Proof-of-work algorithm optimization method and device, computer equipment and storage medium

Abstract

The invention provides a proof-of-work algorithm optimization method and device, computer equipment and a storage medium. The method comprises the steps that multiple first index values and primary random numbers corresponding to the first index values are obtained through calculation according to secondary seed values of the current round; obtaining a first index value corresponding to the maximum number of the primary random numbers, and determining the first index value as a second index value; extracting directed acyclic data from a directed acyclic graph; and according to the secondary seed value and the directed acyclic data, calculating to obtain a secondary seed value of the next round. After the corresponding relation between the first index values and the primary random numbers is obtained through calculation, data are extracted from the directed acyclic graph by taking the first index value corresponding to the most primary random number as a second index value, and calculation of secondary seed values of the next round is carried out according to the data until 64 rounds are finished. The calculation efficiency of the mixing step in the ethash algorithm can be effectively improved, the delay is reduced, and the memory bandwidth bottleneck is relieved, so that the workload proving algorithm is optimized.

Description

technical field [0001] The invention relates to the technical field of proof-of-work, in particular to a proof-of-work algorithm optimization method, device, computer equipment and storage medium. Background technique [0002] The essence of POW (Proof of Work) is to solve a mathematically difficult problem based on computing power. The key point of solving the problem is that there is no way to find the nonce value we need except for violent enumeration, but for the verification output The result is very simple and easy. [0003] The ethash algorithm is a memory-hard function algorithm. During the operation process, the algorithm needs to repeatedly extract a large amount of data randomly from the memory for operation, and find a nonce (Number once, a random number) value to input into the algorithm. , resulting in results below a threshold based on a certain difficulty value. It can be seen from the above description that the performance bottleneck of the Ethash algorith...

AI Technical Summary

Problems solved by technology

[0004] Due to the essential characteristics of the Memory-hard algorithm, memory read bandwidth becomes a performance bottleneck

In addition, because the traditional architecture is based on centralized memory storage, the distributed computing core requests data from the central memory to generate delays. Unlike the hash calculation with a fixed computing cycle in the algorithm, the running cycle required to extract data is unpredictable, resulting in System performance degradation

Images