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Qnap
Accelerator
Mustang-F100-A10-R10
PCIe v3 x8, Arria 10 GX1150 FPGA, 8GB DDR4




Qnap Qnap

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Stock codeIBQ-QAMF100-A10
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PCIe
8GB RAM
Intel Arria 10 GX1150 FPGA
2yr Warranty
Description
Qnap Mustang-F100
Intel® Vision Accelerator Design with Intel® Arria® 10 FPGA

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-F100 is a PCIe-based accelerator card using the programmable Intel® Arria® 10 FPGA that provides the performance and versatility of FPGA acceleration. 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, double-slot. Power-efficiency, low-latency. Supported OpenVINO™ toolkit, AI edge computing ready device. FPGAs can be optimized for different deep learning tasks. Intel® FPGAs supports multiple float-points and inference workloads.
Mustang-F100-A10-R10
PCIe FPGA Highest Performance Accelerator Card with Arria 10 1150GX support DDR4 2400Hz 8GB, PCIe Gen3 x8 interface

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-F100 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-F100 can also work with Intel® OpenVINO™ toolkit to optimize inference workloads for image classification and computer vision.

Operating Systems
Ubuntu 16.04.3 LTS 64bit, CentOS 7.4 64bit (Support Windows 10 in Mar. 2019 & 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, Tiny Yolo, LeNet, SqueezeNet, VGG16, ResNet (more variants are coming soon)
Intel® FPGA Deep Learning Acceleration Suite
High flexibility, Mustang-F100-A10 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-F100 to achieve optimal performance for running inference.

Note: 
1. QTS 4.4.0 (or later) and OWCT v1.0 are required for the QNAP NAS. (OWCT v1.0 coming soon)
2. To use FPGA card computing on the QNAP NAS, the VM pass-through function will be disabled. To avoid potential data loss, make sure that all ongoing NAS tasks are finished before restarting.
Mustang-F100-A10   Main FPGA Intel® Arria® 10 GX1150 FPGA Operating Systems PC: Ubuntu 16.04.3 LTS 64-bit, CentOS 7.4 64-bit (Support Windows 10 in Mar. 2019 & more OS are coming soon)
NAS: QTS Voltage Regulator and Power Supply Intel® Enpirion® Power Solutions Memory 8G on board DDR4 Dataplane Interface PCI Express x8
Compliant with PCI Express Specification V3.0 Power Consumption (W) <60W Operating Temperature & Relative Humidity 5°C~60°C (ambient temperature),5% ~ 90% Cooling Active fan: (50 x 50 x 10 mm) x 2 Dimensions 169.5 mm x 68.7 mm x 33.7 mm Power Connector *Preserved PCIe 6-pin 12V external power Dip Switch/LED indicator Support up to 8 cards. Please assign a card ID number (from 0 to 7) to the Mustang-F100 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.
  Check Compatible NAS Models 28-Bay TS-2888X 24-Bay TVS-2472XU-RP 16-Bay TVS-1672XU-RP 12-Bay TVS-1272XU-RP 8-Bay TVS-872XT, TVS-872XU, TVS-872XU-RP 6-Bay TVS-672XT 4-Bay TVS-472XT Note: 
Please remove the Thunderbolt 3 PCIe card from the TVS-472XT, TVS-672XT and TVS-872XT in order to install the Mustang-F100  
Specifications
Specifications

General

Stock code IBQ-QAMF100-A10
Brand Qnap
Series Accelerator
Model Mustang-F100-A10-R10
Type PCIe v3 x8, Arria 10 GX1150 FPGA, 8GB DDR4
ROHS Y
Date added 20/02/2019

Mustang-F100-A10-R10 Spec Information

Form Factor / Drive Height 169.5 x 68.7 x 33.7 mm
RAM/Cache 8GB
Guarantee 2yr
Processor Intel Arria 10 GX1150 FPGA

Software

Mustang-F100-A10-R10 Speed

Physical

Weight (kg) 1kg
Watts <60W
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Stock codeIBQ-QAMF100-A10
Quick code69466



Qnap
Accelerator
Mustang-F100-A10-R10
PCIe v3 x8, Arria 10 GX1150 FPGA, 8GB DDR4



ddr4-ramintel-inside







why choose span.com

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£1,808.00
£2,169.60
ex.VAT $2,378.94
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Description

