Edge AI Processor IP

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Compare 26 IP from 20 vendors (1 - 10)
  • Complete Neural Processor for Edge AI
    • Designed for Low-Power Neural Network Processing
    • Flexible Training Methods
    • Scalable Neuron Fabric
    Block Diagram -- Complete Neural Processor for Edge AI
  • AI Processor Accelerator
    • Universal Compatibility: Supports any framework, neural network, and backbone.
    • Large Input Frame Handling: Accommodates large input frames without downsizing.
    Block Diagram -- AI Processor Accelerator
  • High-Performance Edge AI Accelerator
    • Performance: Up to 16 TOPs
    • MACs (8x8): 4K, 8K
    • Data Types: 1-bit, INT8, INT16
    Block Diagram -- High-Performance Edge AI Accelerator
  • Highly scalable performance for classic and generative on-device and edge AI solutions
    • Flexible System Integration: The Neo NPUs can be integrated with any host processor to offload the AI portions of the application
    • Scalable Design and Configurability: The Neo NPUs support up to 80 TOPS with a single-core and are architected to enable multi-core solutions of 100s of TOPS
    • Efficient in Mapping State-of-the-Art AI/ML Workloads: Best-in-class performance for inferences per second with low latency and high throughput, optimized for achieving high performance within a low-energy profile for classic and generative AI
    • Industry-Leading Performance and Power Efficiency: High Inferences per second per area (IPS/mm2 and per power (IPS/W)
    Block Diagram -- Highly scalable performance for classic and generative on-device and edge AI solutions
  • High-performance 32-bit multi-core processor with AI acceleration engine
    • Instruction set: T-Head ISA (32-bit/16-bit variable-length instruction set);
    • Multi-core: Isomorphic multi-core, with 1 to 4 optional cores;
    • Pipeline: 12-stage;
    • Microarchitecture: Tri-issue, deep out-of-order;
    Block Diagram -- High-performance 32-bit multi-core processor with AI acceleration engine
  • AI inference processor IP
    • High Performance, Low Power Consumption, Small Foot Print IP for Deep Learning inference processing.
    Block Diagram -- AI inference processor IP
  • Performance AI Accelerator for Edge Computing
    • Performance: Up to 16 TOPs
    • MACs (8x8): 4K, 8K
    • Data Types: 1-bit, INT8, INT16
    • Internal SRAM: Up to 16 MB
    Block Diagram -- Performance AI Accelerator for Edge Computing
  • Neural engine IP - The Cutting Edge in On-Device AI
    • The Origin E6 is a versatile NPU that is customized to match the needs of next-generation smartphones, automobiles, AV/VR, and consumer devices.
    • With support for video, audio, and text-based AI networks, including standard, custom, and proprietary networks, the E6 is the ideal hardware/software co-designed platform for chip architects and AI developers.
    • It offers broad native support for current and emerging AI models, and achieves ultra-efficient workload scheduling and memory management, with up to 90% processor utilization—avoiding dark silicon waste.
    Block Diagram -- Neural engine IP - The Cutting Edge in On-Device AI
  • Neural network processor designed for edge devices
    • High energy efficiency
    • Support mainstream deep learning frameworks
    • Low power consumption
    • An integrated AI solution
  • Performance Efficiency Leading AI Accelerator for Mobile and Edge Devices
    • Performance: Up to 4 TOPs
    • MACs (8x8): 512, 1K, 2K
    • Data Types: 1-bit, INT8, INT16
    Block Diagram -- Performance Efficiency Leading AI Accelerator for Mobile and Edge Devices
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Semiconductor IP