Building High Performance Clouds for Scientific Research with OpenStack
公司规模
Large Corporate
地区
- America
国家
- United States
产品
- OpenStack
- Magellan System
技术栈
- OpenStack
- EC2 APIs
实施规模
- Enterprise-wide Deployment
影响指标
- Innovation Output
- Productivity Improvements
技术
- 基础设施即服务 (IaaS) - 云计算
- 基础设施即服务 (IaaS) - 私有云
适用行业
- Software
服务
- 云规划/设计/实施服务
- 系统集成
关于客户
The Magellan system is a collaborative project funded by the U.S. Department of Energy, involving Argonne National Laboratory and Lawrence Berkeley National Laboratory. It aims to push the limits of technical cloud computing by providing a platform for scientific research. The system is designed to run technical computing workloads and is used by approximately 3,000 scientists and researchers. The project focuses on evaluating the maturity of cloud software stacks and their applicability to scientific applications, with a particular emphasis on the performance impact of virtualization and the scalability of cloud environments.
挑战
The Magellan system, funded by the U.S. Department of Energy, was designed to evaluate the usefulness of cloud computing for technical computing workloads. The initial phase involved constructing a large-scale system at Argonne National Laboratory to operate as a private cloud and assess its applicability to scientific applications. The team faced challenges with the scalability and stability of the early open-source implementation of the EC2 APIs, which proved inadequate for their goal of scaling to 700 nodes. This led them to explore other cloud stacks, eventually considering OpenStack for its potential to manage large-scale cloud environments effectively.
解决方案
The team at Argonne National Laboratory decided to adopt OpenStack, an open-source cloud computing initiative, to address the scalability and stability issues they encountered with the previous platform. OpenStack's ability to manage pools of compute, storage, and networking resources at scale made it an ideal choice for the Magellan system. The deployment of OpenStack allowed the team to build a flexible environment for prototyping, software development, and testing large-scale scientific applications. The system now consists of approximately 750 nodes, including compute, storage, and management nodes, providing a robust platform for scientific research.
运营影响
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