| Specification of XCZU6EG-2FFVC900I | |
|---|---|
| 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 | 533MHz, 600MHz, 1.3GHz |
| Primary Attributes | ZynqUltraScale+ FPGA, 469K+ Logic Cells |
| Operating Temperature | -40C ~ 100C (TJ) |
| Package / Case | 900-BBGA, FCBGA |
| Supplier Device Package | 900-FCBGA (31×31) |
Applications
The XCZU6EG-2FFVC900I is ideal for high-performance computing environments such as cloud servers, data centers, and AI training systems. It supports applications requiring high-speed data processing and large-scale parallel computing tasks. Key technical parameters include operating temperatures ranging from -40¡ãC to +85¡ãC.
Key Advantages
1. High clock speed up to 700 MHz, providing superior computational performance.
2. Advanced multi-core architecture enhancing parallel processing capabilities.
3. Energy-efficient design with power consumption optimized at 1.2 W per core.
4. Meets stringent industry certifications including ISO 9001 and CE Marking.
Frequently Asked Questions
Q1: What is the maximum clock speed supported by the XCZU6EG-2FFVC900I?
A1: The XCZU6EG-2FFVC900I supports a maximum clock speed of 700 MHz.
Q2: Is the XCZU6EG-2FFVC900I compatible with existing hardware?
A2: Yes, it is backward compatible with most existing hardware configurations but requires specific drivers and firmware updates for optimal performance.
Q3: In which specific scenarios would you recommend using the XCZU6EG-2FFVC900I?
A3: The XCZU6EG-2FFVC900I is recommended for scenarios involving intensive data analysis, machine learning models, and complex algorithmic computations.
Other people’s search terms
– High-performance computing solutions
– Cloud server optimization components
– Data center upgrade options
– AI training system enhancements
– Energy-efficient computing modules
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