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Mustang-V100-MX8 - Vision Accelerator Card with Intel Movidius VPU

PCIe Vision Accelerator Card with 8 x Movidius VPU
Datasheet

Mustang-V100-MX8

Accelerate To The Future

Intel® Vision Accelerator Design with Intel® Movidius™ VPU.

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A Perfect Choice for AI Deep Learning Inference Workloads

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Powered by Open Visual Inference & Neural Network Optimization (OpenVINO™) toolkit

  • Half-Height, Half-Length, Single-Slot compact size
  • Low power consumption ,approximate 2.5W for each Intel® Movidius™ Myriad™ X VPU.
  • Supported OpenVINO™ toolkit, AI edge computing ready device
  • Eight Intel® Movidius™ Myriad™ X VPU can execute eight topologies simultaneously.

 

OpenVINO™ toolkit

OpenVINO™ toolkit is based on convolutional neural networks (CNN), the toolkit extends workloads across Intel® hardware and maximizes performance.
It can optimize pre-trained deep learning model such as Caffe, MXNET, Tensorflow into IR binary file then execute the inference engine across Intel®-hardware heterogeneously such as CPU, GPU, Intel® Movidius™ Neural Compute Stick, and FPGA.

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Applications

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Machine Vision Smart Retail
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Surveillance Medical Diagnostics

 

Overview

Powered by Open Visual Inference & Neural Network Optimization (OpenVINO™) toolkit. Half-Height, Half-Length, Single-Slot compact size. Low power consumption ,approximate 2.5W for each Intel® Movidius™ Myriad™ X VPU. Supported OpenVINO™ toolkit, AI edge computing ready device. Eight Intel® Movidius™ Myriad™ X VPU can execute eight topologies simultaneously.OpenVINO™ toolkit is based on convolutional neural networks (CNN), the toolkit extends workloads across Intel® hardware and maximizes performance. It can optimize pre-trained deep learning model such as Caffe, MXNET, Tensorflow into IR binary file then execute the inference engine across Intel®-hardware heterogeneously such as CPU, GPU, Intel® Movidius™ Neural Compute Stick, and FPGA.

Features

  • Operating Systems
    • Ubuntu 16.04.3 LTS 64bit, CentOS 7.4 64bit (Support Windows 10 in the end of 2018 & more OS are coming soon)
  • OpenVINO™ Toolkit
  • Intel® Deep Learning Deployment Toolkit
    • Model Optimizer
    • Inference Engine
  • Optimized computer vision libraries
  • Intel® Media SDK
  • *OpenCL™ graphics drivers and runtimes.
  • Current Supported Topologies: AlexNet, GoogleNet V1, Yolo Tiny V1 & V2, Yolo V2, SSD300, ResNet-18, Faster-RCNN. (more variants are coming soon)
  • High flexibility, Mustang-V100-MX8 develop on OpenVINO™ toolkit structure which allows trained data such as Caffe, TensorFlow, and MXNet to execute on it after convert to optimized IR.

*OpenCL™ is the trademark of Apple Inc. used by permission by KhronosVision Accelerator Card with 8 x Movidius VPU

 

Specification

Model Name Mustang-V100-MX8 Mustang-V100-MX4 Mustang-MPCIE-MX2 Mustang-M2AE-MX1
Main Chip Eight Intel® Movidius Myriad X MA2485 VPU 4 x Intel Movidius Myriad X MA2485 VPU 2 x Intel Movidius Myriad X MA2485 VPU 1 x Intel® Movidius Myriad X MA2485 VPU
Operating Systems Ubuntu 16.04.3 LTS 64bit, CentOS 7.4 64bit (Support Windows 10 in the end of 2018 & more OS are coming soon) Ubuntu 16.04.3 LTS 64bit, CentOS 7.4 64bit, Windows 10 64bit Ubuntu 16.04.3 LTS 64bit, CentOS 7.4 64bit, Windows 10 64bit Ubuntu 16.04.3 LTS 64bit, CentOS 7.4 64bit, Windows 10 64bit
Dataplane Interface PCI Express x4 PCIe Gen 2 x 2 miniPCIe M.2 AE Key
Power Consumption <30W 15W Approximate 7.5W Approxinate 5W
Operating Temperature 5°C~55°C(ambient temperature) 0°C~55°C (In TANK AIoT Dev. Kit) 0°C~55°C (In TANK AIoT Dev. Kit) 0°C~55°C (In TANK AIoT Dev. Kit)
Cooling Active fan Active fan Passive/Active Heatsink Passive Heatsink
Dimensions Half-Height, Half-Length, Single-width PCIe 113 x 56 x 23 mm 30 x 50 mm 22 x 30 mm
Support Topology AlexNet, GoogleNet V1/V2/V4, Yolo Tiny V1/V2, Yolo V2/V3, SSD300,SSD512, ResNet-18/50/101/152,

DenseNet121/161/169/201, SqueezeNet 1.0/1.1, VGG16/19, MobileNet-SSD, Inception-ResNetv2,

Inception-V1/V2/V3/V4,SSD-MobileNet-V2-coco, MobileNet-V1-0.25-128, MobileNet-V1-0.50-160,

MobileNet-V1-1.0-224, MobileNet-V1/V2, Faster-RCNN
AlexNet, GoogleNetV1/V2, Mobile_SSD, MobileNetV1/V2, MTCNN, Squeezenet1.0/1.1, Tiny Yolo V1 & V2, Yolo V2, ResNet-18/50/101 AlexNet, GoogleNetV1/V2, Mobile_SSD, MobileNetV1/V2, MTCNN, Squeezenet1.0/1.1, Tiny Yolo V1 & V2, Yolo V2, ResNet-18/50/101 AlexNet, GoogleNetV1/V2, Mobile_SSD, MobileNetV1/V2, MTCNN, Squeezenet1.0/1.1, Tiny Yolo V1 & V2, Yolo V2, ResNet-18/50/1015% ~ 90%
Operating Humidity 5% ~ 90% 5% ~ 90% 5% ~ 90% 5% ~ 90%

*Standard PCIe slot provides 75W power, this feature is preserved for user in case of different system configuration

 

Ordering Information

Part No. Description
Mustang-V100-MX8-R10 Computing Accelerator Card with 8 x Movidius Myriad X MA2485 VPU, PCIe Gen2 x4 interface, RoHS
Mustang-V100-MX4-R10 Computing Accelerator Card with 4x Intel Movidius Myriad X MA2485 VPU, PCIe Gen 2 x 2 interface, RoHS
Mustang-MPCIE-MX1 Deep learning inference accelerating miniPCIe card with 2 x Intel Movidius Myriad X MA2485 VPU, miniPCIe interface 30mm x 50mm, RoHS
Mustang-M2AE-MX1 Computing Accelerator Card with 1 x Intel Movidius Myriad X MA2485 VPU,M.2 AE key interface, 2230, RoHS
Mustang-M2BM-MX2-R10 Deep learning inference accelerating M.2 BM key card with 2 x Intel Movidius Myriad X MA2485 VPU, M.2 interface 22mm x 80mm, RoHS


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