Parallel Vertex Color Update on Large Dynamic Networks

We present the first GPU-based parallel algorithm to efficiently update vertex coloring on large dynamic networks. For single GPU, we introduce the concept of loosely maintained vertex color update that reduces computation and memory requirements. For multiple GPUs, in distributed environments, we p...

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Veröffentlicht in:Proceedings - International Conference on High Performance Computing S. 115 - 124
Hauptverfasser: Khanda, Arindam, Bhowmick, Sanjukta, Liang, Xin, Das, Sajal K.
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 01.12.2022
Schlagworte:
Dynamic networks
Graphics processing units
Heuristic algorithms
High performance computing
Image color analysis
Kernel
Memory management
Parallel algorithms
Parallel/distributed algorithm
Vertex coloring
ISSN:2640-0316
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Abstract We present the first GPU-based parallel algorithm to efficiently update vertex coloring on large dynamic networks. For single GPU, we introduce the concept of loosely maintained vertex color update that reduces computation and memory requirements. For multiple GPUs, in distributed environments, we propose priority-based ordering of vertices to reduce the communication time. We prove the correctness of our algorithms and experimentally demonstrate that for graphs of over 16 million vertices and over 134 million edges on a single GPU, our dynamic algorithm is as much as 20x faster than state-of-the-art algorithm on static graphs. For larger graphs with over 130 million vertices and over 260 million edges, our distributed implementation with 8 GPUs produces updated color assignments within 160 milliseconds. In all cases, the proposed parallel algorithms produce comparable or fewer colors than state-of-the-art algorithms.
AbstractList We present the first GPU-based parallel algorithm to efficiently update vertex coloring on large dynamic networks. For single GPU, we introduce the concept of loosely maintained vertex color update that reduces computation and memory requirements. For multiple GPUs, in distributed environments, we propose priority-based ordering of vertices to reduce the communication time. We prove the correctness of our algorithms and experimentally demonstrate that for graphs of over 16 million vertices and over 134 million edges on a single GPU, our dynamic algorithm is as much as 20x faster than state-of-the-art algorithm on static graphs. For larger graphs with over 130 million vertices and over 260 million edges, our distributed implementation with 8 GPUs produces updated color assignments within 160 milliseconds. In all cases, the proposed parallel algorithms produce comparable or fewer colors than state-of-the-art algorithms.
Author Khanda, Arindam
Liang, Xin
Das, Sajal K.
Bhowmick, Sanjukta
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  surname: Khanda
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  givenname: Sanjukta
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  givenname: Xin
  surname: Liang
  fullname: Liang, Xin
  email: xliang@mst.edu
  organization: Missouri University of Science and Technology,Rolla,USA
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  givenname: Sajal K.
  surname: Das
  fullname: Das, Sajal K.
  email: sdas@mst.edu
  organization: Missouri University of Science and Technology,Rolla,USA
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Snippet We present the first GPU-based parallel algorithm to efficiently update vertex coloring on large dynamic networks. For single GPU, we introduce the concept of...
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StartPage 115
SubjectTerms Dynamic networks
Graphics processing units
Heuristic algorithms
High performance computing
Image color analysis
Kernel
Memory management
Parallel algorithms
Parallel/distributed algorithm
Vertex coloring
Title Parallel Vertex Color Update on Large Dynamic Networks
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