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NXP eIQ® Neutron Neural Processing Unit (NPU)

Machine Learning09 May 2024
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NXP eIQ for next generation of edge applications: Highly scalable, area and power efficient machine learning accelerator core architecture.

The next wave of edge applications require advanced processing and machine learning capabilities. Machine learning use cases vary widely for the different markets and application domains requiring different amounts of acceleration compute performance and at differing amounts of power dissipation and overall solution cost.

One of the most effective ways to offer improved compute performance and power efficiency for machine learning applications is to integrate a purpose-built and dedicated neural processing unit (NPU), sometimes also referred to as a machine learning accelerator (MLA) or deep learning accelerators (DLA), into the device to complement the CPU compute cores.

NXP offers a very wide portfolio of devices from traditional MCUs in the Kinetis, LPC families and more recently the MCX portfolio of devices, to our i.MX RT crossover MCUs and our i.MX applications processors, and in each of the market areas we serve, we see an increased demand for efficient machine learning compute capabilities. To offer highly- optimized devices to our users across our portfolio, we developed the eIQ Neutron neural processing unit (NPU). The eIQ Neutron NPU architecture scales from the most efficient MCU to the most capable i.MX applications processors in our portfolio. This billions (Giga) to trillions (Tera) operations per cycle scalability combined with the support for a wide variety of neural network types such as CNN, RNN, TCN and Transformer networks and more is a recipe for success.

The eIQ Neutron NPU offers a rich set of options that can be leveraged based on the NXP edge processing device the core is integrated into and the market needs that device family is addressing.

  • Dedicated controller core
  • In-line dequantization, activation and pooling
  • Built in tiny-caching to reduce power consumption and reduce reliance on system memory speed
  • Weight decompression engine
  • Advanced multi-dimensional DMA for input and output formats, including striding, batching, interleaving, concatenating
  • Configurable coupled memory

Designing for next-generation secure, connected Edge devices?

Get more insight by reading the i.MX 95 product announcement blog.

Further to the hardware capabilities and features, the eIQ Neutron NPU cores are fully supported by the award winning eIQ® Machine Learning (ML) Software (SW) Development Environment. The combination of NXP developed hardware acceleration and software enablement offers our users the ability to leverage their experience across the NXP edge processing portfolio as well as the reassurance that support for emerging machine learning neural networks, models and operators can be more efficiently supported even after devices are deployed and in the field.

You can start to develop intelligent solutions with the eIQ Neutron NPU with the MCX-N series of MCUs and the i.MX 95 applications processors with more devices to come.

Explore eIQ Neutron NPU on MCX N MCUs:

MCX N Series Products

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A close-up view of an NXP MCX N Series microchip mounted on a dark circuit board. The chip is highlighted with a glowing, multi-colored outline, emphasizing its central position among other electronic components. The NXP logo is clearly visible in the bottom right corner, and the text 'MCX N Series' is printed on the chip surface.

MCX N94x/54x

    • Arm® Cortex®-M33 @ 150 MHz (Dual core)
    • DSP Accelerator (PowerQUAD, with Co-Processor interface)
    • SmartDMA (co-processor for applications such as parallel camera interface and keypad scanning)
    • eIQ® Neutron N1-16 Neural Processing Unit
    • Power Line Communications (PLC) Controller

    i.MX 95 Family of Applications Processors

    Additional devices supported with eIQ ML SW development environment and offering NPU cores

    Image

    The image shows two microchips, one displaying the text 'BX55' and the other revealing intricate circuit patterns.

    i.MX 8M PLUS

      • 4x or 2x Cortex-A53 up to 1.8 GHz
      • Cortex-M7 up to 800 MHz
      • 32-bit DDR4 and LPDDR4 up to 4.0GT/s
      • Neural Processing Unit (NPU): Delivers up to 2.3 TOPS
      • Dual Image Signal Processor (ISPs): Resolution up to 12MP and input rate up to 375MPixels/s
      • Camera Interface: 2x MIPI CSI

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      Image

      Close-up image of two NXP i.MX 93 microchips, one showing the top with clear product labeling and the other displaying the underside with a ball grid array.

      i.MX 93

        • 1-2x Arm® Cortex®-A55 @ 1.7 GHz
        • Arm Cortex-M33 @ 250Mhz
        • Arm® Ethos™ U-65 microNPU
        • EdgeLock® secure enclave

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        Article Tags

        Robotics
        NXP Semiconductors
        Artificial Intelligence (AI)
        Machine Learning
        Microcontrollers - MCUs

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