MUSTANG-F100-A10-R10 MUSTANG-F100-A10-R10 MUSTANG-F100-A10-R10 MUSTANG-F100-A10-R10


Low-Profile PCIe FPGA Vision Accelerator Card with Intel Arria 10 GX 1150 FPGA, 8GB DDR4, PCIe Gen3 x8 interface, native Intel OpenVINO support
MFR Part

Intel Vision Accelerator Design with Arria 10 FPGA

The MUSTANG-F100-A10 is an Intel Vision Accelerator Design with Intel Arria 10 FPGA, offers exceptional performance, flexibility, and scalability for deep-learning and computer-vision solutions—from NVRs (network video recorders) to edge deep-learning inference appliances to on-premises servers—at a fraction of the cost and with significantly lower power requirements than most of the existing FPGA PCIe cards currently on the market.

The programmable, software-defined Intel Arria 10 FPGA ensures continual performance optimization—taking advantage of periodic FPGA bitstream updates provided by Intel—without necessitating hardware upgrades. The MUSTANG-F100-A10 is designed for long product life (15 years of longevity) and can adapt to a wide range of work conditions, including harsh industrial and/or outdoor environments.

Unlike fixed-function devices, functionality in the Intel Arria 10 FPGA can always be changed or modified to increase or deepen intelligence, which allows the MUSTANG-F100-A10 to be architected to solve very specific problems. And when used for deep learning inference, the MUSTANG-F100-A10 is able to achieve high-performance images per second at reduced power while providing dynamic flexibility, consistent power consumption, and future-proofing for custom or new workloads as well as low latency across a wide spectrum of vision use cases and applications.

The Intel Vision Accelerator Design with Intel Arria 10 FPGA offers a simplified path for developers to run customized topologies in an optimal way and works seamlessly with the OpenVINO toolkit. Fine-grained parallelism enables high throughput on low-batch workloads. The extremely high, fine-grained, on-chip memory bandwidth can more efficiently solve memory challenges. With the OpenVINO toolkit, you don’t need to be an FPGA expert to code applications integrating computer vision.

The MUSTANG-F100-A10 can support more than 20 channels of video inputs, along with vision use cases such as facial detection and recognition. Optimized network topologies include GoogLeNet v1, ResNet-18/50/101, SqeezeNet v1.1, VGG-16, and MobileNet v1. More hardware accelerated topologies are coming with new OpenVINO toolkit releases. Customizable data paths and precision create energy-efficient dataflow for system level optimization. The MUSTANG-F100-A10 is also ideal for complex or large workloads as well as customized applications and use cases where you may want to add your own primitives or sub-layer configurations.

Because of their innate adaptability, FPGAs are always on the cutting edge of new solutions and changing network topologies. This flexibility, and the ability to accelerate algorithm processing, make this Intel Vision Accelerator Design invaluable for complex, massive deep-learning analysis and visual intelligence.


  • Intel Arria 10 GX1150 FPGA and 8GB of DDR4
  • Low-profile card with PCI Express Gen3 x8 interface
  • Supports Ubuntu 16.04.3 LTS 64-bit, CentOS 7.4 64-bit, and Windows 10 64-bit
  • Supported natively by the Intel OpenVINO toolkit
  • Intel FPGAs supports multiple float-points and inference workloads
  • Supports popular deep learning frameworks such as Caffe, TensorFlow, Apache MXNet, and Open Neural Network Exchange (ONNX)
  • Easily deploy open source deep learning frameworks via Intel Deep Learning Deployment Toolkit.

Common Uses

  • Achieve optimized solutions through reprogramming flexibility
  • Deliver high-performance, on-device deep learning inferences at low power and low latency
  • Rapidly process and analyze vast streams of high-quality video data near the edge and respond in real time
  • Deploy compact form factor systems that are suitable at the edge for demanding imaging and video applications

Ordering Guide

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

USB FPGA download cable

MUSTANG-F100-A10 Block Diagram

MUSTANG-F100-A10 Block Diagram

OpenVINO Toolkit for Computer Vision and Deep Learning

The OpenVINO toolkit is a free, downloadable toolkit that helps developers fast-track the development of high performance computer vision and deep learning into flexible, cost-effective vision applications. It is designed to increase performance and reduce time to market for computer vision solutions. It simplifies access to the benefits from the rich set of hardware options available from Intel which can increase performance, reduce power, and maximize hardware utilization. OpenVINO enables deep learning on hardware accelerators and streamlined heterogeneous execution across multiple types of Intel platforms. It includes the Intel Deep Learning Deployment Toolkit with a model optimizer and inference engine, along with optimized computer vision libraries and functions for OpenCV and OpenVX. This comprehensive toolkit supports the full range of vision solutions, speeding computer vision workloads, streamlining deep-learning deployments, and enabling easy, heterogeneous execution across Intel platforms from device to cloud.

The OpenVINO toolkit brings a new level of customization: you can match performance to the application requirements, and then deploy it across any product in the Intel Vision Accelerator Design family. With Intel, you can select the right accelerator for camera, edge appliance, or cloud while using consistent APIs and runtimes. Code developed on the OpenVINO toolkit can be deployed across any of Intel’s architectures (CPU, CPU with integrated graphics, VPU or FPGA) to streamline time to market.

The MUSTANG-F100-A10 is an Intel Vision Accelerator Design with Intel Arria 10 FPGA GX, is half the height and half the length of a standard full-size FPGA add-in card, making it an ideal choice for anyone who needs a smaller form factor. This PCI Express (PCIe) acceleration card is supported natively by the OpenVINO toolkit to deliver high-performance low-latency video inference at the edge or the cloud. The MUSTANG-F100-A10 was designed from the ground up to be optimized for deep learning acceleration. Unlike other general-purpose FPGA with a myriad of features to support a variety of applications. Nonessential components that do not contribute to the goal of deep learning acceleration were removed from the design. Thereby reducing the size of the form factor and lowering the cost to an extremely competitive level. It has been designed to easily add acceleration capabilities to a multitude of PCIe host platforms, where a CPU or GPU lack the computational power for intense computer vision tasks in real time, at high frame rates.

Main FPGA Intel Arria 10 1150 GX FPGAs delivering up to 1.5 TFLOPs
Operating Systems Ubuntu 16.04.3 LTS 64-bit, CentOS 7.4 64-bit, and Windows 10 64-bit
Support for more operating systems coming soon
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
Cooling Active fan
Form Factor Low Profile Half-Height, Half-Length, Double-Slot (optional full height bracket included)
Power Consumption: < 60W, 38~42W typical
Power Connector 6-pin 12V external power
Standard PCIe slots provide 75W of power, this feature is for use in non-standard system configurations
Dip Switch/LED indicator Indicating device number for multiple card support
Operating Temperature 5°C to 60°C (ambient temperature)
Operating Humidity 5% ~ 90%
IEI MUSTANG-F100-A10-R10 Attributes
SKU 59839
Manufacturer IEI
Part Number MUSTANG-F100-A10-R10
Model MUSTANG-F100-A10
Description Low-Profile PCIe FPGA Vision Accelerator Card with Intel Arria 10 GX 1150 FPGA, 8GB DDR4, PCIe Gen3 x8 interface, native Intel OpenVINO support
Manufacturer Description PCIe FPGA Highest Performance Accelerator Card with Arria 10 1150GX support DDR4 2400Hz 8GB, PCIe Gen3 x8 interface
Condition New
Lifecycle Status Active
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