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Duration 14 hours
Course Outline
Introduction to Huawei’s AI Ecosystem
- Overview of Ascend AI hardware variants, including 310, 910, and 910B.
- Exploration of high-level components such as MindSpore, CANN, and AscendCL.
- Discussion on industry positioning and core architectural principles.
The Role of CANN in Huawei’s AI Stack
- Defining CANN: Examining the SDK's purpose and its internal structural layers.
- Analyzing ATC, TBE, and AscendCL for compiling and executing models.
- Understanding how CANN facilitates inference optimization and robust deployment.
MindSpore Overview and Architecture
- Navigating training and inference workflows within MindSpore.
- Examining Graph mode, PyNative, and hardware abstraction mechanisms.
- Exploring integration with Ascend NPUs through the CANN backend.
AI Lifecycle on Ascend: From Training to Deployment
- Creating models in MindSpore or converting them from alternative frameworks.
- Processes for exporting and compiling models using ATC.
- Deploying on Ascend hardware utilizing OM models and AscendCL.
Comparison with Other AI Stacks
- Contrasting MindSpore with PyTorch and TensorFlow in terms of focus and market positioning.
- Comparing deployment workflows on Ascend against GPU-based ecosystems.
- Identifying opportunities and potential limitations for enterprise adoption.
Enterprise Integration Scenarios
- Real-world use cases in smart manufacturing, government AI, and telecommunications.
- Considerations regarding scalability, compliance, and ecosystem maturity.
- Strategies for cloud and on-premise hybrid deployments using the Huawei stack.
Summary and Next Steps
Requirements
- General familiarity with AI workflows or platform architecture concepts.
- A foundational understanding of model training and deployment processes.
- No prior hands-on experience with CANN or MindSpore is necessary.
Target Audience
- AI platform evaluators and infrastructure architects.
- AI/ML DevOps engineers and pipeline integration specialists.
- Technology managers and strategic decision-makers.
