High-performance multi/many-core network processing architectures with shared and private queues

Abstract

Nowadays, the efficient and probabilistic datastructure named Bloom filter is widely used in network processing applications. Moreover, the parallel nature of Bloom filter has made it suitable for multi/many-core architectures. In this paper, two schemes called multi-core architecture with shared queue and multi-core architecture with private queue (both employing Bloom filter cores) are proposed and implemented on FPGA. The inherent parallelism in querying of packets and different number of cores (such as 1, 2, 4, 8 and 16 cores) are considered. Experimental results show that the multicore architecture with private queue achieves higher throughput than the latter one. Furthermore, Bloom filter is also implemented on GPU (as many-core architecture) and the results are compared to the CPU only version. When the number of packets in GPU memory is 16384, the speedup achieved by GPU implementations using CUDA is about 274 times compared to CPU implementation. However FPGA results outperform GPU, so that the throughput of first architecture (shared queue) and second architecture (private queue) with 16 cores are respectively almost 5.5 and 7.1 times higher than GPU throughput.