Parameters |
Factory Lead Time |
1 Week |
Package / Case |
784-BFBGA, FCBGA |
Operating Temperature |
0°C~100°C TJ |
Packaging |
Tray |
Published |
2013 |
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 |
252 |
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, 103K+ 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).
There are Quad ARM? Cortex?-A53 MPCore? with CoreSight?, Dual ARM?Cortex?-R5 with CoreSight?, ARM Mali?-400 MP2 core processors in this SoC.There is a 784-BFBGA, FCBGA package assigned to this system on a chip by the manufacturer.With 256KB RAM implemented, this SoC chip provides users with a high level of performance.As far as its internal architecture is concerned, this SoC design employs the MCU, FPGA technique.The system on a chip is part of the series Zynq? UltraScale+? MPSoC EG.Temperatures should be 0°C~100°C TJ on average for this SoC meaning.A significant feature of this SoC security is the combination of Zynq?UltraScale+? FPGA, 103K+ Logic Cells.A state-of-the-art Tray package houses this SoC system on a chip.252 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.
XCZU2EG-2SFVC784E System On Chip (SoC) applications.
- Microcontroller
- DC-input BLDC motor drive
- Flow Sensors
- Vending machines
- Video Imaging
- Embedded systems
- Efficient hardware for training of neural networks
- Optical drive
- Industrial automation devices
- ARM Cortex M4 microcontroller