5SGXEA3H2F35C2LN
5SGXEA3H2F35C2LN
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Intel Corporation

5SGXEA3H2F35C2LN


5SGXEA3H2F35C2LN
F18-5SGXEA3H2F35C2LN
Active
IC FPGA 432 I/O 1152FBGA
1152-FBGA (35x35)

5SGXEA3H2F35C2LN ECAD Model


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5SGXEA3H2F35C2LN Attributes


Type Description Select
Mfr Intel
Series Stratix® V GX
Package Tray
Number of LABs/CLBs 128300
Number of Logic Elements/Cells 340000
Total RAM Bits 19456000
Number of I/O 432
Voltage - Supply 0.82V ~ 0.88V
Mounting Type Surface Mount
Operating Temperature 0°C ~ 85°C (TJ)
Package / Case 1152-BBGA, FCBGA
Supplier Device Package 1152-FBGA (35x35)
Base Product Number 5SGXEA3

5SGXEA3H2F35C2LN Datasheet Download


5SGXEA3H2F35C2LN Overview



The 5SGXEA3H2F35C2LN chip model is a powerful and versatile device that is suitable for a wide range of applications in high-performance digital signal processing, embedded processing, and image processing. It is designed to be programmed using HDL language, a hardware description language that allows for the efficient development of complex digital systems.


The 5SGXEA3H2F35C2LN chip model offers several advantages over other models. It is highly reliable, with a low power consumption, and is capable of operating at high speeds. It also has a wide range of features, including multiple I/O ports and a large number of memory blocks. Additionally, the chip model is designed to be compatible with a variety of existing and emerging technologies, making it a great choice for future applications.


The demand for the 5SGXEA3H2F35C2LN chip model is expected to grow in the near future, as it is increasingly being used for applications such as robotics, autonomous vehicles, and artificial intelligence. This is due to its ability to process data quickly and accurately, as well as its flexibility and scalability.


The 5SGXEA3H2F35C2LN chip model can be used in the development and popularization of future intelligent robots, as it is capable of processing complex tasks quickly and accurately. To use the model effectively, technical talents with a good understanding of HDL language are needed, as well as knowledge of robotics, artificial intelligence, and embedded systems. Additionally, expertise in programming, debugging, and optimization of the chip model is necessary to ensure its proper functioning.



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