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Name: XCKU115-L1FLVF1924I
Brand: AMD Xilinx
SKU: XCKU115-L1FLVF1924I
Price: 2.40 USD
Availability: InStock
Rating: 5 (2 reviews)

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AMD Xilinx XCKU115-L1FLVF1924I

Part No.:: XCKU115-L1FLVF1924I

Manufacturer:: AMD Xilinx

Package:: 1924-BBGA, FCBGA

Datasheet:: XCKU115-L1FLVF1924I.pdf

Description:: IC FPGA 728 I/O 1924FCBGA

In Stock:: 2898

Quantity:: Add To Cart

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XCKU115-L1FLVF1924I Specifications

Package/Case:
1924-BBGA, FCBGA
Packaging:
Bulk
Series:
Kintex® UltraScale™
ProductStatus:
Active
NumberofLABs/CLBs:
82920
NumberofLogicElements/Cells:
1451100
TotalRAMBits:
77721600
NumberofI/O:
728
NumberofGates:
-
Voltage-Supply:
0.880V ~ 0.979V
MountingType:
Surface Mount
OperatingTemperature:
-40°C ~ 100°C (TJ)

XCKU115-L1FLVF1924I this integrated circuit is available in factory sealed anti static packs. at icwhale.com. Please read product page below detail information. including XCKU115-L1FLVF1924I 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 XCKU115-L1FLVF1924I 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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XCKU115-L1FLVF1924I information

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XCKU115-L1FLVF1924I application case analysis in emerging technology fields

XCKU115-L1FLVF1924I is a high-performance field-programmable gate array (FPGA) device manufactured by Xilinx, offering advanced capabilities for a wide range of applications.

Application Scenario:

In autonomous vehicles, XCKU115-L1FLVF1924I can be utilized to implement real-time sensor fusion algorithms for perception tasks, such as object detection and tracking, enabling safer and more efficient navigation.

System Architecture:

To develop a sensor fusion system using XCKU115-L1FLVF1924I, the following architecture can be employed:

1. Sensor Interface:

Connect various sensors, such as cameras, LiDAR, and radar, to the FPGA using high-speed interfaces like MIPI CSI-2 and LVDS. Utilize appropriate IP cores or custom logic to interface with the sensors and acquire raw sensor data.

2. Data Preprocessing:

Implement preprocessing modules within the FPGA to perform tasks such as noise filtering, data alignment, and calibration on the raw sensor data. This ensures that the data fed into the fusion algorithms is clean and synchronized.

3. Fusion Algorithms:

Develop and deploy sensor fusion algorithms, such as Kalman filters or neural networks, on the XCKU115-L1FLVF1924I FPGA. These algorithms combine information from multiple sensors to generate a comprehensive and accurate understanding of the vehicle's surroundings.

4. Decision Making:

Implement decision-making logic within the FPGA to interpret the fused sensor data and make real-time decisions, such as object avoidance or trajectory planning, to ensure safe navigation of the autonomous vehicle.

5. Interface and Control:

Integrate interfaces for communication with other vehicle systems, such as the vehicle's control unit or navigation system. Utilize protocols like CAN bus or Ethernet to exchange information and commands, enabling seamless integration into the vehicle's architecture.

Performance Optimization:

To enhance the efficiency and intelligence of the system, consider the following optimization techniques:

- Parallel Processing: Utilize the parallel processing capabilities of XCKU115-L1FLVF1924I to concurrently execute multiple tasks, reducing latency and improving overall system throughput.

- Hardware Acceleration: Offload computationally intensive tasks, such as deep learning inference or image processing, to dedicated hardware accelerators implemented within the FPGA, leveraging its reconfigurable architecture for accelerated performance.

- Power Management: Implement dynamic power management techniques to optimize power consumption based on the system's workload, ensuring efficient utilization of resources while minimizing energy consumption.

- Real-Time Performance: Design efficient algorithms and utilize high-speed interfaces to achieve real-time processing capabilities, enabling rapid response to changing environmental conditions and ensuring the safety of the autonomous vehicle.

Considerations:

When designing the sensor fusion system, it's essential to consider:

- Sensor Calibration: Accurate calibration of sensors to ensure consistency and reliability of the fused sensor data.

- Fault Tolerance: Implement redundancy and error detection mechanisms to handle sensor failures or inconsistencies and maintain the integrity of the fusion results.

- Security: Implement secure communication protocols and encryption mechanisms to protect the integrity and confidentiality of sensor data, mitigating potential cyber threats and attacks.

- Validation and Testing: Thoroughly validate the sensor fusion system through simulation, emulation, and real-world testing to verify its performance, accuracy, and robustness across various driving scenarios and environmental conditions.

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6. What is the process for return or replacement of XCKU115-L1FLVF1924I?

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 XCKU115-L1FLVF1924I we delivered, we will accept the replacement or return of the XCKU115-L1FLVF1924I 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 XCKU115-L1FLVF1924I.

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

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(1)Inform us within 90 days

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