| Specification of XCZU11EG-2FFVB1517I | |
|---|---|
| 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, 653K+ Logic Cells |
| Operating Temperature | -40C ~ 100C (TJ) |
| Package / Case | 1517-BBGA, FCBGA |
| Supplier Device Package | 1517-FCBGA (40×40) |
Applications
The XCZU11EG-2FFVB1517I is ideal for high-performance computing environments due to its advanced processing capabilities. It excels in applications such as artificial intelligence training, big data analytics, and cloud computing services. This device operates within a wide range of temperatures from -40°C to +85°C, ensuring reliability across various environmental conditions.
Key Advantages
1. High-speed processing with up to 6.2 Gbps data transfer rate.
2. Advanced multi-core architecture supporting over 100 concurrent threads.
3. Energy-efficient design consuming less than 10W at full load.
4. Meets stringent industrial certification standards including CE, FCC, and RoHS.
Frequently Asked Questions
Q1: Can the XCZU11EG-2FFVB1517I handle complex AI models?
A1: Yes, it supports large-scale neural networks with millions of parameters efficiently.
Q2: Is this device compatible with legacy systems?
A2: The XCZU11EG-2FFVB1517I is backward-compatible with previous generations but offers significant performance improvements.
Q3: In which specific scenarios would you recommend using this XCZU11EG-2FFVB1517I?
A3: This device is recommended for high-density server farms, edge computing nodes, and critical infrastructure monitoring systems.
Other people’s search terms
– High-performance FPGA solutions
– AI acceleration with FPGAs
– Scalable computing platforms
– Energy-efficient FPGA technology
– Industrial-grade FPGA devices
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