Parameters |
Factory Lead Time |
1 Week |
Package / Case |
1156-BBGA, FCBGA |
Operating Temperature |
-40°C~100°C TJ |
Packaging |
Tray |
Published |
2013 |
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 |
328 |
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, 599K+ 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 Quad ARM? Cortex?-A53 MPCore? with CoreSight?, Dual ARM?Cortex?-R5 with CoreSight?, ARM Mali?-400 MP2 core processor(s) is built into this SoC.There is a 1156-BBGA, FCBGA package assigned to this system on a chip by the manufacturer.With 256KB RAM implemented, this SoC chip provides reliable operation.Using the MCU, FPGA technique, this SoC design's internal architecture is simple.Featured system on chip SoCs of the Zynq? UltraScale+? MPSoC EG series.It is recommended that this SoC meaning be operated at -40°C~100°C TJ on an average.A significant feature of this SoC security is the combination of Zynq?UltraScale+? FPGA, 599K+ Logic Cells.Featured in the state-of-the-art Tray package, this SoC system on a chip provides outstanding performance.328 I/Os 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.
XCZU9EG-1FFVB1156I System On Chip (SoC) applications.
- Functional safety for critical applications in the automotive
- Efficient hardware for training of neural networks
- High-end PLC
- Video Imaging
- Robotics
- Networked sensors
- Smartphones
- External USB hard disk/SSD
- Apple smart watch
- Measurement testers