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Course Outline

Introduction to Custom Operator Development

  • Rationale for building custom operators: use cases and constraints.
  • CANN runtime structure and points for operator integration.
  • Overview of TBE, TIK, and TVM within the Huawei AI ecosystem.

Using TIK for Low-Level Operator Programming

  • Understanding the TIK programming model and supported APIs.
  • Memory management and tiling strategies in TIK.
  • Creating, compiling, and registering a custom operator with CANN.

Testing and Validating Custom Operators

  • Unit testing and integration testing of operators within the graph.
  • Debugging kernel-level performance issues.
  • Visualizing operator execution and buffer behavior.

TVM-Based Scheduling and Optimization

  • Overview of TVM as a compiler for tensor operations.
  • Writing a schedule for a custom operator in TVM.
  • TVM tuning, benchmarking, and code generation for Ascend.

Integration with Frameworks and Models

  • Registering custom operators for MindSpore and ONNX.
  • Verifying model integrity and fallback behavior.
  • Supporting multi-operator graphs with mixed precision.

Case Studies and Specialized Optimizations

  • Case study: high-efficiency convolution for small input shapes.
  • Case study: memory-aware attention operator optimization.
  • Best practices for deploying custom operators across devices.

Summary and Next Steps

Requirements

  • Strong understanding of AI model internals and operator-level computation.
  • Experience with Python and Linux development environments.
  • Familiarity with neural network compilers or graph-level optimizers.

Target Audience

  • Compiler engineers working on AI toolchains.
  • Systems developers focused on low-level AI optimization.
  • Developers building custom operators or targeting novel AI workloads.
 14 Hours

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  • 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.
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