论文标题
在矿业库中的合作策略,以获得神经架构的共识
A Collaboration Strategy in the Mining Pool for Proof-of-Neural-Architecture Consensus
论文作者
论文摘要
在最受欢迎的公共可访问的加密货币系统中,采矿池起着关键作用,因为采矿池的采矿加密货币将非营利性的情况变成了个人矿工的盈利。在最近的许多新型区块链共识中,深度学习训练程序成为矿工证明其工作量的任务,因此矿工的计算能力不会纯粹用于哈希难题。这样,硬件和能源将同时支持区块链服务和深度学习培训。虽然矿工的动机是赚取代币,但个别矿工仍有动力加入采矿池以变得更有竞争力。在本文中,我们是第一个为基于深度学习的新颖共识而展示采矿池解决方案的人。 采矿池管理器将完整的搜索空间分配到子空间中,并计划在分配的子空间中的神经体系结构搜索(NAS)任务进行协作。实验表明,这种采矿库的性能比单个矿工更具竞争力。由于矿工行为的不确定性,采矿泳池经理检查了高奖励矿工表现的标准偏差,并准备备用矿工,以确保完成高奖励矿工的任务。
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.