Intel® Vision Accelerator Design With Intel® Movidius™ Vision Processing Unit (VPU)


Specialized processors designed to deliver high-performance machine vision at ultra-low power.

  • Supports up to 16 video streams per device
  • Ideal for camera and network video recorder (NVR) use cases with power, size, and cost constraints
  • Supports small memory footprint networks

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Overview

Deep Neural Networks

Optimized for computer vision applications built using deep neural networks for low power, low cost, and small form factors

Power Efficiency

Ultra-low-power demands allow for integration on cameras and edge servers running on power- and size-constrained systems

Easy to Scale

Scalable analytics with minimal software changes for single- to multiple-chip solutions

Who Needs This Product

Information and operational technologists who:

  • Are new to IoT commercial platforms and need a simple path without a steep learning curve
  • Create solutions that offload deep learning and AI workloads from the CPU or GPU to dedicated accelerator products
  • Need a quicker path to deployment

Use Cases

  • Smart cities
  • Automotive and transportation
  • Healthcare
  • Retail
  • Digital Security

Specifications

Intel® Vision Accelerator Design

Features With 1 Intel® Movidius™ VPU With 2 Intel Movidius VPUs With 8 Intel Movidius VPUs
VPU 1 - MA2485 2 - MA2485 8 - MA2485
Board dimensions

M.2 2230 Key E & A

22 mm x 30 mm

M-PCIe*

30 mm x 50 mm

Half-height, half-length, single-slot PCIe*

68.90 mm x 167.65 mm

VPU memory 4 Gb LPDDR4 POP 4 Gb LPDDR4 POP 4 Gb LPDDR4 POP
Minimum system configuration

Intel Atom® x7 processor E3950

8 GB LPDDR4, 64 GB eMMC

USB 3.0, M.2 2230 connector

Intel Atom x7 processor E3950

8 GB LPDDR4, 64 GB eMMC

USB 3.0, M-PCIe connector

Intel® Core™ i5 processor 6500TE

8 GB RAM, 500 GB HDD

USB 3.0

2 - PCIe x4 x8 x16 connectors

Typical operating system Ubuntu* 16.04 LTS 64 bit Ubuntu 16.04 LTS 64 bit Ubuntu 16.04 LTS 64 bit
Tools Intel® Distribution of OpenVINO™ toolkit Intel Distribution of OpenVINO toolkit Intel Distribution of OpenVINO toolkit

General Specifications

Supported Streams

Typically supports 1 to 16 video streams per device (depends on desired frame rate and algorithm complexity)

Efficiency

High efficiency

Precision

Supports FP16 precision networks

Customization

Hardware optimized for generic cases

Suppliers

Purchase or review documentation from the suppliers below.