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NDP115

NDP115

Home / Products / Processors / Neural Decision Processors / NDP115
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: 448kB, dmem: 64kB

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: 64kB, dmem: 144kB

DSP Clock

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

DSP Features

HiFi3: Fixed-point

Package [mm]

2mm x 2mm 25-ball WLBGA

Product status

Active

The Syntiant® NDP115 Neural Decision Processor™ is a special purpose chip deep learning and is ideal for always-on applications in battery powered devices and other power constrained systems. The NDP115 applies neural processing to run multiple applications simultaneously with minimal power consumption. Built using the Syntiant Core 2™ programmable deep learning architecture, NDP115 is designed to natively run multiple Deep Neural Networks (DNN) on a variety of architectures, such as CNN, RNN and fully connected networks. NDP115 brings a level of ML performance that delivers 25x the tensor throughput compared to the Syntiant Core 1™ embedded in Syntiant’s NDP100 and NDP101 devices, and is able to run speech inferences at a mere 280 microwatts. A programmable HiFi 3 DSP is available for flexible feature extraction classical audio processing.

  • Syntiant Core 2TM neural processor
  • Support for concurrent neural networks
  • Embedded user programmable HiFi-3 DSP with 144KB 64 bit data RAM and 64KB 64 bit instruction RAM
  • Deeply embedded Arm Cortex MO microcontroller for device management with 48KB SRAM, dual-timers, and UART functionality
  • Direct input of PCM audio and support for up to 5 audio streams
  • I2C controller and target modes for sensor control and integration
  • Up to 13 GPIO pins
  • Flexible clock generation
  • Onboard firmware decryption and authentication
  • 25-ball WLBGA package (0.4mm pitch)

The NDP115 supports dozens of application-defined audio sequences for a variety of use cases including:
  • Far-field, near-field and close-talk voice interface
  • Multiple wake words and local commands
  • Acoustic Echo Cancellation (AEC), noise suppression, beamforming
  • Speech enhancement
  • Speaker identification and verification
  • Acoustic event and scene classification
  • Multi-sensor fusion

NDP115

Home / Products / Processors / Neural Decision Processors / NDP115
NDP115
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: 448kB, dmem: 64kB

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: 64kB, dmem: 144kB

DSP Clock

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

DSP Features

HiFi3: Fixed-point

Package [mm]

2mm x 2mm 25-ball WLBGA

Product status

Active

Ask us about this product
Claim Free Samples

The Syntiant® NDP115 Neural Decision Processor™ is a special purpose chip deep learning and is ideal for always-on applications in battery powered devices and other power constrained systems. The NDP115 applies neural processing to run multiple applications simultaneously with minimal power consumption. Built using the Syntiant Core 2™ programmable deep learning architecture, NDP115 is designed to natively run multiple Deep Neural Networks (DNN) on a variety of architectures, such as CNN, RNN and fully connected networks. NDP115 brings a level of ML performance that delivers 25x the tensor throughput compared to the Syntiant Core 1™ embedded in Syntiant’s NDP100 and NDP101 devices, and is able to run speech inferences at a mere 280 microwatts. A programmable HiFi 3 DSP is available for flexible feature extraction classical audio processing.

  • Syntiant Core 2TM neural processor
  • Support for concurrent neural networks
  • Embedded user programmable HiFi-3 DSP with 144KB 64 bit data RAM and 64KB 64 bit instruction RAM
  • Deeply embedded Arm Cortex MO microcontroller for device management with 48KB SRAM, dual-timers, and UART functionality
  • Direct input of PCM audio and support for up to 5 audio streams
  • I2C controller and target modes for sensor control and integration
  • Up to 13 GPIO pins
  • Flexible clock generation
  • Onboard firmware decryption and authentication
  • 25-ball WLBGA package (0.4mm pitch)

The NDP115 supports dozens of application-defined audio sequences for a variety of use cases including:
  • Far-field, near-field and close-talk voice interface
  • Multiple wake words and local commands
  • Acoustic Echo Cancellation (AEC), noise suppression, beamforming
  • Speech enhancement
  • Speaker identification and verification
  • Acoustic event and scene classification
  • Multi-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.
NDP115

Characteristics

Additional information

DNN Core Memory

pmem: 448kB, dmem: 64kB

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: 64kB, dmem: 144kB

DSP Clock

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

DSP Features

HiFi3: Fixed-point

Package [mm]

2mm x 2mm 25-ball WLBGA

Product status

Active

NDP115

Home / Products / Processors / Neural Decision Processors / NDP115
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® NDP115 Neural Decision Processor™ is a special purpose chip deep learning and is ideal for always-on applications in battery powered devices and other power constrained systems. The NDP115 applies neural processing to run multiple applications simultaneously with minimal power consumption. Built using the Syntiant Core 2™ programmable deep learning architecture, NDP115 is designed to natively run multiple Deep Neural Networks (DNN) on a variety of architectures, such as CNN, RNN and fully connected networks. NDP115 brings a level of ML performance that delivers 25x the tensor throughput compared to the Syntiant Core 1™ embedded in Syntiant’s NDP100 and NDP101 devices, and is able to run speech inferences at a mere 280 microwatts. A programmable HiFi 3 DSP is available for flexible feature extraction classical audio processing.

  • Syntiant Core 2TM neural processor
  • Support for concurrent neural networks
  • Embedded user programmable HiFi-3 DSP with 144KB 64 bit data RAM and 64KB 64 bit instruction RAM
  • Deeply embedded Arm Cortex MO microcontroller for device management with 48KB SRAM, dual-timers, and UART functionality
  • Direct input of PCM audio and support for up to 5 audio streams
  • I2C controller and target modes for sensor control and integration
  • Up to 13 GPIO pins
  • Flexible clock generation
  • Onboard firmware decryption and authentication
  • 25-ball WLBGA package (0.4mm pitch)

The NDP115 supports dozens of application-defined audio sequences for a variety of use cases including:
  • Far-field, near-field and close-talk voice interface
  • Multiple wake words and local commands
  • Acoustic Echo Cancellation (AEC), noise suppression, beamforming
  • Speech enhancement
  • Speaker identification and verification
  • Acoustic event and scene classification
  • Multi-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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NDP115

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