XCZU7EV-L2FFVF1517E
XCZU7EV-L2FFVF1517E
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rohs
AMD Xilinx

XCZU7EV-L2FFVF1517E


XCZU7EV-L2FFVF1517E
F20-XCZU7EV-L2FFVF1517E
Active
CMOS, BGA, BGA1517,39X39,40
BGA, BGA1517,39X39,40

XCZU7EV-L2FFVF1517E ECAD Model


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XCZU7EV-L2FFVF1517E Attributes


Type Description Select
Rohs Code Yes
Part Life Cycle Code Active
Surface Mount YES
Supply Voltage-Nom 720 mV
uPs/uCs/Peripheral ICs Type MICROPROCESSOR CIRCUIT
Technology CMOS
Additional Feature ALSO AVAILABLE WITH 0.85V NOMINAL SUPPLY
Supply Voltage-Max 742 mV
Supply Voltage-Min 698 mV
Temperature Grade OTHER
JESD-30 Code R-PBGA-B1517
JESD-609 Code e1
Moisture Sensitivity Level 4
Operating Temperature-Max 110 °C
Peak Reflow Temperature (Cel) 245
Time@Peak Reflow Temperature-Max (s) 30
Number of Terminals 1517
Package Body Material PLASTIC/EPOXY
Package Code BGA
Package Shape RECTANGULAR
Package Style GRID ARRAY
Terminal Finish Tin/Silver/Copper (Sn/Ag/Cu)
Terminal Form BALL
Terminal Position BOTTOM
Ihs Manufacturer XILINX INC
Package Description BGA, BGA1517,39X39,40
Reach Compliance Code compliant
ECCN Code 5A002.A.4
HTS Code 8542.39.00.01

XCZU7EV-L2FFVF1517E Datasheet Download


XCZU7EV-L2FFVF1517E Overview



The chip model XCZU7EV-L2FFVF1517E is a cutting-edge technology developed by Xilinx, a leading semiconductor company. This chip model is designed for high-performance computing applications, such as artificial intelligence, machine learning, and computer vision. It is based on the Xilinx Ultrascale+ architecture, which allows for high-speed data processing and improved system performance.


The XCZU7EV-L2FFVF1517E chip model is equipped with a wide range of features, including a high-bandwidth memory interface, a high-speed transceiver, and a low-power, low-latency network-on-chip. It also includes a wide range of programmable logic resources, such as DSPs, block RAMs, and multipliers. These features make the XCZU7EV-L2FFVF1517E chip model an ideal choice for applications that require high-performance computing.


In terms of industry trends, the XCZU7EV-L2FFVF1517E chip model is expected to be widely adopted in the future. It is well-suited for the development of edge computing systems, as well as for the development of intelligent robots. The chip model is also expected to be popular in the automotive, aerospace, and medical industries. Additionally, the chip model is expected to be used in a variety of applications, such as facial recognition, natural language processing, and autonomous vehicles.


In terms of the future development of related industries, the XCZU7EV-L2FFVF1517E chip model is likely to become even more popular. As technology advances, more applications are likely to be developed that require high-performance computing. Additionally, the chip model is expected to be used in the development of more advanced robots, as well as in the development of autonomous vehicles.


In terms of whether the application environment requires the support of new technologies, this depends on the specific technologies that are needed. For example, if the application requires facial recognition technology, then the chip model would need to be equipped with the necessary features. Similarly, if the application requires natural language processing, then the chip model would need to be equipped with the necessary features.


In terms of whether the XCZU7EV-L2FFVF1517E chip model can be applied to the development and popularization of future intelligent robots, the answer is yes. This chip model is well-suited for the development of robots, as it is equipped with a wide range of features, such as a high-bandwidth memory interface, a high-speed transceiver, and a low-power, low-latency network-on-chip. Additionally, the chip model is expected to be used in the development of more advanced robots, as technology advances.


In terms of what technical talents are needed to use the XCZU7EV-L2FFVF1517E chip model effectively, the answer depends on the specific application. Generally speaking, engineers with experience in programming, embedded systems, and digital signal processing are likely to be needed. Additionally, experts in artificial intelligence, machine learning, and computer vision are likely to be needed to use the chip model effectively.



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Unit Price: $3,988.4458
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Pricing (USD)

QTY Unit Price Ext Price
1+ $3,709.2546 $3,709.2546
10+ $3,669.3701 $36,693.7014
100+ $3,469.9478 $346,994.7846
1000+ $3,270.5256 $1,635,262.7780
10000+ $2,991.3344 $2,991,334.3500
The price is for reference only, please refer to the actual quotation!

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