AI Development and Training Platform
Seamless AI Development
Through advanced computing power scheduling strategies, the platform quickly starts the development and training process, integrates multiple key links such as development environment, training environment and effect evaluation, and provides users with a one-stop AI development experience. Leveraging advanced computational scheduling strategies, the platform accelerates the development and training process. It seamlessly integrates essential components, including the development environment, training framework, and performance evaluation. This comprehensive approach delivers users a streamlined, one-stop experience for AI development, empowering them to achieve results efficiently and effectively.
Advantages
Instant-on
Through advanced computing power scheduling strategies, the platform quickly responds to developers' needs, enabling instant start of development and training, significantly shortening the project cycle.
Flexible Configuration
Developers can freely select CPU cores, memory, GPU models, and quantities to create a personalized development environment tailored to project requirements.
Efficient Development
Supports card-free boot, online development with tools like Jupyter, Python, and VSCode, as well as image saving functions, allowing developers to efficiently write and debug code anytime, anywhere.
Resource Optimization
Provides strategies like timed shutdown and release to help developers plan resource usage rationally and reduce costs effectively.
Capabilities
Development Machine Service
Provides flexible online creation of development machines, allowing users to customize CPU, memory, GPU model, system disk, and more. Supports seamless operations with tools like Jupyter, Python, and VSCode, while enabling resource management through timed shutdown and release strategies to optimize utilization.
Distributed Training Service
Offers model adjustment capabilities for fine-tuning and advanced training needs. Supports diversified training methods such as pre-training DLC, SFT fine-tuning, and various innovative techniques like Wenshengwen and Wenshengtu to address sophisticated business scenarios.
Model Effect Evaluation
Enables comprehensive evaluation of large models based on performance, efficiency, generalization, inference speed, resource consumption, and scalability. Delivers multi-dimensional insights into model applicability and overall quality to refine AI development.
Mirror Repository
Provides a repository of pre-configured images tailored for AI development and training. Supports users in pushing custom images and saving them in the development environment, creating an integrated platform for seamless development and training workflows.
Flexible Resource Management
Combines advanced scheduling strategies, such as Kubernetes and custom-defined configurations, to optimize task execution. Features resource recovery through automatic shutdown and release mechanisms, ensuring efficient resource allocation and minimized wastage.
User-Friendly Operations
Simplifies complex workflows with intuitive interfaces for one-click task submission. Supports built-in computing frameworks and mirroring acceleration to minimize distribution time and enhance deployment efficiency.
Application Scenarios
Computing Center Builder
Enables builders to manage computing power resources more efficiently, maximizing resource utilization and controlling costs.
Intelligent Computing Center Operator
Allows operators to provide differentiated services, meeting the needs of different customers while improving service quality and customer satisfaction.
Enterprise Resource Management
Helps enterprises manage and optimize internal computing resources, improving resource utilization and reducing operating costs.
Customer Management and Marketing
Enables refined customer management and marketing operations to enhance user conversion rates and repurchase rates.
AI Model Training
Efficiently schedules and manages GPU resources to accelerate the model training process and improve training efficiency.