Compiler Optimizations for Machine Learning

• Intermediate Representations

  Design and manipulate high-level and low-level intermediate representations for tensor computations.

• Graph Optimization

  Implement graph-level transformations such as operator fusion, constant folding, and dead code elimination.

• Loop Transformations

  Apply advanced loop optimizations including tiling, unrolling, and reordering to maximize cache locality.

• MLIR Infrastructure

  Utilize the Multi-Level Intermediate Representation framework to build custom dialects and lowering pipelines.

• Auto-tuning

  Develop strategies for automated kernel search and cost modeling to find optimal execution schedules.

There are no prerequisite courses for this course.

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