QNAP Mustang-V100

• PCIe-based accelerator card
• Boost your NAS/PC Computing power
• Half-height, half-length, single-slot compact size

Mustang-V100

Intel Vision Accelerator Design with Intel Movidius VPU

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.

• 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.

Available Models : Mustang-V100-MX8-R10

Computing Accelerator Card with 8 x Movidius Myriad X MA2485 VPU, PCIe Gen2 x4 interface, RoHS

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.

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.

• Operating Systems
  Ubuntu 16.04.3 LTS 64-bit, CentOS 7.4 64-bit, Windows 10 (More OS are coming soon)
• OpenVINO Toolkit
  • IntelDeep Learning Deployment Toolkit
    • - Model Optimizer
    • - Inference Engine
  • Optimized computer vision libraries
  • IntelMedia 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.

QNAP NAS as an Inference Server

OpenVINO toolkit extends workloads across Intel hardware (including accelerators) and maximizes performance. When used with QNAPs 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

Check Compatible NAS Models

Dimensions (Unit: mm)