Manufacturer Part Number
XCVU7P-L2FLVA2104E
Manufacturer
Xilinx
Introduction
The Xilinx XCVU7P-L2FLVA2104E is a high-performance, low-power Virtex® UltraScale+™ FPGA (Field Programmable Gate Array) designed for a wide range of embedded applications. It offers exceptional logic capacity, advanced signal processing capabilities, and advanced security features, making it a versatile choice for demanding applications.
Product Features and Performance
98,520 Configurable Logic Blocks (CLBs)
1,724,100 Logic Elements/Cells
260,812,800 Total RAM Bits
832 I/O Pins
Voltage Supply Range: 0.698V ~ 0.742V
Operating Temperature Range: 0°C ~ 110°C (TJ)
2104-BBGA, FCBGA Package
2104-FCBGA (47.5x47.5) Supplier Device Package
Product Advantages
High logic capacity and advanced signal processing capabilities for complex applications
Low power consumption for energy-efficient designs
Flexible and configurable architecture for customized solutions
Robust security features to protect intellectual property and data
Key Reasons to Choose This Product
Exceptional performance and scalability for demanding embedded applications
Power-efficient design for energy-conscious projects
Versatile and adaptable platform for a wide range of use cases
Trusted Xilinx brand and comprehensive ecosystem support
Quality and Safety Features
Rigorous quality control and testing processes
Compliance with industry standards and safety regulations
Compatibility
The Xilinx XCVU7P-L2FLVA2104E is compatible with the Virtex® UltraScale+™ FPGA family and can be used in a variety of embedded applications.
Application Areas
High-performance computing
Artificial intelligence and machine learning
Aerospace and defense
Industrial automation
Medical imaging
Telecommunications
Product Lifecycle
The Xilinx XCVU7P-L2FLVA2104E is an active product. Xilinx continues to offer this model, as well as other Virtex® UltraScale+™ FPGA variants, to address the evolving needs of the market. Customers are advised to contact our website's sales team for more information on available options and potential alternative models.