Tutorialmultidimensional dmaaieryzen aimlir
AMD Ryzen AI Performs Image Zero Padding
5.9
A technical session demonstrates zero padding of images using multidimensional AIE shim DMA on the AMD Ryzen AI Phoenix NPU, leveraging the IRON API and MLIR-based AI Engine toolchain. The design targets a Phoenix SOC with 16 AI cores, 4 memory tiles and 4 shim DMAs, requires image dimensions multiple of eight pixels, and provides build/run steps using OpenCV and Python for validation.
Key Points
- 1Demonstrates zero padding via AIE shim multidimensional DMA on AMD Ryzen AI Phoenix NPU.
- 2Preserves edge data and maintains output dimensions for convolutional kernels, enabling accurate ML inference.
- 3Provides build and run steps plus IRON API, MLIR, and OpenCV for reproducible deployment workflows.
Scoring Rationale
Practical, reproducible tutorial with direct build/run instructions and toolchain details; limited novelty and narrow hardware scope limit broader applicability.
Sources
Public references used for this report.
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