A mining pool solution for novel proof-of-neural-architecture consensus

Abstract

In many recent novel blockchain consensuses, deep learning training procedure becomes the task for miners to prove their workload, thus the computation power of miners will not purely be spent on the hash puzzle. Therefore, the hardware and energy will support the blockchain service and deep learning training at the same time. The incentive of miners is to earn tokens and individual miners will find mining pools become more competitive. To the best of our knowledgeWe are the first to demonstrate a mining pool solution for novel consensuses based on deep learning. This work adopts from exist Proof-of-Deep-Learning (PoDL) as the consensus and Neural Architecture Search (NAS) as the workload. The mining pool manager partitions the full searching space into subspaces and all miners contributes to the NAS task in the assigned tasks. The strong miners are assigned for exploration and the weak miners are assigned for exploitation. In section IV, it shows the performance of this mining pool is more competitive than an individual miner in conducting NAS as workload.