XQV2000E-6FG1156N
XQV2000E-6FG1156N
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rohs

AMD Xilinx

XQV2000E-6FG1156N


XQV2000E-6FG1156N
F20-XQV2000E-6FG1156N
Active
FIELD PROGRAMMABLE GATE ARRAY, CMOS, PLASTIC, FPBGA-1156
PLASTIC, FPBGA-1156

XQV2000E-6FG1156N ECAD Model


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XQV2000E-6FG1156N Attributes


Type Description Select
Rohs Code No
Part Life Cycle Code Not Recommended
Supply Voltage-Nom 1.8 V
Number of Inputs 804
Number of Outputs 804
Number of Logic Cells 43200
Number of Equivalent Gates 2541952
Number of CLBs 9600
Programmable Logic Type FIELD PROGRAMMABLE GATE ARRAY
Screening Level 38535Q/M;38534H;883B
Temperature Grade MILITARY
Package Shape SQUARE
Technology CMOS
Organization 9600 CLBS, 2541952 GATES
Clock Frequency-Max 357.2 MHz
Power Supplies 1.2/3.6,1.8 V
Supply Voltage-Max 1.89 V
Supply Voltage-Min 1.71 V
JESD-30 Code S-PBGA-B1156
Qualification Status Not Qualified
JESD-609 Code e0
Moisture Sensitivity Level 3
Operating Temperature-Max 125 °C
Operating Temperature-Min -55 °C
Peak Reflow Temperature (Cel) 225
Time@Peak Reflow Temperature-Max (s) 30
Number of Terminals 1156
Package Body Material PLASTIC/EPOXY
Package Code BGA
Package Equivalence Code BGA1156,34X34,40
Package Shape SQUARE
Package Style GRID ARRAY
Surface Mount YES
Terminal Finish TIN LEAD
Terminal Form BALL
Terminal Pitch 1 mm
Terminal Position BOTTOM
Width 35 mm
Length 35 mm
Seated Height-Max 2.6 mm
Ihs Manufacturer XILINX INC
Part Package Code BGA
Package Description PLASTIC, FPBGA-1156
Pin Count 1156
Reach Compliance Code not_compliant
ECCN Code 3A001.A.2.C
HTS Code 8542.39.00.01

XQV2000E-6FG1156N Datasheet Download


XQV2000E-6FG1156N Overview



The chip model XQV2000E-6FG1156N is a revolutionary new technology that has the potential to revolutionize the way we think about networks and intelligent systems. This chip model is the latest in a series of advanced chips that have been developed to provide improved performance for tasks such as artificial intelligence, machine learning, and natural language processing. It is designed to provide an efficient and cost-effective solution for a wide range of applications.


The XQV2000E-6FG1156N chip model is a versatile and powerful tool for building intelligent systems. It is capable of handling a wide range of tasks, from basic data processing to more complex tasks such as image recognition and natural language processing. The chip model also offers a high degree of flexibility, allowing for the development of custom algorithms and applications.


The XQV2000E-6FG1156N chip model is suitable for use in a variety of network and intelligent scenarios. It can be used to create intelligent robots and autonomous vehicles, as well as to build systems that can interact with humans in natural language. It can also be used to develop and improve the accuracy of machine learning algorithms.


In addition to its potential applications in networks and intelligent systems, the XQV2000E-6FG1156N chip model can also be used to develop and popularize future intelligent robots. This chip model is capable of handling complex tasks such as image recognition, natural language processing, and machine learning. To effectively use the chip model, it is important to understand the specific design requirements and product description of the chip model. This includes understanding the chip's architecture, memory and processor capacity, as well as its power consumption and heat dissipation. Additionally, it is important to have a good understanding of the programming language used to program the chip model.


Case studies and precautions should also be taken into account when using the XQV2000E-6FG1156N chip model. It is important to consider the potential risks and limitations of the chip model, such as the possibility of data loss or system failure. Additionally, it is important to consider the potential security risks associated with the chip model, such as the possibility of malicious software or hardware.


In summary, the XQV2000E-6FG1156N chip model has the potential to revolutionize the way we think about networks and intelligent systems. It can be used to create intelligent robots and autonomous vehicles, as well as to develop and improve the accuracy of machine learning algorithms. To use the chip model effectively, it is important to understand the specific design requirements and product description of the chip model, as well as to consider the potential risks and limitations associated with its use. Additionally, it is important to have a good understanding of the programming language used to program the chip model, as well as the potential security risks associated with it.



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