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Write efficient IRON Python designs and C++ AIE kernels for AMD XDNA NPUs (AIE2 / AIE2P architectures, e.g., Ryzen AI Phoenix, Hawk, Strix, Krackan Point). Use whenever the user asks about IRON, ObjectFifo, Worker/Program/Runtime, NPU programming, AIE…
原文语言：英语
Guide to optimizing an AIE/IRON design's dataflow — dispatch partitioning, tile placement, overlays, weight/activation streaming strategy, and DMA bandwidth/compression — once it's already functionally correct. Distinct from aie-kernel-opt (which optimizes a…
原文语言：英语
Guide to validating an AIE/IRON dataflow design in software before it ever touches hardware — a threaded ObjectFifo/Worker mock for deadlock/FIFO-depth detection, bit-exact validation against a numeric oracle, tiny isolated probes to de-risk novel mechanisms,…
原文语言：英语
Guide to bringing up a new IRON design on real AIE/NPU hardware for the first time — sequential block-by-block (and, for large models, dispatch-by-dispatch) bring-up against a reference, immediate output comparison against the numeric oracle/ONNX Runtime,…
原文语言：英语
Standalone guide to optimizing AIE / Peano-compiled kernels (INT8 conv, matmul, attention, elementwise). Covers the measure-first methodology (baseline, bit-exact gate, ablation, verify-in-.o) and the catalog of concrete levers in priority order — loop hints,…
原文语言：英语
Guide to preparing an ML model for AIE/NPU deployment before any device or dataflow work begins — choosing/locking a quantization scheme, exporting ONNX, extracting a deployment manifest (per-op scales/zero-points/shifts/layout), and building a bit-exact…
原文语言：英语