  In most popular public accessible cryptocurrency systems, the mining pool
plays a key role because mining cryptocurrency with the mining pool turns the
non-profitable situation into profitable for individual miners. In many recent
novel blockchain consensuses, the 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. In this way, the hardware and
energy will support the blockchain service and deep learning training
simultaneously. While the incentive of miners is to earn tokens, individual
miners are motivated to join mining pools to become more competitive. In this
paper, we are the first to demonstrate a mining pool solution for novel
consensuses based on deep learning.
  The mining pool manager partitions the full searching space into subspaces
and all miners are scheduled to collaborate on the Neural Architecture Search
(NAS) tasks in the assigned subspace. Experiments demonstrate that the
performance of this type of mining pool is more competitive than an individual
miner. Due to the uncertainty of miners' behaviors, the mining pool manager
checks the standard deviation of the performance of high reward miners and
prepares backup miners to ensure the completion of the tasks of high reward
miners.
