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Name: XCVU125-2FLVA2104E
Brand: AMD Xilinx
SKU: XCVU125-2FLVA2104E
Price: 2.40 USD
Availability: InStock
Rating: 5 (2 reviews)

Any Feature, including a modified Existing Feature, that is not an Existing Feature.

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AMD Xilinx XCVU125-2FLVA2104E

Part No.:: XCVU125-2FLVA2104E

Manufacturer:: AMD Xilinx

Package:: 2104-BBGA, FCBGA

Datasheet:: XCVU125-2FLVA2104E.pdf

Description:: IC FPGA 832 I/O 2104FCBGA

In Stock:: 2708

Quantity:: Add To Cart

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XCVU125-2FLVA2104E Specifications

Package/Case:
2104-BBGA, FCBGA
Packaging:
Bulk
Series:
Virtex® UltraScale™
ProductStatus:
Active
NumberofLABs/CLBs:
89520
NumberofLogicElements/Cells:
1566600
TotalRAMBits:
90726400
NumberofI/O:
832
NumberofGates:
-
Voltage-Supply:
0.922V ~ 0.979V
MountingType:
Surface Mount
OperatingTemperature:
0°C ~ 100°C (TJ)

XCVU125-2FLVA2104E this integrated circuit is available in factory sealed anti static packs. at icwhale.com. Please read product page below detail information. including XCVU125-2FLVA2104E price, data-sheet, in-stock availability, technical difficulties. Also. Quickly Enter the access of compare listing to find out replaceable electronic parts. If you want to retrieve comprehensive data for XCVU125-2FLVA2104E to optimize the supply chain (including cross references, life-cycle, parametric, counterfeit risk, obsolescence managements forecasts), please contact to our Tech-supports team.

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XCVU125-2FLVA2104E information

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XCVU125-2FLVA2104E application case analysis in emerging technology fields

XCVU125-2FLVA2104E is a high-performance FPGA chip developed by Xilinx, known for its versatility and advanced features. It offers an array of resources and capabilities that enable the implementation of complex digital systems with superior efficiency and intelligence.

Application Scenario:

In the field of autonomous vehicles, XCVU125-2FLVA2104E plays a crucial role in enhancing both the efficiency and intelligence of onboard systems. Here's how:

1. Sensor Fusion:

Utilizing the abundant logic resources and high-speed interfaces of XCVU125-2FLVA2104E, multiple sensor data streams from cameras, LiDAR, radar, and ultrasonic sensors can be efficiently fused in real-time. This enables the vehicle's perception system to generate a comprehensive and accurate understanding of its surroundings, essential for safe navigation.

2. Deep Learning Acceleration:

With its advanced DSP slices and high-speed memory interfaces, XCVU125-2FLVA2104E accelerates deep learning algorithms for object detection, classification, and path planning. This allows autonomous vehicles to make intelligent decisions quickly and adapt to dynamic environments with precision.

3. Real-Time Control:

By leveraging the fast and deterministic processing capabilities of XCVU125-2FLVA2104E, critical control tasks such as steering, braking, and acceleration can be executed with ultra-low latency. This enhances the responsiveness of the vehicle's control system, ensuring rapid and accurate reactions to changing road conditions.

4. High-Definition Visualization:

Using the FPGA's high-speed interfaces and parallel processing capabilities, XCVU125-2FLVA2104E enables the rendering of high-definition visualizations for driver displays and augmented reality overlays. This enhances the user experience by providing clear and detailed information about the vehicle's surroundings and operational status.

5. Adaptive System Optimization:

Through dynamic reconfiguration and partial reprogramming features, XCVU125-2FLVA2104E allows for on-the-fly optimization of FPGA resources based on changing application requirements. This adaptive capability maximizes system efficiency and ensures optimal utilization of hardware resources throughout the vehicle's lifecycle.

Considerations:

- Power Efficiency: Despite its high performance, power efficiency remains a critical consideration for autonomous vehicles. Efforts should be made to optimize the FPGA's power consumption while maintaining peak performance levels.

- Functional Safety: As autonomous vehicles operate in safety-critical environments, stringent measures must be taken to ensure the functional safety of FPGA-based systems. This includes robust fault tolerance mechanisms and thorough validation of system designs.

- Security: Given the increasing cybersecurity threats facing connected vehicles, implementing robust security measures within FPGA-based systems is paramount. Secure boot mechanisms, encryption techniques, and intrusion detection systems should be employed to safeguard sensitive data and prevent unauthorized access.

- Environmental Considerations: Autonomous vehicles are subjected to a wide range of environmental conditions, including temperature extremes and mechanical vibrations. The reliability of XCVU125-2FLVA2104E in such harsh environments should be validated through rigorous testing and qualification procedures.

- Scalability: As the complexity of autonomous vehicle systems continues to evolve, XCVU125-2FLVA2104E should offer scalability options to accommodate future upgrades and expansions. This ensures long-term compatibility and investment protection for vehicle manufacturers and developers.

XCVU125-2FLVA2104E FAQ

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3. Are the XCVU125-2FLVA2104E price and inventory displayed accurate?

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6. What is the process for return or replacement of XCVU125-2FLVA2104E?

All goods will implement Pre-Shipment Inspection (PSI), selected at random from all batches of your order to do a systematic inspection before arranging the shipment. If there is something wrong with the XCVU125-2FLVA2104E we delivered, we will accept the replacement or return of the XCVU125-2FLVA2104E only when all of the below conditions are fulfilled:

(1)Such as a deficiency in quantity, delivery of wrong items, and apparent external defects (breakage and rust, etc.), and we acknowledge such problems.

(2)We are informed of the defect described above within 90 days after the delivery of XCVU125-2FLVA2104E.

(3)The PartNo is unused and only in the original unpacked packaging.

Two processes to return the products:

(1)Inform us within 90 days

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