首页> 外文期刊>Symmetry >A Distributed Snapshot Protocol for Efficient Artificial Intelligence Computation in Cloud Computing Environments
【24h】

A Distributed Snapshot Protocol for Efficient Artificial Intelligence Computation in Cloud Computing Environments

机译:云计算环境中用于高效人工智能计算的分布式快照协议

获取原文
           

摘要

Many artificial intelligence applications often require a huge amount of computing resources. As a result, cloud computing adoption rates are increasing in the artificial intelligence field. To support the demand for artificial intelligence applications and guarantee the service level agreement, cloud computing should provide not only computing resources but also fundamental mechanisms for efficient computing. In this regard, a snapshot protocol has been used to create a consistent snapshot of the global state in cloud computing environments. However, the existing snapshot protocols are not optimized in the context of artificial intelligence applications, where large-scale iterative computation is the norm. In this paper, we present a distributed snapshot protocol for efficient artificial intelligence computation in cloud computing environments. The proposed snapshot protocol is based on a distributed algorithm to run interconnected multiple nodes in a scalable fashion. Our snapshot protocol is able to deal with artificial intelligence applications, in which a large number of computing nodes are running. We reveal that our distributed snapshot protocol guarantees the correctness, safety, and liveness conditions.
机译:许多人工智能应用程序通常需要大量的计算资源。结果,在人工智能领域,云计算的采用率正在增加。为了满足对人工智能应用程序的需求并确保服务水平协议,云计算不仅应提供计算资源,还应提供有效计算的基本机制。在这方面,快照协议已用于在云计算环境中创建全局状态的一致快照。但是,现有的快照协议并未在人工智能应用程序的上下文中进行优化,在人工智能应用程序中,大规模迭代计算已成为常态。在本文中,我们提出了一种分布式快照协议,用于在云计算环境中进行高效的人工智能计算。所提出的快照协议基于分布式算法,以可扩展的方式运行互连的多个节点。我们的快照协议能够处理运行大量计算节点的人工智能应用程序。我们发现,我们的分布式快照协议保证了正确性,安全性和活跃性条件。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号