Memory Aware Packet Matching Architecture for High-Speed Networks

TLDR: This paper proposes a novel parallel hardware architecture for hash-based exact match classification of multiple packets per clock cycle with reduced memory replication requirements and shows that the proposed approach can use memory very efficiently and scales exceptionally well with increased record capacities.

Abstract: Packet classification is a crucial operation for many different networking tasks ranging from switching or routing to monitoring and security devices like firewall or IDS. Generally, accelerated architectures implementing packet classification must be used to satisfy ever-growing demands of current high-speed networks. Furthermore, to keep up with the rising network throughputs, the accelerated architectures for FPGAs must be able to classify more than one packet in each clock cycle. This can be mainly achieved by utilization of multiple processing pipelines in parallel, what brings replication of FPGA logic and more importantly scarce on-chip memory resources. Therefore in this paper, we propose a novel parallel hardware architecture for hash-based exact match classification of multiple packets per clock cycle with reduced memory replication requirements. The basic idea is to leverage the fact that modern FPGAs offer hundreds of BlockRAM tiles that can be accessed (addressed) independently to maintain high throughput of matching even without fully replicated memory architecture. Our results show that the proposed approach can use memory very efficiently and scales exceptionally well with increased record capacities. For example, the designed architecture is able to achieve throughput of more than 2 Tbps (over 3 000 Mpps) with an effective capacity of more than 40 000 IPv4 flow records for the cost of only 366 BlockRAM tiles and around 57 000 LUTs.