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GAMT: A Fast and Scalable GPU-Based IP Lookup Engine for Software Routers

GAMT (GPU-Accelerated Multi-bit Trie) is designed to improve IP lookup performance for software routers by leveraging GPU computing. Compared to previous models, GAMT efficiently scales to IPv6 and maintains stable lookup throughput, even under frequent updates. Through the use of an optimized multi-bit trie structure and performance enhancements, this engine mitigates latency and enhances speed for dynamic data environments. The design principles and experimental results demonstrate GAMT's capacity to surpass existing solutions in efficiency and adaptability.

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GAMT: A Fast and Scalable GPU-Based IP Lookup Engine for Software Routers

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  1. GAMT: A Fast and Scalable IP Lookup Engine forGPU-based Software Routers Author: YanbiaoLi, DafangZhang, Alex X. Liu and Jintao Zheng Publisher: ANCS 2013 Presenter: Yu Hao, Tseng Date: 2013/11/13

  2. Outline • Introduction • Background and Related Work • GPU-Accelerated Lookup Engine • GPU-accelerated Multi-bit Trie • Performance Optimization • Experimental Evaluation

  3. Introduction • The GPU is becoming an emerging platform for high performance general-purpose computing. • J. Zhao et al. [27] - GPU-Accelerated Lookup Engine (GALE) • only applicable for IPv4 • decline sharply with the increase of update frequency • GPU-Accelerated Multi-bit Trie (GAMT) • Scale to IPv6 smoothly • Keep stable lookup throughput under highly frequent updates • Improve lookup performance with latency controlled

  4. Background and Related Work • Multi-bit Trie

  5. Background and Related Work (Cont.) • CUDA Programming Model • Coalescence of Global Memory Accesses • Overlapping Behaviors on the GPU • GPU-Accelerated IP Lookup Engine

  6. GPU-Accelerated Lookup Engine

  7. GPU-accelerated Multi-bit Trie • Encoding Rules and Lookup Approach

  8. GPU-accelerated Multi-bit Trie (Cont.) • Encoding Rules and Lookup Approach • Ex : 10001* • Step 1. Default (inf, jump) = (0, 1) • Step 2. (inf, jump) = (0 + 1, 1) = (1, 1) => (inf, jump) = (0, 2) • Step 3. (inf, jump) = (0 + 0, 2) = (0, 2) => (inf, jump) = (0, 3) • Step 4. (inf, jump) = (0 + 1, 3) = (1, 3) => (inf, jump) = (5, 0)

  9. GPU-accelerated Multi-bit Trie (Cont.) • Encoding Rules and Lookup Approach

  10. GPU-accelerated Multi-bit Trie (Cont.) • Update Mechanism

  11. GPU-accelerated Multi-bit Trie (Cont.) • Update Mechanism

  12. GPU-accelerated Multi-bit Trie (Cont.) • Architecture Overview

  13. Performance Optimization • Possibility of being Faster than GALE

  14. Performance Optimization (Cont.) • Optimized Multi-bit Trie

  15. Performance Optimization (Cont.) • Optimized Multi-bit Trie

  16. Performance Optimization (Cont.) • Delete in Lazy Mode • Multi-Stream Pipeline

  17. Experimental Evaluation • Evaluation Methodology

  18. Experimental Evaluation (Cont.) • Evaluation Methodology

  19. Experimental Evaluation (Cont.) • Lookup Performance

  20. Experimental Evaluation (Cont.) • Lookup Performance

  21. Experimental Evaluation (Cont.) • Lookup Performance

  22. Experimental Evaluation (Cont.) • Update Overhead

  23. Experimental Evaluation (Cont.) • Comprehensive Performance

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