Intel® Vision Accelerator Design with Intel® Movidius™ VPU
Computing Accelerator Card with 8 x Movidius Myriad X MA2485 VPU, PCIe Gen2 x4 interface, RoHS
As QNAP NAS evolves to support a wider range of applications (including surveillance, virtualization, and AI) you not only need more storage space on your NAS, but also require the NAS to have greater power to optimize targeted workloads. The Mustang-V100 is a PCIe-based accelerator card using an Intel® Movidius™ VPU that drives the demanding workloads of modern computer vision and AI applications. It can be installed in a PC or compatible QNAP NAS to boost performance as a perfect choice for AI deep learning inference workloads. >> Difference between Mustang-F100 and Mustang-V100.
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.
Get deep learning acceleration on Intel-based Server/PC
You can insert the Mustang-V100 into a PC/workstation running Linux® (Ubuntu®) to acquire computational acceleration for optimal application performance such as deep learning inference, video streaming, and data center. As an ideal acceleration solution for real-time AI inference, the Mustang-V100 can also work with Intel® OpenVINO™ toolkit to optimize inference workloads for image classification and computer vision.
Ubuntu 16.04.3 LTS 64-bit, CentOS 7.4 64-bit, Windows 10 (More OS are coming soon)
OpenVINO™ ToolkitIntel® 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 Khronos
QNAP NAS as an Inference Server
OpenVINO™ toolkit extends workloads across Intel® hardware (including accelerators) and maximizes performance. When used with QNAP’s OpenVINO™ Workflow Consolidation Tool, the Intel®-based QNAP NAS presents an ideal Inference Server that assists organizations in quickly building an inference system. Providing a model optimizer and inference engine, the OpenVINO™ toolkit is easy to use and flexible for high-performance, low-latency computer vision that improves deep learning inference. AI developers can deploy trained models on a QNAP NAS for inference, and install the Mustang-V100 to achieve optimal performance for running inference.
Note: QTS 4.4.0 (or later) and OWCT v1.1.0 are required for the QNAP NAS.
Easy-to-manage Inference Engine with QNAP OWCT
Upload a video file -> Download inference result
Check Compatible NAS Models
TVS-872XT, TVS-872XU, TVS-872XU-RP
1. Check Compatibility List for more supported models.
2. Installing “Mustang Card User Driver” in the QTS App Center is required.
Eight Intel® Movidius™ Myriad™ X MA2485 VPU
PC: Ubuntu 16.04.3 LTS 64-bit, CentOS 7.4 64-bit, Windows 10 (More OS are coming soon)
NAS: QTS (Installing “Mustang Card User Driver” in the App Center is required.)
PCI Express x4
Compliant with PCI Express Specification V2.0
Power Consumption (W)
Operating Temperature & Relative Humidity
5°C~55°C (ambient temperature)，5% ~ 90%
Active fan: 47 x 47 x 9.4 mm
169.54 mm x 80.05 mm x 23.16 mm
*Preserved PCIe 6-pin 12V external power
Dip Switch/LED indicator
Up to 16 cards can be supported with operating systems other than QTS; QNAP TS-2888X NAS supports up to 8 cards. Please assign a card ID number (from 0 to 15) to the Mustang-V100 by using rotary switch manually. The card ID number assigned here will be shown on the LED display of the card after power-up.
*Standard PCIe slot provides 75W power, this feature is preserved for user in case of different system configuration
Compatibility for Mustang-V100:
TVS-472XT, TVS-672N, TVS-672XT, TS-883XU, TS-883XU-RP, TVS-872N, TVS-872XT, TVS-872XU, TVS-872XU-RP, TVS-882, TVS-882BR, TVS-882BRT3, TVS-882T, TS-1283XU-RP, TS-h1283XU-RP, TVS-1272XU-RP, TVS-1282, TVS-1282T, TVS-1282T3, TS-1683XU-RP, TS-1685, TVS-1672XU-RP, TS-2483XU-RP, TVS-2472XU-RP, TS-983XU, TS-983XU-RP, TVS-972XU, TVS-972XU-RP, QVP-63A, QVP-85A, TS-h686, TS-h886, TS-h1683XU-RP, TS-h2483XU-RP, TVS-h1288X, TVS-h1688X
| Stock code || IBQ-QAMV100-MX8|
| Brand || Qnap|
| Series || Accelerator|
| Model || Mustang-V100-MX8-R10|
| Type || PCIe v2 x4, Eight Intel Movidius Myriad X MA2485 VPU|
| UPC || 842936100894|
| ROHS || Y|
| Date added || 16/05/2019|
Mustang-V100-MX8-R10 Spec Information
| Form Factor / Drive Height || 169.5 x 80 x 23 mm|
| Guarantee || 2yr|
| Processor || Eight Intel® Movidius™ Myriad™ X MA2485 VPU|
| Weight (kg) || 1kg|
| Watts || <30W|