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Course Outline
Performance Concepts and Metrics
- Latency, throughput, power consumption, and resource utilization
- Distinguishing system-level from model-level bottlenecks
- Profiling strategies for inference versus training
Profiling on Huawei Ascend
- Utilizing CANN Profiler and MindInsight
- Diagnosing kernel and operator performance
- Offload patterns and memory mapping
Profiling on Biren GPU
- Biren SDK performance monitoring capabilities
- Kernel fusion, memory alignment, and execution queues
- Profiling with consideration for power and temperature
Profiling on Cambricon MLU
- BANGPy and Neuware performance tools
- Kernel-level visibility and log analysis
- Integrating the MLU profiler with deployment frameworks
Graph and Model-Level Optimization
- Strategies for graph pruning and quantization
- Operator fusion and restructuring computational graphs
- Standardizing input sizes and tuning batches
Memory and Kernel Optimization
- Optimizing memory layouts and data reuse
- Efficient buffer management across different chipsets
- Platform-specific kernel tuning techniques
Cross-Platform Best Practices
- Achieving performance portability through abstraction strategies
- Developing shared tuning pipelines for multi-chip environments
- Case study: tuning an object detection model across Ascend, Biren, and MLU
Summary and Next Steps
Requirements
- Hands-on experience with AI model training or deployment pipelines
- Knowledge of GPU/MLU compute principles and model optimization techniques
- Familiarity with basic performance profiling tools and metrics
Target Audience
- Performance engineers
- Machine learning infrastructure teams
- AI system architects
21 Hours
Custom Corporate Training
Training solutions designed exclusively for businesses.
- Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
- Flexible Schedule: Dates and times adapted to your team's agenda.
- Format: Online (live), In-company (at your offices), or Hybrid.
Price per private group, online live training, starting from 4800 € + VAT*
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