XCZU17EG-1FFVC1760I
| Parameters | |
|---|---|
| Factory Lead Time | 1 Week |
| Package / Case | 1760-BBGA, FCBGA |
| Operating Temperature | -40°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 | 512 |
| 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, 926K+ 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(s) Quad ARM? Cortex?-A53 MPCore? with CoreSight?, Dual ARM?Cortex?-R5 with CoreSight?, ARM Mali?-400 MP2 is integrated into this SoC.Its package is 1760-BBGA, FCBGA.A 256KB RAM SoC chip provides reliable performance to users.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 expected that this SoC meaning will operate at -40°C~100°C TJ on average.There is one thing to note about this SoC security: it combines Zynq?UltraScale+? FPGA, 926K+ Logic Cells.It is packaged in a state-of-the-art Tray package.As a whole, this SoC part includes 512 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.
XCZU17EG-1FFVC1760I System On Chip (SoC) applications.
- Self-aware system-on-chip (SoC)
- Level
- Smart appliances
- Mobile computing
- Communication interfaces ( I2C, SPI )
- Smart appliances
- Body control module
- Smartphones
- Wireless sensor networks
- Deep learning hardware