Qnap Accelerator Mustang-F100-A10-R10 PCIe v3 x8, Arria 10 GX1150 FPGA, 8GB DDR4


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Qnap MustangF100A10R10 Key features


PCIe
8GB RAM
Intel Arria 10 GX1150 FPGA
2yr Warranty


Qnap Mustang-F100
Intel® Vision Accelerator Design with Intel® Arria® 10 FPGA

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-F100 is a PCIe-based accelerator card using the programmable Intel® Arria® 10 FPGA that provides the performance and versatility of FPGA acceleration. 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, double-slot.
  • Power-efficiency, low-latency.
  • Supported OpenVINO™ toolkit, AI edge computing ready device.
  • FPGAs can be optimized for different deep learning tasks.
  • Intel® FPGAs supports multiple float-points and inference workloads.


Mustang-F100-A10-R10
PCIe FPGA Highest Performance Accelerator Card with Arria 10 1150GX support DDR4 2400Hz 8GB, PCIe Gen3 x8 interface

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-F100 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-F100 can also work with Intel® OpenVINO™ toolkit to optimize inference workloads for image classification and computer vision.

Operating Systems
Ubuntu 16.04.3 LTS 64bit, CentOS 7.4 64bit (Support Windows 10 in Mar. 2019 & 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, Tiny Yolo, LeNet, SqueezeNet, VGG16, ResNet (more variants are coming soon)
Intel® FPGA Deep Learning Acceleration Suite
High flexibility, Mustang-F100-A10 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-F100 to achieve optimal performance for running inference.

Note: 
1. QTS 4.4.0 (or later) and OWCT v1.0 are required for the QNAP NAS. (OWCT v1.0 coming soon)
2. To use FPGA card computing on the QNAP NAS, the VM pass-through function will be disabled. To avoid potential data loss, make sure that all ongoing NAS tasks are finished before restarting.

Mustang-F100-A10

 

Main FPGA

Intel® Arria® 10 GX1150 FPGA

Operating Systems

PC: Ubuntu 16.04.3 LTS 64-bit, CentOS 7.4 64-bit (Support Windows 10 in Mar. 2019 & more OS are coming soon)
NAS: QTS

Voltage Regulator and Power Supply

Intel® Enpirion® Power Solutions

Memory

8G on board DDR4

Dataplane Interface

PCI Express x8
Compliant with PCI Express Specification V3.0

Power Consumption (W)

<60W

Operating Temperature & Relative Humidity

5°C~60°C (ambient temperature),5% ~ 90%

Cooling

Active fan: (50 x 50 x 10 mm) x 2

Dimensions

169.5 mm x 68.7 mm x 33.7 mm

Power Connector

*Preserved PCIe 6-pin 12V external power

Dip Switch/LED indicator

Support up to 8 cards. Please assign a card ID number (from 0 to 7) to the Mustang-F100 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.

 

Check Compatible NAS Models

28-Bay

TS-2888X

24-Bay

TVS-2472XU-RP

16-Bay

TVS-1672XU-RP

12-Bay

TVS-1272XU-RP

8-Bay

TVS-872XT, TVS-872XU, TVS-872XU-RP

6-Bay

TVS-672XT

4-Bay

TVS-472XT

Note: 
Please remove the Thunderbolt 3 PCIe card from the TVS-472XT, TVS-672XT and TVS-872XT in order to install the Mustang-F100

 






How to install Kodi and Netflix on your QNAP NAS in 2019
Our Brief Guide to installing KODI on your NAS
how to install kodi on qnap


Specifications

General

Stock code IBQ-QAMF100-A10
Brand Qnap
Series Accelerator
Model Mustang-F100-A10-R10
Type PCIe v3 x8, Arria 10 GX1150 FPGA, 8GB DDR4
ROHS Y
Date added 20/02/2019

Mustang-F100-A10-R10 Spec Information

Form Factor / Drive Height 169.5 x 68.7 x 33.7 mm
RAM/Cache 8GB
Guarantee 2yr
Processor Intel Arria 10 GX1150 FPGA

Software

Mustang-F100-A10-R10 Speed

Physical

Weight (kg) 1kg
Watts <60W
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