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NDP102

Home / Products / Processors / Neural Decision Processors / NDP102
Our family of Neural Decision Processors (NDPs) are specifically designed to run deep learning models, providing 100x the efficiency and 10/30x the throughput of existing low-power MCUs.
Ask us about this product
Claim Free Samples

Syntiant leads in edge-AI with custom silicon enabling deep learning on battery-powered devices. Their technology supports real-time data processing and decision-making with minimal power consumption, from hearing aids to automotive applications. Syntiant’s solutions empower developers to quickly deploy efficient deep learning models across a wide range of edge devices, revolutionizing applications in audio, video, and sensor processing.

Characteristics

Additional information

DNN Core Memory

params: 589k1

DNN Core Clock

< 16MHz

DNN Core Features

4 Layer, Fully Connected

MCU Memory

M0, 112kB

MCU Clock

< 16MHz

DSP Memory

–

DSP Clock

–

DSP Features

–

Package [mm]

1,7mm x 2,5mm 20-ball eWLB

Product status

Active

The Syntiant® Neural Decision ProcessorTM architecture is built from the ground up to run deep learning algorithms. With embedded Syntiant Core 1TM, the NDP102 is capable of performing sensor processing at under 100uW and can operate as a standalone always-on component of a larger system. It achieves breakthrough performance by highly coupled computation and memory, exploiting the vast inherent parallelism of deep learning and computing at only required numerical precision. The device combines these elements to achieve approximately 100x efficiency improvement over stored program architectures such as CPUs and DSPs.

  • Under 100uW active power consumption in always-on sensor applications
  • 1.71mm x 2.51mm 20-pin eWLB (0.4mm pitch)
  • Syntiant Core 1TM neural processor
  • Hardware feature extraction up to 100Hz frame rate and up to 40 frequency bins per frame
  • Fully connected neural network, supporting up to 589k parameters
  • Deeply embedded ARM cortex-MO processor with 112KB SRAM
  • Six GPIO pins with programmable direction and drive strength
  • Integrated clock multiplier and dividers support low frequency clock source or external clocking
  • I2C serial interface for sensor applications
  • On-chip programmable clock divider
  • External serial flash boot
  • Integrated clock multiplier and dividers support low-frequency clock source or external clocking
  • On board firmware security and authentication
  • Software Development Kit (SDK) integrates in any software environment
  • Training Development Kit (TDK) to enable the use of standard frameworks such as TensorFlow for customer-programmed application

The NDP102 supports dozens of application-defined sensor sequences for a variety of use cases including:
  • Event detection
  • Pressure sensing
  • Gesture recognition
  • Anomaly detection
  • Sensor fusion

NDP102

Home / Products / Processors / Neural Decision Processors / NDP102
Our family of Neural Decision Processors (NDPs) are specifically designed to run deep learning models, providing 100x the efficiency and 10/30x the throughput of existing low-power MCUs.

Additional information

DNN Core Memory

params: 589k1

DNN Core Clock

< 16MHz

DNN Core Features

4 Layer, Fully Connected

MCU Memory

M0, 112kB

MCU Clock

< 16MHz

DSP Memory

–

DSP Clock

–

DSP Features

–

Package [mm]

1,7mm x 2,5mm 20-ball eWLB

Product status

Active

Ask us about this product
Claim Free Samples

The Syntiant® Neural Decision ProcessorTM architecture is built from the ground up to run deep learning algorithms. With embedded Syntiant Core 1TM, the NDP102 is capable of performing sensor processing at under 100uW and can operate as a standalone always-on component of a larger system. It achieves breakthrough performance by highly coupled computation and memory, exploiting the vast inherent parallelism of deep learning and computing at only required numerical precision. The device combines these elements to achieve approximately 100x efficiency improvement over stored program architectures such as CPUs and DSPs.

