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Lanyun Yushengdai AIDC OS
Overview :
Lanyun Yushengdai AIDC OS is a product specializing in GPU computing cloud services, aiming to provide enterprises and developers with powerful computing capabilities and flexible resource configurations. The product supports multiple GPU models, on-demand billing, and is suitable for fields such as deep learning and graphic rendering. Its main advantages include high-performance computing resources, scalable storage solutions, and a compliant cloud service environment, meeting the needs of businesses of all sizes. The price ranges from 1.50 to 1.60 yuan per hour, depending on the selected GPU model.
Target Users :
Suitable for enterprises and developers who need high-performance computing, especially users in industries such as deep learning, artificial intelligence, and graphic rendering. This product can help them quickly obtain computing resources, improve work efficiency, and reduce IT costs.
Use Cases
Company A uses Lanyun's GPU cloud service for deep learning model training, significantly improving the training efficiency of the model.
Developer B uses Lanyun's computing resources for graphic rendering and successfully completes a large animation project.
Research Institute C processes large-scale data analysis through Lanyun's GPU cloud service, shortening the data processing time.
Features
Provides various GPU model options to meet different computing needs
Pay-as-you-go billing for flexible cost control
Supports multiple operating systems with strong compatibility
Offers high availability and reliable cloud services
Scalable storage solutions for different application scenarios
Compliant cloud migration to ensure user data security
User-friendly interface for easy resource management
How to Use
Visit the Lanyun official website and register an account.
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After logging in, select the desired GPU model and resource configuration.
Choose the billing method according to your needs, such as pay-as-you-go or monthly billing.
Confirm the order and complete the payment.
Start using the rented GPU resources to perform computing tasks.
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