Development and Ecosystem Layer
One-Click AI Development with Integrated Tools
Accelerate Large Model Training and Inference
AI-Stack manages GPU resource pools on a single platform and enables collaborative computing across nodes, flexibly supporting multi-node training and large-scale inference while improving resource utilization and deployment flexibility.
Distributed Training
- Support for leading training frameworks and workflows, including DeepSpeed, Slurm on Kubernetes.
- Easily create multi-node clusters through an intuitive graphical interface.
- Intelligent scheduling reduces resource wait times and prevents scheduling deadlocks.
- Automatic recovery and checkpoint-based training resumption minimize disruption and lost progress.
Distributed Inference
- Supports Prefill/Decode (PD) disaggregation.
- Scale each phase independently based on demand, using different GPU types to balance latency and hardware costs.
- Intelligent routing across replicas and multi-node model deployment support high concurrency and very large models.
AI development is at your fingertips!
Based on Kubernetes and Docker, AI-Stack delivers an efficient, intuitive workspace, cutting the environment setup to one minute. This lets developers immediately focus on model design, training, and deployment. AI-Stack integrates mainstream ANN, ML frameworks, and tools, fully supporting the process from data preparation to model deployment, offering a consistent, seamless experience both on-premise and in the cloud.
AI & LLM Support
Fully supports leading AI frameworks and LLM inference engines, including PyTorch, TensorFlow, DeepSpeed, vLLM, and SGLang.
Convenient Environment Configuration
Quickly set up and manage your development environment, saving time and effort.
Workflow Automation
AI-Stack enhances your development efficiency through automation, simplifying the model training and deployment process.
Highly Scalable AI Development Platform
Seamlessly integrate with various third-party tools and platforms. Connect with a wide range of databases, data analytics tools, and cloud service platforms. Support the storage of model data in different formats and frameworks, helping you build comprehensive machine learning solutions.
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Ecosystem Layers