Journal Article10.1109/TETC.2015.2460453
IP Address Lookup by Using GPU
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TL;DR: An IPv6-capable data structure is proposed and an CUDA-based IP forwarding engine with the proposed approach has the capability of GPPS IP forwarding rate on a low-end CUDA device by employing dual data structures.
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Abstract: We present a novel parallel IP address lookup architecture based on graphics processing unit (GPU) via compute unified device architecture (CUDA). Our architecture consists of two functions: 1) host function and 2) device function. The host function is executed by a CPU to construct and update the data structure of IP address lookup executed by the device function in a GPU. Both host and device functions are executed simultaneously to fully utilize computational resources. To shorten the lookup time, a trie-based data structure optimized for CUDA is developed. The trie-based data structure uses multi-bit stride to shorten the trie depth and also improves the efficiency of texture cache in GPUs. The experimental results show that a low-end G92 GPU can achieve a throughput of more than 1.3 billion packets per second for IPv4 routing tables with more than 350K prefixes while a high-end GT200 GPU can further double the performance. By employing dual data structures, the implementation can support several hundred thousand updates per second.
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Citations
Exploiting integrated GPUs for network packet processing workloads
Janet Tseng,Ren Wang,James Tsai,Saikrishna Edupuganti,Alexander W. Min,Shinae Woo,Stephen Junkins,Tsung-Yuan Charlie Tai +7 more
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Scalable GPU-Accelerated IPv6 Lookup Using Hierarchical Perfect Hashing
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- 01 Dec 2014
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8
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High Performance IP Address Lookup Using GPU
Junghwan Kim,Jinsoo Kim +1 more
TL;DR: A data structure for multibit trie to exploit GPU hardware efficiently and a novel scheme that the root subtrie is loaded on Shared Memory which is specialized for fast access in GPU improves the lookup performance.
2
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Fast address lookups using controlled prefix expansion
V. Srinivasan,George Varghese +1 more
TL;DR: The main technique, controlled prefix expansion, transforms a set of prefixes into an equivalent set with fewer prefix lengths, and optimization techniques based on dynamic programming, and local transformations of data structures to improve cache behavior are used.