XC2V1000-5FFG896C Overview

A 896-BBGA, FCBGA package is provided with this component. There are FIELD PROGRAMMABLE GATE ARRAY transistors in this type of FPGA. Having 432 I/Os makes data transfers more coherent. In order to operate fpga chips, a voltage supply of 1.5V volts is required. The Surface Mount-slot connector on the FPGA module can be connected to the development board. Powered by a 1.425V~1.575V supply voltage, fpga chips is able to operate at high speeds. FPGAs belonging to the Virtex?-II series are a type of FPGA that belong to the Virtex?-II series of FPGAs. Fpga chips is necessary to keep the operating temperature wFpga chipshin 0°C~85°C TJ when the device is operating. Fpga chips is designed to maximiTraye space efficiency by containing the FPGA model in Tray. In total, it has 896 terminations on each end. Having a RAM bit size of 737280 means that this device will offer you a lot of memory. In order to find related parts, you can use its base part number XC2V1000. The RAM si90kBe of this FPGA module reaches 90kB to ensure normal operation of the program. The device is designed with 896 pins in total. 1280 LABs and CLBs are built into this FPGA. I think, as long as this FPGA is mounted in Surface Mount, it could perform excellently according to its specifications as long as you mount it in Surface Mount. With a 1.5V supply voltage, designers can fully utilize the flexibility of the device. 1000000 gates make up the basic block of its construction. As far as the pin count is concerned, it has 896 pins. Fpga semiconductor is important to note that the data is stored and transferred in 10240 different registers.

XC2V1000-5FFG896C Features

432 I/Os
Up to 737280 RAM bits
896 LABs/CLBs
10240 registers

XC2V1000-5FFG896C Applications

There are a lot of Xilinx Inc. XC2V1000-5FFG896C FPGAs applications.

• Automotive driver's assistance
• Software-defined radios
• Automotive Applications
• Camera time adjustments
• Military Temperature
• Device controllers
• Bioinformatics
• ADAS
• Solar Energy
• High Performance Computing