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NDP101

NDP101

Home / Products / Processors / Neural Decision Processors / NDP101
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]

5mm x 5mm 32-pin QFN

Product status

Active

The Syntiant® Neural Decision Processor™ architecture is built from the ground up to run deep learning algorithms. With embedded Syntiant Core 1™, the NDP101 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.

  • System on chip in a 32 pin QFN package
  • Suitable for applications that require an MCU for control and a neural engine for decision making
  • Dual PDM microphone input or PCM-over-SPI input
  • Stereo/mono I2S interface multiplexed with PDM
  • Direct access to neural network over SPI for sensor applications
  • Frequency, time-domain & batch input models
  • 16-bit input holding tank with faster than real-time SPI extraction
  • General purpose ARM Cortex-M0 processor with 112KB SRAM
  • Eight GPIO pins with programmable direction and drive strength
  • Support for external serial flash boot
  • Integrated clock multiplier and dividers support low frequency clock source or external clocking
  • Optimized interrupt and SPI slave interface
  • Master SPI interface for sensor interfaces
  • Onboard firmware security and authentication
  • English Speech Service for keyword training
  • Software Development Kit (SDK) integrates in any software environment
  • Training Development Kit (TDK) to enable the user of standard frameworks such as TensorFlow for customer-programmed applications
  • Support for 64 output classifications
  • Active power consumption of <140μW while recognizing words

The NDP101 supports dozens of application-defined audio sequences for a variety of use cases including:
  • Keyword speech interface
  • Wake word detection
  • Speaker identification
  • Sensor applications
  • Audio event and environment classification

NDP101

Home / Products / Processors / Neural Decision Processors / NDP101
NDP101
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]

5mm x 5mm 32-pin QFN

Product status

Active

Ask us about this product
Claim Free Samples

The Syntiant® Neural Decision Processor™ architecture is built from the ground up to run deep learning algorithms. With embedded Syntiant Core 1™, the NDP101 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.

  • System on chip in a 32 pin QFN package
  • Suitable for applications that require an MCU for control and a neural engine for decision making
  • Dual PDM microphone input or PCM-over-SPI input
  • Stereo/mono I2S interface multiplexed with PDM
  • Direct access to neural network over SPI for sensor applications
  • Frequency, time-domain & batch input models
  • 16-bit input holding tank with faster than real-time SPI extraction
  • General purpose ARM Cortex-M0 processor with 112KB SRAM
  • Eight GPIO pins with programmable direction and drive strength
  • Support for external serial flash boot
  • Integrated clock multiplier and dividers support low frequency clock source or external clocking
  • Optimized interrupt and SPI slave interface
  • Master SPI interface for sensor interfaces
  • Onboard firmware security and authentication
  • English Speech Service for keyword training
  • Software Development Kit (SDK) integrates in any software environment
  • Training Development Kit (TDK) to enable the user of standard frameworks such as TensorFlow for customer-programmed applications
  • Support for 64 output classifications
  • Active power consumption of <140μW while recognizing words

The NDP101 supports dozens of application-defined audio sequences for a variety of use cases including:
  • Keyword speech interface
  • Wake word detection
  • Speaker identification
  • Sensor applications
  • Audio event and environment classification

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.
NDP101

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]

5mm x 5mm 32-pin QFN

Product status

Active

NDP101

Home / Products / Processors / Neural Decision Processors / NDP101
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 Processor™ architecture is built from the ground up to run deep learning algorithms. With embedded Syntiant Core 1™, the NDP101 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.

  • System on chip in a 32 pin QFN package
  • Suitable for applications that require an MCU for control and a neural engine for decision making
  • Dual PDM microphone input or PCM-over-SPI input
  • Stereo/mono I2S interface multiplexed with PDM
  • Direct access to neural network over SPI for sensor applications
  • Frequency, time-domain & batch input models
  • 16-bit input holding tank with faster than real-time SPI extraction
  • General purpose ARM Cortex-M0 processor with 112KB SRAM
  • Eight GPIO pins with programmable direction and drive strength
  • Support for external serial flash boot
  • Integrated clock multiplier and dividers support low frequency clock source or external clocking
  • Optimized interrupt and SPI slave interface
  • Master SPI interface for sensor interfaces
  • Onboard firmware security and authentication
  • English Speech Service for keyword training
  • Software Development Kit (SDK) integrates in any software environment
  • Training Development Kit (TDK) to enable the user of standard frameworks such as TensorFlow for customer-programmed applications
  • Support for 64 output classifications
  • Active power consumption of <140μW while recognizing words

The NDP101 supports dozens of application-defined audio sequences for a variety of use cases including:
  • Keyword speech interface
  • Wake word detection
  • Speaker identification
  • Sensor applications
  • Audio event and environment classification

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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NDP101

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