XCZU5EG-1SFVC784E
| Parameters | |
|---|---|
| Factory Lead Time | 11 Weeks |
| Package / Case | 784-BFBGA, FCBGA |
| Operating Temperature | 0°C~100°C TJ |
| Packaging | Tray |
| Published | 2016 |
| Series | Zynq® UltraScale+™ MPSoC EG |
| Part Status | Active |
| Moisture Sensitivity Level (MSL) | 4 (72 Hours) |
| HTS Code | 8542.31.00.01 |
| Peak Reflow Temperature (Cel) | NOT SPECIFIED |
| Time@Peak Reflow Temperature-Max (s) | NOT SPECIFIED |
| Number of I/O | 252 |
| Speed | 500MHz, 600MHz, 1.2GHz |
| RAM Size | 256KB |
| Core Processor | Quad ARM® Cortex®-A53 MPCore™ with CoreSight™, Dual ARM®Cortex™-R5 with CoreSight™, ARM Mali™-400 MP2 |
| Peripherals | DMA, WDT |
| Connectivity | CANbus, EBI/EMI, Ethernet, I2C, MMC/SD/SDIO, SPI, UART/USART, USB OTG |
| Architecture | MCU, FPGA |
| Primary Attributes | Zynq®UltraScale+™ FPGA, 256K+ Logic Cells |
| RoHS Status | ROHS3 Compliant |
This SoC is built on Quad ARM? Cortex?-A53 MPCore? with CoreSight?, Dual ARM?Cortex?-R5 with CoreSight?, ARM Mali?-400 MP2 core processor(s).
Quad ARM? Cortex?-A53 MPCore? with CoreSight?, Dual ARM?Cortex?-R5 with CoreSight?, ARM Mali?-400 MP2 core processor(s) are used in the construction of this SoC.Package 784-BFBGA, FCBGA is assigned to this system on a chip by the manufacturer.The SoC chip provides users with reliable performance because it is implemented with 256KB RAM.A MCU, FPGA technique is used for the SoC design's internal architecture.Zynq? UltraScale+? MPSoC EG is the series name of this system on chip SoC.Typical operating temperatures for this SoC meaning should be 0°C~100°C TJ.This SoC security combines Zynq?UltraScale+? FPGA, 256K+ Logic Cells and that is something to note.There is a state-of-the-art Tray package that houses this SoC system on a chip.This SoC part has a total of 252 I/Os.
Quad ARM? Cortex?-A53 MPCore? with CoreSight?, Dual ARM?Cortex?-R5 with CoreSight?, ARM Mali?-400 MP2 processor.
256KB RAM.
Built on MCU, FPGA.
There are a lot of Xilinx Inc.
XCZU5EG-1SFVC784E System On Chip (SoC) applications.
- Industrial sectors
- Efficient hardware for training of neural networks
- Temperature
- Wireless networking
- Automotive gateway
- Industrial Pressure
- High-end PLC
- Digital Media
- ARM
- Special Issue Editors