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NDP200

NDP200

Home / Products / Processors / Neural Decision Processors / NDP200
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.
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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

pmem: 896kB, dmem: 128kB

DNN Core Clock

Same as DSP

DNN Core Features

All Networks, Fixed Point

MCU Memory

M0, 48kB

MCU Clock

Same as DSP

DSP Memory

imem: 96kB, dmem: 192kB

DSP Clock

0,9V: < 22MHz, 1,0V: < 60MHz, 1,1V: < 100MHz

DSP Features

HiFi3: Fixed-point

Package [mm]

5mm x 5mm 40-pin QFN

Product status

Active

The Syntiant® NDP200 Neural Decision Processor™ is a special-purpose chip for image and sensor processing for always-on applications in battery powered devices and other power constrained systems. The NDP200 applies neural processing to run multiple applications simultaneously with minimal battery power consumption. Built using the Syntiant Core 2T™ programmable deep learning architecture, NDP200 is designed to natively run deep multiple neural networks (DNN) on a variety of architectures, such as CNN, RNN and fully connected networks, and it performs vision processing with highly accurate inference at under 1mW. NDP200 brings a level of ML performance that delivers 25x the tensor throughput than the Syntiant Core 1™ embedded in Syntiant’s NDP100 and NDP101 devices. A programmable Hifi3 DSP is available for feature extraction and signal processing.

  • Neural network supported concurrently: fullyconnected, 1D & 2D convolution, depth wise convolution, recurrent neural network including LSTM and GRU, average and max pooling
  • Up to 896k neural parameters in 8-bit mode, 1.8M parameters in 4-bit mode, and more than 7M parameters in1-bit mode
  • 11-wire direct image interface
  • Dual PDM digital microphone interface
  • I2S serial interface with PCM
  • SPI and I2C controller and target for multimodal sensor fusion
  • 26 GPIO pins
  • Programmable HiFi 3 DSP
  • Up to 100MHz internal operating frequency
  • Embedded Arm Cortex-M0 for device management with 48KB SRAM, dual timers and UART functionality
  • Low power PLL for flexible clock input
  • Onboard firmware decryption 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 applications
  • 5mm x 5mm 40-pin QFN package (0.4mm pitch)

The NDP200 supports dozens of application-defined imaging, speech, and sensor sequences for a variety of use cases including:
  • Person presence detection
  • Object classification
  • Wake words and local commands
  • Motion tracking
  • Acoustic event and scene classification
  • Multi-sensor fusion

Datasheet

NDP200

Home / Products / Processors / Neural Decision Processors / NDP200
NDP200
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

pmem: 896kB, dmem: 128kB

DNN Core Clock

Same as DSP

DNN Core Features

All Networks, Fixed Point

MCU Memory

M0, 48kB

MCU Clock

Same as DSP

DSP Memory

imem: 96kB, dmem: 192kB

DSP Clock

0,9V: < 22MHz, 1,0V: < 60MHz, 1,1V: < 100MHz

DSP Features

HiFi3: Fixed-point

Package [mm]

5mm x 5mm 40-pin QFN

Product status

Active

Ask us about this product
Claim Free Samples

The Syntiant® NDP200 Neural Decision Processor™ is a special-purpose chip for image and sensor processing for always-on applications in battery powered devices and other power constrained systems. The NDP200 applies neural processing to run multiple applications simultaneously with minimal battery power consumption. Built using the Syntiant Core 2T™ programmable deep learning architecture, NDP200 is designed to natively run deep multiple neural networks (DNN) on a variety of architectures, such as CNN, RNN and fully connected networks, and it performs vision processing with highly accurate inference at under 1mW. NDP200 brings a level of ML performance that delivers 25x the tensor throughput than the Syntiant Core 1™ embedded in Syntiant’s NDP100 and NDP101 devices. A programmable Hifi3 DSP is available for feature extraction and signal processing.

  • Neural network supported concurrently: fullyconnected, 1D & 2D convolution, depth wise convolution, recurrent neural network including LSTM and GRU, average and max pooling
  • Up to 896k neural parameters in 8-bit mode, 1.8M parameters in 4-bit mode, and more than 7M parameters in1-bit mode
  • 11-wire direct image interface
  • Dual PDM digital microphone interface
  • I2S serial interface with PCM
  • SPI and I2C controller and target for multimodal sensor fusion
  • 26 GPIO pins
  • Programmable HiFi 3 DSP
  • Up to 100MHz internal operating frequency
  • Embedded Arm Cortex-M0 for device management with 48KB SRAM, dual timers and UART functionality
  • Low power PLL for flexible clock input
  • Onboard firmware decryption 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 applications
  • 5mm x 5mm 40-pin QFN package (0.4mm pitch)

The NDP200 supports dozens of application-defined imaging, speech, and sensor sequences for a variety of use cases including:
  • Person presence detection
  • Object classification
  • Wake words and local commands
  • Motion tracking
  • Acoustic event and scene classification
  • Multi-sensor fusion

Datasheet
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.
NDP200

Characteristics

Additional information

DNN Core Memory

pmem: 896kB, dmem: 128kB

DNN Core Clock

Same as DSP

DNN Core Features

All Networks, Fixed Point

MCU Memory

M0, 48kB

MCU Clock

Same as DSP

DSP Memory

imem: 96kB, dmem: 192kB

DSP Clock

0,9V: < 22MHz, 1,0V: < 60MHz, 1,1V: < 100MHz

DSP Features

HiFi3: Fixed-point

Package [mm]

5mm x 5mm 40-pin QFN

Product status

Active

NDP200

Home / Products / Processors / Neural Decision Processors / NDP200
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® NDP200 Neural Decision Processor™ is a special-purpose chip for image and sensor processing for always-on applications in battery powered devices and other power constrained systems. The NDP200 applies neural processing to run multiple applications simultaneously with minimal battery power consumption. Built using the Syntiant Core 2T™ programmable deep learning architecture, NDP200 is designed to natively run deep multiple neural networks (DNN) on a variety of architectures, such as CNN, RNN and fully connected networks, and it performs vision processing with highly accurate inference at under 1mW. NDP200 brings a level of ML performance that delivers 25x the tensor throughput than the Syntiant Core 1™ embedded in Syntiant’s NDP100 and NDP101 devices. A programmable Hifi3 DSP is available for feature extraction and signal processing.

  • Neural network supported concurrently: fullyconnected, 1D & 2D convolution, depth wise convolution, recurrent neural network including LSTM and GRU, average and max pooling
  • Up to 896k neural parameters in 8-bit mode, 1.8M parameters in 4-bit mode, and more than 7M parameters in1-bit mode
  • 11-wire direct image interface
  • Dual PDM digital microphone interface
  • I2S serial interface with PCM
  • SPI and I2C controller and target for multimodal sensor fusion
  • 26 GPIO pins
  • Programmable HiFi 3 DSP
  • Up to 100MHz internal operating frequency
  • Embedded Arm Cortex-M0 for device management with 48KB SRAM, dual timers and UART functionality
  • Low power PLL for flexible clock input
  • Onboard firmware decryption 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 applications
  • 5mm x 5mm 40-pin QFN package (0.4mm pitch)

The NDP200 supports dozens of application-defined imaging, speech, and sensor sequences for a variety of use cases including:
  • Person presence detection
  • Object classification
  • Wake words and local commands
  • Motion tracking
  • Acoustic event and scene classification
  • Multi-sensor fusion

Datasheet
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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NDP200

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