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AMD VCK5000 Versal™ Development Card

The AMD VCK5000 Versal™ development card is built on the AMD 7nm Versal adaptive SoC architecture and is designed to optimize 5G, data center compute, AI, signal processing, radar, and many other applications. Fully supported by Vitis™, Vitis AI, and partner solutions like Mipsology Zebra® and Aupera® VMSS, the VCK5000 domain-specific architecture brings strong horsepower per watt while keeping ease-of-use in mind with C/C++, software programmability. Delivering the near 100% compute efficiency per watt in standard AI benchmarks and 2x TCO compared to the flagship nVidia GPUs, the VCK5000 development platform is ideal for CNN, RNN, and NLP acceleration for your cloud and edge applications.

Price: $13,195.00
Part Number:
- DK-VCK5000-G-ED
Lead Time: 8 weeks
Device Support: Versal AI Core

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Note: Lead times are for AMD direct orders of 10 units or less. For lead times on larger quantities, contact customer service.

Product Information

AI Inference
AI Engine
Specifications

AI Inference Development

If you are an AI developer, bring your TensorFlow and PyTorch trained models to directly infer on Versal using Mipsology Zebra and build, configure, and deploy computer vision applications on FPGA platforms with Aupera Video Machine Learning Streaming Server solution.

Key Features

2x TCO Reduction vs Mainstream nVidia GPUs

2x perf/w and perf/$ compared to Nvidia Ampere with standard MLPerf Models
Achieves 90% compute efficiency
Consume less than 100W at card level

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2x End-to-End Video Analytics Throughput vs nVidia GPUs

Full pipeline from H.264 decode to computer vision to up to 10 AI models
Video decode and CV run on x86 CPU or discrete U30 Alveo card
Plug-in based pipeline composition from FFmpeg / Gstreamer

_{ML Heavy: H.264 Decode + Yolov3 + 3x ResNet-18}
_{Video Heavy: H.264 Decode + tinyYolov3 + 3x ResNet-50}

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Easy to Use with Familiar Frameworks

Easy-to-use software flow for any CPU & GPU users, no hardware programming required
Run inference from Tensorflow framework directly on board
State-of-the-art model supported with mainstream frameworks PyTorch, TensorFlow, TensoFlow 2 and Caffe

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Partner Solutions

Mipsology Zebra Software

Zebra combines high performance with unprecedented ease of use and is AMD's preferred AI accelerator for computing neural networks for image-based AI applications.

Zebra seamlessly replaces GPU/CPU to compute any image based neural network faster and with lower power consumption. And with Zebra, there is no need to retrain or make any changes to your network or application. Zebra deploys with a simple Linnux command, so you don’t need FPGA knowledge to use Zebra.

Get 5 free demo hours of Zebra in the VMAccel® cloud

Buy

Download Solution Brief

Contact Mipsology

Aupera Video Machine Learning Streaming Server Solution

Aupera VMSS is a software framework for Video AI inferencing applications. VMSS2.0 allows users to rapidly build, configure, and deploy Computer Vision pipelines using a graphical user interface (GUI); with no coding. Custom pipelines can be easily built using Aupera’s node toolkit, decoding, pre-processing, post-processing, etc.; or by creating custom nodes which can be uploaded, built, tested, and used all from the GUI.

Aupera’s commercial video AI applications can also be configured, launched, and visualized through this framework. Users have a choice of checking the results of their custom pipeline through video overlays or by sending text output.

Get 5 free demo hours of VMSS 2.0 in the VMAccel® cloud

Buy

Download Solution Brief

Download User Guide

AI Engine Development

If you are looking to implement algorithm acceleration with AI engine and programmable logic, we provide AI engine C/C++ high-level abstraction APIs and Vitis Accelerated Libraries. The Vitis end-to-end flow is developed using C/C++ to run on X86 or embedded processors and manage runtime interactions with the accelerator with XRT. The hardware component, or kernel, can be developed using C/C++, or RTL target on PL or AI Engines.

Key Features

Power and Performance

Up to 10x performance improvements compared to previous generation AMD UltraScale+™ with less power in diverse applications
Industry-leading compute power: up 145 TOPS (int8); 37 TOPS (int16); 12T FLOPs (fp32)

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Software Familiarity

A familiar software development flow with Vitis unified software platform
Accelerate your applications faster with AI engine C/C++ high-level abstraction APIs and Vitis Accelerated Libraries

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Mixed Kernel Development

Customize your own data pipeline with mixed kernels
Develop AIE kernels in C/C++, PL kernels in RTL or HLS, and let Vitis stitch together the full system

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Get Started with AI Engine Development

Step 1: Purchase

Purchase VCK5000 production silicon-based card

Buy

Step 2: Access Secure Site

Request access to the VCK5000 Versal Development Card Secure Site

Step 3: Get Started

Follow the getting started steps and installation guide in the VCK5000 Versal Development Card Secure Site

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Resources

VCK5000 Documentation

_{Certain AMD technologies may require third-party enablement or activation. Supported features may vary by operating system. Please confirm with system manufacturer for specific features. No technology or product can be completely secure.}

Board Specifications	Value
Height	12.225 inch (31.05 cm)
Width	10.675 inch (27.11 cm)
Thickness (+/-5%)	0.119 inch (0.302 cm)
Operating Environmental Temperature	0◦C to +45◦C
Storage Environmental Temperature	-25◦C to +60◦C

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AMD VCK5000 Versal™ Development Card

Product Information

AI Inference Development

Key Features

Explore partner solutions and articles, and learn about the key features for AI Inference Development with the VCK5000.

2x TCO Reduction vs Mainstream nVidia GPUs

2x End-to-End Video Analytics Throughput vs nVidia GPUs

Easy to Use with Familiar Frameworks

Partner Solutions

Mipsology Zebra AI Inference Solutions & Aupera Video Machine Learning Streaming Server

Mipsology Zebra Software

Aupera Video Machine Learning Streaming Server Solution

Power and Performance

Software Familiarity

Mixed Kernel Development

Step 1: Purchase

Step 2: Access Secure Site

Step 3: Get Started

Resources

Documentation