XCVU190-3FLGB2104E

XCVU190-3FLGB2104E

Manufacturer No:

XCVU190-3FLGB2104E

Manufacturer:

AMD

Description:

IC FPGA 702 I/O 2104FCBGA

Datasheet:

Datasheet

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XCVU190-3FLGB2104E Specifications

  • Type
    Parameter
  • Packaging
    Tray
The XCVU190-3FLGB2104E is a specific model of integrated circuit (IC) chip manufactured by Xilinx. It belongs to the Virtex UltraScale+ family of FPGAs (Field-Programmable Gate Arrays). Here are some advantages and application scenarios of this chip:Advantages: 1. High Performance: The XCVU190-3FLGB2104E chip offers high-performance computing capabilities, making it suitable for demanding applications that require significant processing power. 2. Large Capacity: With a capacity of 1.9 million logic cells, this chip provides ample resources for complex designs and applications. 3. Versatility: The chip supports a wide range of I/O standards, making it compatible with various interfaces and protocols. 4. Programmability: Being an FPGA, the XCVU190-3FLGB2104E chip is highly programmable, allowing users to customize its functionality according to their specific requirements. 5. Power Efficiency: The chip incorporates power optimization features, enabling efficient power consumption and reducing overall energy costs.Application Scenarios: 1. High-Performance Computing: The XCVU190-3FLGB2104E chip is suitable for applications that require high-performance computing, such as data centers, scientific research, and simulations. 2. Video Processing: With its large capacity and high-performance capabilities, this chip can be used for video processing tasks, including video encoding, decoding, and transcoding. 3. Network Infrastructure: The chip can be utilized in networking equipment, such as routers and switches, to handle high-speed data processing and packet forwarding. 4. Aerospace and Defense: The XCVU190-3FLGB2104E chip can be employed in aerospace and defense applications, including radar systems, signal processing, and communication systems. 5. Artificial Intelligence and Machine Learning: Due to its computational power, the chip can be utilized in AI and ML applications, such as deep learning inference and neural network acceleration.It's important to note that the specific use cases and application scenarios may vary depending on the requirements and design choices of the end-user.