技术
- 分析与建模 - 机器学习
- 应用基础设施与中间件 - 数据交换与集成
适用行业
- 建筑物
- 建筑与基础设施
适用功能
- 产品研发
用例
- 需求计划与预测
- 时间敏感网络
服务
- 云规划/设计/实施服务
- 系统集成
关于客户
Annapurna Labs 成立于 2011 年,是一家无晶圆厂芯片初创公司,专注于为快速增长的云基础设施带来创新。四年后,它被亚马逊网络服务(AWS)收购。此后,Annapurna Labs 加速创新,开发了多款让云客户受益的产品,包括基于 64 位 Arm Neoverse 架构专用云服务器的 AWS Nitro 技术、Inferentia 定制机器学习芯片和 AWS Graviton2 处理器。
挑战
Annapurna Labs 是一家被 Amazon Web Services (AWS) 收购的无晶圆厂芯片初创公司,在管理专用 Amazon Elastic Compute Cloud (EC2) 实例上的工作负载方面面临着挑战。团队有时可以通过手动添加新的按需实例来进行扩展,但该过程不是自动化的,从而导致效率低下、忘记未使用的计算资源以及扩展不足或扩展过多。作为一家芯片设计公司,上市时间和工程效率是他们的关键指标。该团队需要一种解决方案,可以增加结构和效率以扩展 AWS 计算资源,缩短获得结果的时间,并将开发模型更改为持续集成。
解决方案
Annapurna Labs 选择 Altair Accelerator™ 作业调度程序用于其前端和后端工作流程。 Accelerator 的快速扩展功能由 Annapurna Labs 开发,仅在有需求时自动启动新实例,并在处理需求的速度足够快时停止扩展。这种许可证优先的调度方法使 Accelerator 能够有效地区分等待许可证的工作负载与等待硬件的工作负载。与 Annapurna Labs 合作添加了许多功能,包括可配置的实例类型选择、Spot 实例支持、防止各种错误、精细控制每个新实例上可以执行的作业数量等等。 Rapid Scaling 还了解在第一个选择不可用时如何选择备份实例类型。
运营影响
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