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Name: XCVU080-2FFVC1517E
Brand: AMD Xilinx
SKU: XCVU080-2FFVC1517E
Price: 2.40 USD
Availability: InStock
Rating: 5 (2 reviews)

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AMD Xilinx XCVU080-2FFVC1517E

Part No.:: XCVU080-2FFVC1517E

Manufacturer:: AMD Xilinx

Package:: 1517-BBGA, FCBGA

Datasheet:: XCVU080-2FFVC1517E.pdf

Description:: IC FPGA 520 I/O 1517FCBGA

In Stock:: 2180

Quantity:: Add To Cart

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XCVU080-2FFVC1517E Specifications

Package/Case:
1517-BBGA, FCBGA
Packaging:
Tray
Series:
Virtex® UltraScale™
ProductStatus:
Active
NumberofLABs/CLBs:
55714
NumberofLogicElements/Cells:
975000
TotalRAMBits:
51200000
NumberofI/O:
520
NumberofGates:
-
Voltage-Supply:
0.922V ~ 0.979V
MountingType:
Surface Mount
OperatingTemperature:
0°C ~ 100°C (TJ)

XCVU080-2FFVC1517E this integrated circuit is available in factory sealed anti static packs. at icwhale.com. Please read product page below detail information. including XCVU080-2FFVC1517E 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 XCVU080-2FFVC1517E 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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XCVU080-2FFVC1517E information

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XCVU080-2FFVC1517E application case analysis in emerging technology fields

XCVU080-2FFVC1517E is a high-performance FPGA device designed by Xilinx, featuring advanced capabilities for accelerating complex algorithms and processing massive data sets efficiently.

Application Scenario:

In the field of artificial intelligence (AI) and machine learning (ML), XCVU080-2FFVC1517E can be instrumental in accelerating computations for deep learning models, enabling faster inference times and training processes.

Algorithm Acceleration:

Utilizing the parallel processing architecture of XCVU080-2FFVC1517E, developers can implement custom hardware accelerators for specific AI/ML tasks, such as convolutional neural network (CNN) inference or recurrent neural network (RNN) computations. This leads to significant speedups compared to traditional CPU-based implementations.

Data Processing:

With its high-speed interfaces and large on-chip memory resources, XCVU080-2FFVC1517E can efficiently handle massive datasets commonly encountered in AI/ML applications, such as image recognition or natural language processing. This capability streamlines data preprocessing, feature extraction, and post-processing tasks.

Real-Time Decision Making:

By deploying AI/ML models directly onto XCVU080-2FFVC1517E, systems can make real-time decisions autonomously, enabling applications like autonomous vehicles, industrial automation, or predictive maintenance to respond swiftly to changing environments or conditions.

Energy Efficiency:

Optimizing algorithms for hardware acceleration on XCVU080-2FFVC1517E can lead to significant energy savings compared to running the same computations on traditional CPU or GPU architectures. This is particularly beneficial for edge computing or battery-powered devices where energy efficiency is crucial.

Considerations:

When leveraging XCVU080-2FFVC1517E for AI/ML applications, developers should consider:

- Hardware Resource Utilization: Efficiently mapping algorithms onto FPGA resources to maximize performance and minimize resource usage.

- Algorithm Optimization: Designing algorithms specifically for FPGA acceleration, considering factors like parallelism, memory access patterns, and pipeline optimization.

- Development Tools: Utilizing Xilinx development tools and libraries, such as Vivado and Vitis AI, to streamline FPGA design, implementation, and debugging processes.

- System Integration: Integrating XCVU080-2FFVC1517E seamlessly into larger systems, considering factors like interfacing with sensors, actuators, or external processors.

- Verification and Testing: Rigorous testing and verification procedures to ensure the correctness, reliability, and safety of FPGA-accelerated AI/ML applications in real-world environments.

XCVU080-2FFVC1517E FAQ

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3. Are the XCVU080-2FFVC1517E price and inventory displayed accurate?

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6. What is the process for return or replacement of XCVU080-2FFVC1517E?

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 XCVU080-2FFVC1517E we delivered, we will accept the replacement or return of the XCVU080-2FFVC1517E 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 XCVU080-2FFVC1517E.

(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