Movidius Neural Network Compute Stick

  • RS Stock No. 139-3655
  • Mfr. Part No. NCSM2450.DK1
  • Manufacturer Intel
Technical data sheets
Legislation and Compliance
RoHS Certificate of Compliance
COO (Country of Origin): US
Product Details

Movidius Neural Compute Stick

The Neural Network Compute Stick from Movidius™ allows Deep Neural Network development without the need for expensive, power-hungry supercomputer hardware. Simply prototype and tune the Deep Neural Network with the 100Gflops of computing power provided by the Movidius stick. A Cloud connection is not required. The USB stick form-factor makes for easy connection to a host PC while the on-board Myriad-2 Vision Processing Unit (VPU) delivers the necessary computational performance. The Myriad-2 achieves high-efficiency parallel processing courtesy of its twelve Very Long Instruction Word (VLIW) processors. The decision on parallel scheduling is carried out at program compile time, relieving the processors of this chore at run-time.


• Movidius 600MHz Myriad-2 SoC with 12 x 128-bit VLIW SHAVE vector processors • 2MB of 400Gbps transfer-rate on-chip memory
• Supports FP16, FP32 and integer operations with 8-, 16- and 32-bit accuracy
• All data and power provided over a single USB 3.0 port on a host PC
• Real-time, on-device inference without Cloud connectivity
• Quickly deploy existing CNN models or uniquely trained networks
• Multiple Movidius Sticks can be networked to the host PC via a suitable hub
• Dimensions: 72.5 x 27 x 14mm


Automatically convert a trained Caffe-based Convolutional Neural Network (CNN) into an embedded neural network optimized for the on-board Myriad-2 VPU. The SDK also supports TensorFlow.


Layer-by-layer performance metrics for both industry-standard and custom-designed neural networks enable effective tuning for optimal real-world performance at ultra-low power. Validation scripts allow developers to compare the accuracy of the optimized model on the device to the original PC-based model.


The Movidius Stick can behave as a discrete neural network accelerator by adding dedicated deep learning inference capabilities to existing computing platforms for improved performance and power efficiency.

Attribute Value
Classification Compute Stick
Name Movidius
Processor Family Name Myriad
Processor Part Number Myriad-2
Processor Type SoC
28 : Next working day
835 Within 5 working day(s) (Global stock)
Price (ex. GST) Each
$ 138.81
(exc. GST)
$ 159.63
(inc. GST)
Per unit
1 +
Related Products
On-chip debugging emulator for Renesas Electronics microcontrollers (M16C, ...
On-chip debugging emulator for Renesas Electronics microcontrollers (M16C, H8, 740 family),Follow-on model from E8 Emulator. Real-time emulation possible with CPU operating at maximum frequencyAdequate break and trace functions installed for Tiny microcomputer system developmentSupport memory expansion mode ...
SAM-ICE is a JTAG emulator designed for all ...
SAM-ICE is a JTAG emulator designed for all Atmel AT91 ARM7/ARM9/Cortex-M3 cores. Features & Benefits of the AT91SAM-ICE JTAG Emulator•Any ARM7/ARM9/Cortex-M3 Atmel core supported, including Thumb™ mode•Serial Wire Debug (SWD) supported since SAM-ICE hardware version 6•Serial Wire Viewer (SWV) ...
The Digilent Pmod AD1 is a two-channel, 12-bit ...
The Digilent Pmod AD1 is a two-channel, 12-bit ADC module featuring the Analog Devices AD7476A device. • Simultaneous A/D conversion at up to 1MSPS per channel• Dual 2-pole Sallen-Key anti-alias filters• Host communication: SPI bus• 6-pin Pmod connector with GPIO ...
The Pmod GPS utilizes the MediaTeK GPS MT3329 ...
The Pmod GPS utilizes the MediaTeK GPS MT3329 device on a GlobalTop FGPMMOPA6H GPS antenna module to receive positional data from GPS satellites. • Ultra-sensitive GPS module (-165dBm)• Low power consumption• Up to 10Hz update rate• Host communication: serial UART• ...