  • Under 100uW active power consumption in always-on sensor applications
  • 1.71mm x 2.51mm 20-pin eWLB (0.4mm pitch)
  • Syntiant Core 1TM neural processor
  • Hardware feature extraction up to 100Hz frame rate and up to 40 frequency bins per frame
  • Fully connected neural network, supporting up to 589k parameters
  • Deeply embedded ARM cortex-MO processor with 112KB SRAM
  • Six GPIO pins with programmable direction and drive strength
  • Integrated clock multiplier and dividers support low frequency clock source or external clocking
  • I2C serial interface for sensor applications
  • On-chip programmable clock divider
  • External serial flash boot
  • Integrated clock multiplier and dividers support low-frequency clock source or external clocking
  • On board firmware security and authentication
  • Software Development Kit (SDK) integrates in any software environment
  • Training Development Kit (TDK) to enable the use of standard frameworks such as TensorFlow for customer-programmed application

The NDP102 supports dozens of application-defined sensor sequences for a variety of use cases including:
  • Event detection
  • Pressure sensing
  • Gesture recognition
  • Anomaly detection
  • Sensor fusion

Syntiant leads in edge-AI with custom silicon enabling deep learning on battery-powered devices. Their technology supports real-time data processing and decision-making with minimal power consumption, from hearing aids to automotive applications. Syntiant’s solutions empower developers to quickly deploy efficient deep learning models across a wide range of edge devices, revolutionizing applications in audio, video, and sensor processing.

Characteristics

Additional information

DNN Core Memory

params: 589k1

DNN Core Clock

< 16MHz

DNN Core Features

4 Layer, Fully Connected

MCU Memory

M0, 112kB

MCU Clock

< 16MHz

DSP Memory

–

DSP Clock

–

DSP Features

–

Package [mm]

1,7mm x 2,5mm 20-ball eWLB

Product status

Active

NDP102

Home / Products / Processors / Neural Decision Processors / NDP102
Our family of Neural Decision Processors (NDPs) are specifically designed to run deep learning models, providing 100x the efficiency and 10/30x the throughput of existing low-power MCUs.
Ask us about this product
Claim Free Samples

The Syntiant® Neural Decision ProcessorTM architecture is built from the ground up to run deep learning algorithms. With embedded Syntiant Core 1TM, the NDP102 is capable of performing sensor processing at under 100uW and can operate as a standalone always-on component of a larger system. It achieves breakthrough performance by highly coupled computation and memory, exploiting the vast inherent parallelism of deep learning and computing at only required numerical precision. The device combines these elements to achieve approximately 100x efficiency improvement over stored program architectures such as CPUs and DSPs.

  • Under 100uW active power consumption in always-on sensor applications
  • 1.71mm x 2.51mm 20-pin eWLB (0.4mm pitch)
  • Syntiant Core 1TM neural processor
  • Hardware feature extraction up to 100Hz frame rate and up to 40 frequency bins per frame
  • Fully connected neural network, supporting up to 589k parameters
  • Deeply embedded ARM cortex-MO processor with 112KB SRAM
  • Six GPIO pins with programmable direction and drive strength
  • Integrated clock multiplier and dividers support low frequency clock source or external clocking
  • I2C serial interface for sensor applications
  • On-chip programmable clock divider
  • External serial flash boot
  • Integrated clock multiplier and dividers support low-frequency clock source or external clocking
  • On board firmware security and authentication
  • Software Development Kit (SDK) integrates in any software environment
  • Training Development Kit (TDK) to enable the use of standard frameworks such as TensorFlow for customer-programmed application

The NDP102 supports dozens of application-defined sensor sequences for a variety of use cases including:
  • Event detection
  • Pressure sensing
  • Gesture recognition
  • Anomaly detection
  • Sensor fusion

Syntiant leads in edge-AI with custom silicon enabling deep learning on battery-powered devices. Their technology supports real-time data processing and decision-making with minimal power consumption, from hearing aids to automotive applications. Syntiant’s solutions empower developers to quickly deploy efficient deep learning models across a wide range of edge devices, revolutionizing applications in audio, video, and sensor processing.

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NDP102

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