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Neural Processing Unit Acceleration: Operator Mapping, Graph Optimization, and Efficient AI Execution on NPUs
Paperback
Publisher: Independently Published
Published: Oct 1 2026
Pages: 78
Weight: 0.26
Height: 0.16 Width: 6.00 Depth: 9.00
Language: English
- Graph Preparation & Lowering: Step-by-step techniques for graph capture, constant folding, shape inference, and execution lowering.
- Operator Mapping & Fallbacks: Strategies for supporting custom ops, fused operations, and managing robust fallback paths.
- Quantization Strategies for NPUs: Calibration methods, per-channel scaling, activation ranges, and int8/int4 kernel optimization.
- Heterogeneous Execution: Mastering CPU-NPU splits, GPU fallback, and pipeline synchronization.
- Profiling & Debugging: Identifying operator hotspots, solving precision drift, and eliminating driver mismatches in production. Whether you are optimizing vision models for mobile chips, edge robotics, or auto-grade SoCs, this book provides clear decision frameworks, practical checklists, and production-ready architectural patterns. Take your edge AI deployments to production speed-scroll up and get your copy today!
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