Accelerating Blockchain Search of Full Nodes Using GPUs

Abstract

Blockchain is a distributed ledger system based on P2P network and originally used for a crypto currency system. The P2P network of Blockchain is maintained by full nodes which are in charge of verifying all the transactions in the network. However, most Blockchain user nodes do not act as full nodes, because workload of full nodes is quite high for personal mobile devices. Blockchain search queries, such as confirming balance, transaction contents, and transaction histories, from many users go to the full nodes. As a result, search throughput of full nodes would be a new bottleneck of Blockchain system, because the number of full nodes is less than the number of users of Blockchain systems. In this paper, we propose an acceleration method of Blockchain search using GPUs. More specifically, we introduce an array-based Patricia tree structure suitable for GPU processing so that we can make effective use of Blockchain feature that there are no update and delete queries. In the evaluations, the proposed method is compared with an existing GPU-based key-value search and a conventional CPU-based search in terms of the throughput of Blockchain key search. As a result, the throughput of our proposal is 3.4 times higher than that of the existing GPU-based search and 14.1 times higher than that of the CPU search when the number of keys is 80 ×2^20 and the key length is 256-bit in Blockchain search queries.