Skip to Main Content
Efficiently locating information in large-scale distributed systems is a challenging problem to which Peer-to-Peer (P2P) Distributed Hash Tables (DHTs) can provide a highly scalable and cost-effective solution. However, there is very little experience on using DHTs in performance sensitive environments such as High Performance Computing (HPC) datacenters, and there is no published experimental comparison among low-latency DHTs. To fill this gap, we conducted an in-depth performance comparison of three proposed low-latency single-hop DHTs namely 1h-Calot, D1HT, and OneHop. Specifically, we compared experimentally the lookup latency and CPU use of D1HT with those of 1h-Calot by running each of them concurrently with the normal workload production for a subset of 1,800 nodes of a heavy-loaded HPC datacenter. In addition, we carried out an analytical performance comparison among the three single-hop DHTs for system sizes of up to 10 million nodes. The results showed that D1HT consistently had the smallest overhead and in most cases it required one order of magnitude less bandwidth than 1h-Calot and OneHop. Overall, the combination of our experimental and analytical results suggests that D1HT can provide a very effective solution for a broad range of environments, from large-scale HPC datacenters to widely deployed Internet P2P applications such as BitTorrent with up to one million peers. This ability to support such a wide range of environments may allow D1HT to be used as an inexpensive and scalable commodity software substrate for large-scale distributed applications.