Audience

Developers requiring an adaptable and real-time AI inference acceleration solution to build accelerated applications

About Xilinx

The Xilinx’s AI development platform for AI inference on Xilinx hardware platforms 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. 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.

Integrations

API:
Yes, Xilinx offers API access

Ratings/Reviews

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Company Information

Xilinx
Founded: 1984
United States
www.xilinx.com/products/design-tools/vitis/vitis-ai.html

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Product Details

Platforms Supported
SaaS
Training
Documentation
Live Online
Webinars
In Person
Support
Phone Support
Online

Xilinx Frequently Asked Questions

Q: What kinds of users and organization types does Xilinx work with?
Q: What languages does Xilinx support in their product?
Q: What kind of support options does Xilinx offer?
Q: What other applications or services does Xilinx integrate with?
Q: Does Xilinx have an API?
Q: What type of training does Xilinx provide?

Xilinx Product Features

Artificial Intelligence

For Healthcare
Multi-Language
Chatbot
For Sales
Rules-Based Automation
Machine Learning
Natural Language Processing
Predictive Analytics
Virtual Personal Assistant (VPA)
Process/Workflow Automation
For eCommerce
Image Recognition

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Templates
Visualization
Statistical / Mathematical Tools