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Name: XA6SLX25-2CSG324Q
Brand: AMD Xilinx
SKU: XA6SLX25-2CSG324Q
Price: 2.40 USD
Availability: InStock
Rating: 5 (2 reviews)

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AMD Xilinx XA6SLX25-2CSG324Q

Part No.:: XA6SLX25-2CSG324Q

Manufacturer:: AMD Xilinx

Package:: 324-LFBGA, CSPBGA

Datasheet:: XA6SLX25-2CSG324Q.pdf

Description:: IC FPGA 226 I/O 324CSBGA

In Stock:: 3014

Quantity:: Add To Cart

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XA6SLX25-2CSG324Q Specifications

Package/Case:
324-LFBGA, CSPBGA
Packaging:
Tray
Series:
Automotive, AEC-Q100, Spartan®-6 LX XA
ProductStatus:
Active
NumberofLABs/CLBs:
1879
NumberofLogicElements/Cells:
24051
TotalRAMBits:
958464
NumberofI/O:
226
NumberofGates:
-
Voltage-Supply:
1.14V ~ 1.26V
MountingType:
Surface Mount
OperatingTemperature:
-40°C ~ 125°C (TJ)

XA6SLX25-2CSG324Q this integrated circuit is available in factory sealed anti static packs. at icwhale.com. Please read product page below detail information. including XA6SLX25-2CSG324Q 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 XA6SLX25-2CSG324Q 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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XA6SLX25-2CSG324Q information

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XA6SLX25-2CSG324Q application case analysis in emerging technology fields

XA6SLX25-2CSG324Q is a field-programmable gate array (FPGA) chip renowned for its flexibility and performance, widely utilized in diverse applications across industries. It features a reconfigurable architecture, abundant logic resources, and high-speed interfaces, making it suitable for tasks requiring high computational throughput and adaptability.

Application Scenario:

In the field of image processing, XA6SLX25-2CSG324Q can significantly enhance efficiency and intelligence. Let's explore its application in real-time object detection and recognition.

Algorithm Implementation:

To implement real-time object detection using XA6SLX25-2CSG324Q, a convolutional neural network (CNN) model such as YOLO (You Only Look Once) can be deployed. The FPGA's parallel processing capabilities and high-speed interfaces facilitate rapid inference, enabling efficient detection of objects in video streams.

Data Streaming:

Utilizing the FPGA's high-speed transceivers, raw video data can be streamed directly into the chip for processing. The reconfigurable nature of XA6SLX25-2CSG324Q allows for flexible data handling and manipulation, enabling seamless integration with various camera interfaces and resolutions.

Real-Time Processing:

By parallelizing computations across the FPGA's logic cells and utilizing dedicated hardware blocks for tasks like convolution and pooling, real-time processing of video frames can be achieved with low latency. This enables swift detection and recognition of objects in dynamic environments.

Integration with Edge Devices:

After object detection, the FPGA can communicate the results to edge devices or central processing units for further analysis or action. This integration enhances the intelligence of edge computing systems by offloading computationally intensive tasks and enabling timely decision-making.

Customization and Optimization:

One of the key advantages of using XA6SLX25-2CSG324Q is the ability to customize and optimize algorithms for specific applications. Designers can fine-tune the FPGA configuration and algorithm parameters to maximize performance and efficiency, tailored to the requirements of the target application.

Considerations:

When deploying XA6SLX25-2CSG324Q for real-time object detection, it's essential to consider:

- Resource Utilization: Efficiently utilize the FPGA's resources to accommodate complex neural network models and maximize computational throughput.

- Power Consumption: Optimize the design to minimize power consumption, especially in edge computing scenarios where energy efficiency is crucial.

- Algorithm Accuracy: Validate the accuracy of the object detection algorithm under various lighting conditions, object orientations, and environmental factors.

- Latency Requirements: Ensure that the system meets latency requirements for real-time applications, balancing processing speed with detection accuracy.

- Scalability: Design the system with scalability in mind, allowing for future upgrades or integration with additional sensors and processing units to handle more complex tasks.

XA6SLX25-2CSG324Q FAQ

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3. Are the XA6SLX25-2CSG324Q price and inventory displayed accurate?

The price and inventory of XA6SLX25-2CSG324Q fluctuates frequently and cannot be updated in time, it will be updated periodically within 24 hours. And, our quotation usually expires after 5 days.

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6. What is the process for return or replacement of XA6SLX25-2CSG324Q?

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 XA6SLX25-2CSG324Q we delivered, we will accept the replacement or return of the XA6SLX25-2CSG324Q 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 XA6SLX25-2CSG324Q.

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

Two processes to return the products:

(1)Inform us within 90 days

(2)Obtain Requesting Return Authorizations