Multi-GPU Approach for Development of Parallel and Scalable Pub-Sub System

  • Medha A. ShahEmail author
  • Dinesh Kulkarni
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 810)


Event matching plays an important part in the overall attainment of the content-based Publish-Subscribe system. These systems demand guaranteed message delivery, high throughput and low matching time. Existing parallel content matching algorithms make use of multiple cores and off the shelf hardware easily available in today’s modern computers. For a large number of events and subscriptions, these algorithms suffer from performance degradation. In this paper, we propose high-performance Publish-Subscribe system designed to run efficiently on multiple GPUs. Performance comparison with existing CCM (CUDA Content Matching) algorithm clearly demonstrates 32% improvement in matching latency.


High performance Parallel matching algorithm Multiple GPUs Matching latency 


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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Department of CSEWalchand College of EngineeringSangliIndia
  2. 2.Department of Information TechnologyWalchand College of EngineeringSangliIndia

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