XCZU4EG-2FBVB900E
| Parameters | |
|---|---|
| Factory Lead Time | 11 Weeks |
| Package / Case | 900-BBGA, FCBGA |
| Operating Temperature | 0°C~100°C TJ |
| Packaging | Tray |
| Published | 2016 |
| Series | Zynq® UltraScale+™ MPSoC EG |
| Pbfree Code | yes |
| 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 | 204 |
| Speed | 533MHz, 600MHz, 1.3GHz |
| 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, 192K+ 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).
A core processor Quad ARM? Cortex?-A53 MPCore? with CoreSight?, Dual ARM?Cortex?-R5 with CoreSight?, ARM Mali?-400 MP2 is used to build this SoC.Its package is 900-BBGA, FCBGA.A SoC chip with 256KB RAM is provided for users to enjoy reliable performance.Internally, this SoC design uses the MCU, FPGA technique.Zynq? UltraScale+? MPSoC EG is the series number of this system on chip SoC.This SoC meaning should have an average operating temperature of 0°C~100°C TJ when it is operating normally.In addition, this SoC security combines Zynq?UltraScale+? FPGA, 192K+ Logic Cells.This SoC system on a chip has been designed in a state-of-the-art Tray package.204 I/Os in total are included in this SoC part.
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.
XCZU4EG-2FBVB900E System On Chip (SoC) applications.
- Functional safety for critical applications in the automotive
- String inverter
- Industrial sectors
- Mobile market
- Industrial
- Efficient hardware for training of neural networks
- Medical Pressure
- Flow Sensors
- Body control module
- Networked sensors