| 深度学习云服务适配问题研究 |
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| 引用本文： | 林 健,谢冬鸣,余 波.深度学习云服务适配问题研究[J].教育技术导刊,2020,19(6):1-8. |
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| 作者姓名： | 林 健 谢冬鸣 余 波 |
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| 作者单位： | 东云睿连（武汉）计算技术有限公司，湖北 武汉 430200 |
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| 摘 要： | 深度学习技术是支撑众多人工智能应用的基础，云服务是当今主流的计算能力供给模式。以云服务方式提供深度学习能力广受关注，构建这类服务的关键在于深度学习业务向云服务模式适配，具体涉及作业调度、存储接入和资源管理等方面的兼容性问题与适配型特性研发。OMAI 深度学习平台将深度学习业务云服务化，通过作业调度中间层抽象、异构存储容器内挂载、资源表达式匹配等机制，有效解决了深度学习业务的云服务适配问题。OMAI 为人工智能云服务研发提供指导路。
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| 关 键 词： | 深度学习 人工智能 云服务 高性能计算 平台软件 |
| 收稿时间： | 2020-02-19 |
Research on Cloud Service Adaptation of Deep Learning |
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| LIN Jian,XIE Dong-ming,YU Bo.Research on Cloud Service Adaptation of Deep Learning[J].Introduction of Educational Technology,2020,19(6):1-8. |
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| Authors: | LIN Jian XIE Dong-ming YU Bo |
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| Institution: | Oriental Mind（Wuhan）Computing Technology Co.，Ltd.，Wuhan 430200，China |
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| Abstract: | Deep learning is the foundation that enables many artificial intelligence applications. Cloud service is the mainstream provisioning mode of computing power today. Providing deep learning capabili-ties by using cloud services has received widespread attention from major cloud vendors. The key to constructing such services is the adaptation of deep learning workload to cloud service models，
which involves the compatibility issues and adaptive developments of job scheduling，storage access，and resource management. OMAI deep learning platform performs a practice of adapting deep learning as a service on the cloud. It effectively solves the cloud service adaptation problem of deep learning workload through mechanisms such as the middle-layer abstraction of job scheduling，the mount of
heterogeneous storage inside containers and the matching mechanism of resource expressions. The experience of designing OMAI provides a general guidance for the development of artificial intelligence services on clouds. |
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| Keywords: | deep learning artificial intelligence cloud service high-performance computing platform software |
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