liu, Fangxin, Liang, Xiaoyao, He, Zhezhi, Jiang, Li

“…Graph Convolutional Network (GCN) is a promising but computing- and memory-intensive learning model…”
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DyGNN: Algorithm and Architecture Support of Dynamic Pruning for Graph Neural Networks by Chen, Cen, Li, Kenli, Zou, Xiaofeng, Li, Yangfan

“…Recently, graph neural networks (GNNs) have achieved great success for graph representation learning tasks…”
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iG-kway: Incremental k-way Graph Partitioning on GPU by Lee, Wan Luan, Jiang, Shui, Lin, Dian-Lun, Chang, Che, Zhang, Boyang, Chung, Yi-Hua, Schlichtmann, Ulf, Ho, Tsung-Yi, Huang, Tsung-Wei

“…Recent advances in GPU-accelerated graph partitioning have achieved significant performance gains but remain limited to full graph partitioning, lacking support for incremental updates…”
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GPart: A GNN-Enabled Multilevel Graph Partitioner by Chen, Magi, Wang, Ting-Chi

“…This paper introduces GPart, a scalable multilevel framework for graph partitioning that integrates GNN embeddings with efficient coarsening and refinement techniques…”
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SumPA: Efficient Pattern-Centric Graph Mining with Pattern Abstraction by Gui, Chuangyi, Liao, Xiaofei, Zheng, Long, Yao, Pengcheng, Wang, Qinggang, Jin, Hai

“…Graph mining aims to explore interesting structural information of a graph. Pattern-centric systems typically transform a generic-purpose graph mining problem into a series of subgraph matching problems for high performance…”
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LearnGraph: A Learning-Based Architecture for Dynamic Graph Processing by Zhang, Lingling, Wu, Yijian, Jiang, Hong, Zhou, Ziyu, Lu, Tiancheng

“…Dynamic graph processing systems using conventional array-based architectures face significant throughput limitations due to inefficient memory access and index management…”
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EMGraph: Fast Learning-Based Electromigration Analysis for Multi-Segment Interconnect Using Graph Convolution Networks by Jin, Wentian, Chen, Liang, Sadiqbatcha, Sheriff, Peng, Shaoyi, Tan, Sheldon X.-D.

“… VLSI multisegment interconnect trees can be naturally viewed as graphs. Based on this observation, we propose a new graph convolution network (GCN…”
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ACGraph: Accelerating Streaming Graph Processing via Dependence Hierarchy by Jiang, Zihan, Mao, Fubing, Guo, Yapu, Liu, Xu, Liu, Haikun, Liao, Xiaofei, Jin, Hai, Zhang, Wei

“… To address this issue, we propose ACGraph, a novel streaming graph processing approach for monotonic graph algorithms…”
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Parallelizing Maximal Clique Enumeration on GPUs by Almasri, Mohammad, Chang, Yen-Hsiang, Hajj, Izzat El, Nagi, Rakesh, Xiong, Jinjun, Hwu, Wen-mei

“…We present a GPU solution for exact maximal clique enumeration (MCE) that performs a search tree traversal following the Bron-Kerbosch algorithm…”
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Anchor First, Accelerate Next: Revolutionizing GNNs with PIM by Harnessing Stationary Data by Chen, Jiaxian, Qi, Yuxuan, Zhu, Yongbiao, Yuan, Jianan, Sun, Kaoyi, Wang, Tianyu, Ma, Chenlin, Wang, Yi

“…Substantial data movement caused by irregular graph topologies hinders the efficient processing of graph neural networks (GNNs…”
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PSMiner: A Pattern-Aware Accelerator for High-Performance Streaming Graph Pattern Mining by Qi, Hao, Zhang, Yu, He, Ligang, Luo, Kang, Huang, Jun, Lu, Haoyu, Zhao, Jin, Jin, Hai

“…Streaming Graph Pattern Mining (GPM) has been widely used in many application fields…”
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Synchronization in graph analysis algorithms on the Partially Ordered Event‐Triggered Systems many‐core architecture by Rafiev, Ashur, Yakovlev, Alex, Tarawneh, Ghaith, Naylor, Matthew F., Moore, Simon W., Thomas, David B., Bragg, Graeme M., Vousden, Mark L., Brown, Andrew D.

“…One of the key problems in designing and implementing graph analysis algorithms for distributed platforms is to find an optimal way of managing communication flows in the massively parallel processing network. Message…”
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SGIRR: Sparse Graph Index Remapping for ReRAM Crossbar Operation Unit and Power Optimization by Wang, Cheng-Yuan, Chang, Yao-Wen, Chang, Yuan-Hao

“… This paper proposes a two-stage algorithm with a crossbar OU-aware scheme for sparse graph index remapping for ReRAM (SGIRR…”
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Dynamic Allocation of Processor Cores to Graph Applications on Commodity Servers by Pons, Lucia, Sahuauillo, Julio, Jones, Timothy M.

“…Graph processing is increasingly adopted to solve problems that span many application domains, including scientific computing, social networks, and big-data analytics…”
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Late Breaking Results: An Efficient and Scalable Track Assignment with GPU Parallelism by Liu, Genggeng, Huang, Pengcheng, Li, Zepeng, Liu, Wen-Hao, Huang, Xing, Guo, Wenzhong

“… Based on the independence and divisibility of track assignment, we propose a GPU-accelerated parallel track assignment algorithm…”
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SAGA: A Memory-Efficient Accelerator for GANN Construction via Harnessing Vertex Similarity by Chen, Ruiyang, Liu, Xueyuan, Qi, Chunyu, Yao, Yuanzheng, Sun, Yanan, Liang, Xiaoyao, Song, Zhuoran

“…Graph-traversal-based Approximate Nearest Neighbor (GANN) search and construction have become key retrieval techniques in various domains, such as recommendation systems and social networks…”
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