NPU Processor IP Cores
Welcome to the ultimate NPU Processor IP hub! Explore our vast directory of NPU Processor IP Cores.
Neural Network Processing Unit (NPU) IP cores are highly scalable, programmable computer vision and artificial intelligence processors that supports AI operations upgrades for endpoints, edge devices, and cloud devices.
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NPU Processor IP Cores
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32
NPU Processor IP Cores
from 7 vendors
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General Purpose Neural Processing Unit (NPU)
- Hybrid Von Neuman + 2D SIMD matrix architecture
- 64b Instruction word, single instruction issue per clock
- 7-stage, in-order pipeline
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NPU IP for Embedded AI
- Fully programmable to efficiently execute Neural Networks, feature extraction, signal processing, audio and control code
- Scalable performance by design to meet wide range of use cases with MAC configurations with up to 64 int8 (native 128 of 4x8) MACs per cycle
- Future proof architecture that supports the most advanced ML data types and operators
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NPU IP family for generative and classic AI with highest power efficiency, scalable and future proof
- Support wide range of activations & weights data types, from 32-bit Floating Point down to 2-bit Binary Neural Networks (BNN)
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AI accelerator (NPU) IP - 1 to 20 TOPS
- Performance efficient 18 TOPS/Watt
- Scalable performance from 2-9K MACS
- Capable of processing HD images on chip
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AI accelerator (NPU) IP - 32 to 128 TOPS
- Performance efficient 18 TOPS/Watt
- 36K-56K MACS
- Multi-job support
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AI accelerator (NPU) IP - 16 to 32 TOPS
- Performance efficient 18 TOPS/Watt
- Scalable performance from 18K MACS
- Capable of processing HD images on chip
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Highly scalable inference NPU IP for next-gen AI applications
- Matrix Multiplication: 4096 MACs/cycles (int 8), 1024 MACs/cycles (int 16)
- Vector processor: RISC-V with RVV 1.0
- Custom instructions for softmax and local storage access
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AI Accelerator (NPU) IP - 3.2 GOPS for Audio Applications
- 3.2 GOPS
- Ultra-low <300uW power consumption
- Low latency
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4-/8-bit mixed-precision NPU IP
- Easy customization at different core sizes and performance
- NN Converter converts a network file into an internal network format and supports ONNX (PyTorch), TF-Lite, and CFG (Darknet)
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Enhanced Neural Processing Unit for safety providing 98,304 MACs/cycle of performance for AI applications
- Adds hardware safety features to NPX6 NPU, minimizing area and power impact
- Supports ISO 26262 automotive safety standard
- Supports CNNs, transformers, including generative AI, recommender networks, RNNs/LSTMs, etc
- IP targets ASIL B and ASIL D compliance to ISO 26262