Optimal Artificial Intelligence Inference from Edge to Cloud
The Vitis™ AI development environment is Xilinx’s development platform for AI inference on Xilinx hardware platforms, including both edge devices and Alveo™ cards. It consists of optimized IP, tools, libraries, models, and example designs. It is designed with high efficiency and ease-of-use in mind, unleashing the full potential of AI acceleration on Xilinx FPGA and ACAP.
How your development works with Vitis AI:
- Supports mainstream frameworks and the latest models capable of diverse deep learning tasks
- Provides a comprehensive set of pre-optimized models that are ready to deploy on Xilinx devices. You can find the closest model and start re-training for your applications!
- Provides a powerful open source quantizer that supports pruned and unpruned model quantization, calibration, and fine tuning.
- The AI profiler provides layer by layer analysis to help with bottlenecks
- The AI library offers open source high-level C++ and Python APIs for maximum portability from edge to cloud.
- Efficient and scalable IP cores can be customized to meet your needs of many different applications from a throughput, latency, power and lower-precision perspective.
Explore All the Possibilities with Vitis AI
AI Model Zoo
Open to all users rich and off-the-shelf deep learning models from the most popular frameworks, Pytorch, Tensorflow, Tensorflow 2 and Caffe. AI model zoo provides optimized and retrainable AI models, with which you will be able achieve faster deployment, performance acceleration and productization on all Xilinx platforms.
AI Optimizer
With world-leading model compression technology, we can reduce model complexity by 5x to 50x with minimal accuracy impact. Deep Compression takes the performance of your AI inference to the next level.
AI Quantizer
By converting the 32-bit floating-point weights and activations to fixed-point like INT8, the AI Quantizer can reduce the computing complexity without losing prediction accuracy. The fixed-point network model requires less memory bandwidth, thus providing faster speed and higher power efficiency than the floating-point model.
AI Compiler
Maps the AI model to a high-efficient instruction set and data flow. Also performs sophisticated optimizations such as layer fusion, instruction scheduling, and reuses on-chip memory as much as possible.
AI Profiler
The performance profiler allows programmers to perform an in-depth analysis of the efficiency and utilization of your AI inference implementation.
AI Library
The Vitis AI Library is a set of high-level libraries and APIs built for efficient AI inference with Deep-Learning Processor Unit (DPU). It is built based on the Vitis AI Runtime with unified APIs and provides easy-to-use interfaces for the AI model deployment on Xilinx platforms.
Vitis AI Documentation
Empowering Autonomous Driving and ADAS Technologies
Real-Time Multi-Class 3D Object Detection
With Vitis AI, it is now possible to achieve real-time processing with the 3D perception AI algorithm on embedded platforms. The co-optimization from hardware and software speed up delivers leading performance of the state-of-art PointPillars model on Xilinx ZU+ MPSoC.
Ultra-Low Latency Application for Autonomous Driving
Latency determines the decision-making for autonomous driving cars when running at high speeds and encountering obstacles. With an innovated domain-specific accelerator and software optimization, Vitis AI empowers autonomous driving vehicles to process deep learning algorithms with ultra-low latency and higher performance.
Object Detection & Segmentation
With strong scalability and adaptability to fit across many low-end to high-end ADAS products, Vitis AI delivers industry-leading performance supporting popular AI algorithms for object detection, lane detection and segmentation in the front ADAS, and In-cabin or surround-view systems.
Making Cities Smarter and Safer
Video Analytics
Cities are increasingly employing intelligence-based systems at the edge point and cloud end. The massive data generated every day requires a powerful end-to-end AI analytics system in order to quickly detect and process objects, traffic, and face behavior. This adds valuable insight to each frame from edge to cloud.
Learn more about Xilinx in Machine & Computer Vision >
Transforming the Power of AI to Improve Health
AI in Imaging, Diagnostics and Clinical Equipment
Vitis AI offers powerful tools and IPs to uncover and identify hidden patterns from medical image data to help fight against disease and improve health.
Learn more about Xilinx in Healthcare AI >
AI On-Premise and in the Data Center
Datacenter Acceleration
Videos
Webinars
Adaptable AI Inference with Vitis AI
In this webinar, go in depth with the key components of Vitis AI and learn how to achieve adaptable and efficient AI inference on Xilinx hardware platforms.
Vitis AI Deep Dive
In this Webinar, learn to use Vitis AI to deploy and run your pre-trained DNN models to Xilinx’s embedded SoC and Alveo acceleration platforms. Then get started with using Vitis AI to run examples on the board.
Accelerating AI Camera Development with Xilinx Vitis
Learn how to leverage Xilinx MPSoCs with Vitis in order to implement AI Camera designs.
Whole App Acceleration
In this webinar, we will show how Vitis and Vitis AI enable developers to accelerate the whole application on Xilinx platforms.
DPU-PYNQ for Python-Powered Edge AI Appliances
Chris Anderson chats with Quenton Hall of Xilinx about how developers can leverage ZYNQ FPGAs in Edge AI appliances.