Specification of XCZU3EG-1SFVC784I | |
---|---|
Status | Active |
Series | Zynq? UltraScale+? MPSoC EG |
Package | Tray |
Supplier | AMD |
Architecture | MCU, FPGA |
Core Processor | Quad ARM Cortex-A53 MPCore with CoreSight, Dual ARMCortex-R5 with CoreSight, ARM Mali-400 MP2 |
Flash Size | – |
RAM Size | 256KB |
Peripherals | DMA, WDT |
Connectivity | CANbus, EBI/EMI, Ethernet, IC, MMC/SD/SDIO, SPI, UART/USART, USB OTG |
Speed | 500MHz, 600MHz, 1.2GHz |
Primary Attributes | ZynqUltraScale+ FPGA, 154K+ Logic Cells |
Operating Temperature | -40C ~ 100C (TJ) |
Package / Case | 784-BFBGA, FCBGA |
Supplier Device Package | 784-FCBGA (23×23) |
Applications
The XCZU3EG-1SFVC784I is ideal for high-performance computing environments such as cloud servers, data centers, and AI training systems. It excels in applications requiring high-speed data processing and large-scale parallel computing tasks. This FPGA can also be utilized in telecommunications infrastructure for advanced signal processing and network management.
Key Advantages
1. Operating Temperature Range: -40°C to +85°C
2. Unique Architecture Feature: Advanced multi-core processing capabilities
3. Power Efficiency: 1.5W per gigabit per second
4. Certification Standards: Meets industry standards for reliability and performance
Frequently Asked Questions
Q1: What is the maximum clock frequency supported by the XCZU3EG-1SFVC784I?
A1: The XCZU3EG-1SFVC784I supports a maximum clock frequency of up to 600 MHz.
Q2: Is the XCZU3EG-1SFVC784I compatible with existing hardware?
A2: Yes, it is backward compatible with previous generations of Xilinx FPGAs, ensuring seamless integration into existing designs.
Q3: In which specific scenarios would you recommend using the XCZU3EG-1SFVC784I?
A3: The XCZU3EG-1SFVC784I is recommended for scenarios involving complex data analysis, real-time processing, and high-bandwidth communication systems.
Other people’s search terms
– High-performance computing solutions
– Advanced signal processing FPGA
– Cloud server FPGA
– Large-scale parallel computing
– AI training system FPGA