A space- and time-efficient hash table hierarchically indexed by bloom filters
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Hash tables (HTs) are poorly designed for multiple memory accesses during IP lookup and this design flow critically affects their throughput in high-speed routers. Thus, a high capacity HT with a predictable lookup throughput is desirable. A recently proposed fast HT (FHT) [20] has drawbacks like low on-chip memory utilization for a high-speed router and substantial memory overheads due to off-chip duplicate keys and pointers. Similarly, a Bloomier filter-based HT (BFHT) [13], generating an index to a key table, suffers from setup failures and static membership testing for keys. In this paper, we propose a novel hash architecture which addresses these issues by using pipelined Bloom filters. The proposed scheme, a hierarchically indexed HT (HIHT), generates indexes to a key table for the given key, so that the on-chip memory size is reduced and the overhead of pointers in a linked list is removed. Secondly, an HIHT demonstrates approximately 5.1 and 2.3 times improvement in onchip space efficiency with at most one off-chip memory access, compared to an FHT and a BFHT, respectively. In addition to our analyses on access time and memory space, our simulation for IP lookup with 6 BGP tables shows that an HIHT exhibits 4.5 and 2.0 times on-chip memory efficiencies for 160Gbps router than an FHT and a BFHT, respectively. 2008 IEEE.
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2008 IEEE International Symposium on Parallel and Distributed Processing
