5CGXBC4C6U19C7N Allicdata Electronics
Allicdata Part #:

5CGXBC4C6U19C7N-ND

Manufacturer Part#:

5CGXBC4C6U19C7N

Price: $ 85.30
Product Category:

Integrated Circuits (ICs)

Manufacturer: Intel FPGAs/Altera
Short Description: IC FPGA 224 I/O 484UBGA
More Detail: N/A
DataSheet: 5CGXBC4C6U19C7N datasheet5CGXBC4C6U19C7N Datasheet/PDF
Quantity: 1000
84 +: $ 77.54110
Stock 1000Can Ship Immediately
$ 85.3
Specifications
Series: Cyclone® V GX
Part Status: Active
Number of LABs/CLBs: 18868
Number of Logic Elements/Cells: 50000
Total RAM Bits: 2862080
Number of I/O: 224
Voltage - Supply: 1.07 V ~ 1.13 V
Mounting Type: Surface Mount
Operating Temperature: 0°C ~ 85°C (TJ)
Package / Case: 484-FBGA
Supplier Device Package: 484-UBGA (19x19)
Base Part Number: 5CGXBC4
Description

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Introduction to FPGAs

Field Programmable Gate Arrays (FPGAs) are programmable integrated circuits that are used in a number of applications, from embedded systems to image processing. FPGAs are made up of configurable logic blocks and interconnects, and can be programmed to implement a wide range of functions in a highly-efficient manner. FPGAs are used in a range of applications, from automotive, aerospace and defense to industrial, communication and consumer markets.

5CGXBC4C6U19C7N Application Field and Working Principle

The 5CGXBC4C6U19C7N FPGA from Xilinx is a mid-range entry-level programmable logic device with 56,432 flip-flops and 32-bit wide I/O operations. It is suitable for a range of applications, including embedded systems, signal processing, communications and medical imaging. The 5CGXBC4C6U19C7N FPGA is based on the Virtex-5QV architecture and provides a high-performance, low-power solution for operations such as image processing and streaming data manipulation.

The 5CGXBC4C6U19C7N FPGA consists of configurable logic blocks and interconnect resources, which can be programmed to implement a variety of functions in a highly efficient manner. The configurable logic blocks are composed of logic cells, look-up tables, tree-adders and other resources, which can be programmed to perform complex operations. The flip-flops form the backbone of any FPGA and allow data to be stored in the device. Additional features such as memory blocks, block RAMs, differential PLLs and partial reconfiguration capability help to increase the 5CGXBC4C6U19C7N\'s flexibility and performance. The configurable logic blocks are connected through a system of interconnects and can be programmed to perform a variety of logic functions, such as arithmetic operations, comparisons, and state machines.

The 5CGXBC4C6U19C7N FPGA also supports high-level synthesis operations and is able to configure its own programming tools, memory blocks, clocking and I/O. This feature enables users to create custom applications in a reconfigurable environment.

The 5CGXBC4C6U19C7N FPGA is suited for applications such as automotive and industrial control, wireless telecommunications, audio and video processing, medical imaging, and computer vision and machine learning. The device also provides flexibility in terms of frequency and power, allowing users to reduce design time and cost. Additionally, the 5CGXBC4C6U19C7N is capable of operating at very low power, providing improved performance while reducing power consumption.

Conclusion

The 5CGXBC4C6U19C7N FPGA from Xilinx is a mid-range entry-level programmable logic device suitable for a range of applications, including embedded systems, signal processing, communications and medical imaging. The device is made up of configurable logic blocks and interconnects, which can be programmed to perform a variety of logic functions in an efficient manner. The 5CGXBC4C6U19C7N also supports high-level synthesis operations and is able to configure its own programming tools, memory blocks, clocking and I/O. This feature enables users to create custom applications in a reconfigurable environment. The 5CGXBC4C6U19C7N is suited for automotive and industrial control, wireless telecommunications, audio and video processing, medical imaging, and computer vision and machine learning.

The specific data is subject to PDF, and the above content is for reference

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