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Accelerate to The Future - Mustang-200, Computing Accelerator Card
Accelerate to The Future - Mustang-200, Computing Accelerator Card


Mustang-200 : Accelerate to The Future

In the era of information explosion, various digital services such as over-the-top (OTT), multiple-system operator (MSO), content delivery network (CDN), SaaS providers are faced with shortage of computing resources. These service providers need more computing power that is large and strong enough to cope with enormous amount of information, data, audio and video, etc. In the past, in the absence of space constraints, we will increase the number of servers to deal with huge amounts of data, but the space is still limited. In the limited space, we can only use FPGA expansion cards or GPU expansion cards to increase the performance of the server. However, these cards often have only one single function and are lack of flexibility. The only one solution is to create an intelligent, versatile, dense computing accelerator.

Therefore, Mustang-200 is born!

Overview :

● 10 Gigabit Ethernet based x86 computing nodes support decentralized computing architecture
● Perfectly integrated QNAP QTS-Lite provides a flexible and secure developing environment
● Support virtualization technology, virtual machine (VM) & container technology
● Fit standard server, compatible with PCI-Express x4, x8, x16
● Increase computing power without changing or adding servers
● Achieve higher densities computing and lower the total cost )

cloud-downloadDownload Mustang-200 Datasheet

QTS Lite - Software of the Mustang-200

The integrated QTS-Lite operating system supports various virtualization technologies such as containers and virtual machines, so you can convert your physical system into a virtual one (P2V) and assign it to one of the nodes on the Mustang-200. Performance can be instantly boosted without interruption or additional physical space requirements.
No matter what kind of software you use, it can be hosted inside the Mustang-200, allowing you to do more and achieve more in performancecritical applications such as artificial intelligence, academic research, and simulations.

Features :

*Real-time computing
*Batch computing
*Parallel processing
*Automatic load balancing in each computing node
*Combine multiple cards as cluster via QTS Lite
assign each node to compute at the same time
*Control and manage QTS Lite via APIs

3 ways to drive Mustang-200 Accelerator


Container Station :

Design your owned Container Applications


Virtualization Station :

Running your existing S/W application


Mustang-200 App (QPKG) Development :

Designed for use by professional software developers, network and system integrators, and independent software developers to construct complete hardware and software integration platforms and develop applications.

QTS Lite provides you MORE


Distribute tasks among units of Mustang-200

With Mustang-200, every additional CPU works independently, so you can assign tasks to any nodes of your choice, and have real-time control of every node works.
Distribute tasks among units of Mustang-200

Scalable infrastructure to suit your needs

The Mustang-200 needs no proprietary hardware and can be immediately installed into your existing system. If you need to perform additional calculations, you can always add additional Mustang-200 as they work independently from each other. The maximum amount of Mustang-200 is limited only by the number of available PCIe x4 slots in your system. This gives you enormous potential to expand your total computing capabilities.

Perfect for fog computing

With robust computing capabilities and scalable characteristics, the Mustang-200 is perfectly suited for fog/edge computing. With fog/edge computing, you can pre-process data generated within your organization or across your devices on-premise, to filter out irrelevant information and only keep valuable insights, and then further utilize them by sending or uploading to cloud platforms. You can save a great deal of cloud platform and bandwidth fees as your data to be analyzed is filtered and only relevant data will be further dealt with.
Perfect for fog computing



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