下载PDF
Rapid Chip Design in the Cloud: Annapurna Labs' Journey with Altair Accelerator
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
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。
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。
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
数量效益
相关案例.
Case Study
Energy Saving & Power Monitoring System
Recently a university in Taiwan was experiencing dramatic power usage increases due to its growing number of campus buildings and students. Aiming to analyze their power consumption and increase their power efficiency across 52 buildings, the university wanted to build a power management system utilizing web-based hardware and software. With these goals in mind, they contacted Advantech to help them develop their system and provide them with the means to save energy in the years to come.
Case Study
IoT System for Tunnel Construction
The Zenitaka Corporation ('Zenitaka') has two major business areas: its architectural business focuses on structures such as government buildings, office buildings, and commercial facilities, while its civil engineering business is targeted at structures such as tunnels, bridges and dams. Within these areas, there presented two issues that have always persisted in regard to the construction of mountain tunnels. These issues are 'improving safety" and "reducing energy consumption". Mountain tunnels construction requires a massive amount of electricity. This is because there are many kinds of electrical equipment being used day and night, including construction machinery, construction lighting, and ventilating fan. Despite this, the amount of power consumption is generally not tightly managed. In many cases, the exact amount of power consumption is only ascertained when the bill from the power company becomes available. Sometimes, corporations install demand-monitoring equipment to help curb the maximum power demanded. However, even in these cases, the devices only allow the total volume of power consumption to be ascertained, or they may issue warnings to prevent the contracted volume of power from being exceeded. In order to tackle the issue of reducing power consumption, it was first necessary to obtain an accurate breakdown of how much power was being used in each particular area. In other words, we needed to be able to visualize the amount of power being consumed. Safety, was also not being managed very rigorously. Even now, tunnel construction sites often use a 'name label' system for managing entry into the work site. Specifically, red labels with white reverse sides that bear the workers' names on both sides are displayed at the tunnel work site entrance. The workers themselves then flip the name label to the appropriate side when entering or exiting from the work site to indicate whether or not they are working inside the tunnel at any given time. If a worker forgets to flip his or her name label when entering or exiting from the tunnel, management cannot be performed effectively. In order to tackle the challenges mentioned above, Zenitaka decided to build a system that could improve the safety of tunnel construction as well as reduce the amount of power consumed. In other words, this new system would facilitate a clear picture of which workers were working in each location at the mountain tunnel construction site, as well as which processes were being carried out at those respective locations at any given time. The system would maintain the safety of all workers while also carefully controlling the electrical equipment to reduce unnecessary power consumption. Having decided on the concept, our next concern was whether there existed any kind of robust hardware that would not break down at the construction work site, that could move freely in response to changes in the working environment, and that could accurately detect workers and vehicles using radio frequency identification (RFID). Given that this system would involve many components that were new to Zenitaka, we decided to enlist the cooperation of E.I.Sol Co., Ltd. ('E.I.Sol') as our joint development partner, as they had provided us with a highly practical proposal.
Case Study
Intelligent Building Automation System and Energy Saving Solution
One of the most difficult problems facing the world is conserving energy in buildings. However, it is not easy to have a cost-effective solution to reduce energy usage in a building. One solution for saving energy is to implement an intelligent building automation system (BAS) which can be controlled according to its schedule. In Indonesia a large university with a five floor building and 22 classrooms wanted to save the amount of energy being used.
Case Study
Powering Smart Home Automation solutions with IoT for Energy conservation
Many industry leaders that offer Smart Energy Management products & solutions face challenges including:How to build a scalable platform that can automatically scale-up to on-board ‘n’ number of Smart home devicesData security, solution availability, and reliability are the other critical factors to deal withHow to create a robust common IoT platform that handles any kind of smart devicesHow to enable data management capabilities that would help in intelligent decision-making
Case Study
Splunk Partnership Ties Together Big Data & IoT Services
Splunk was faced with the need to meet emerging customer demands for interfacing IoT projects to its suite of services. The company required an IoT partner that would be able to easily and quickly integrate with its Splunk Enterprise platform, rather than allocating development resources and time to building out an IoT interface and application platform.