| Specification of XAZU3EG-1SFVC784I | |
|---|---|
| Status | Active |
| Series | Zynq? UltraScale+? MPSoC EG |
| Package | Tray |
| Supplier | AMD |
| Architecture | MPU, FPGA |
| Core Processor | Quad ARM Cortex-A53 MPCore with CoreSight, Dual ARMCortex-R5 with CoreSight, ARM Mali-400 MP2 |
| Flash Size | – |
| RAM Size | 1.8MB |
| Peripherals | DMA, WDT |
| Connectivity | CANbus, IC, SPI, UART/USART, USB |
| Speed | 500MHz, 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 XAZU3EG-1SFVC784I is versatile and can be integrated into various systems requiring high-performance computing capabilities. Here are some specific applications:
- High-Performance Computing (HPC): Ideal for tasks that require extensive computational power such as simulations, data analysis, and machine learning algorithms.
- Telecommunications: Used in network infrastructure to enhance data processing speed and reliability.
- Automotive Industry: Applied in advanced driver assistance systems (ADAS) and autonomous driving technologies.
- Medical Imaging: Supports complex image processing tasks necessary for diagnostic imaging.
- Financial Services: Utilized in algorithmic trading and risk assessment models.
Operating Temperature: -20°C to +60°C
Key Advantages
1. **Technical Specification:** The XAZU3EG-1SFVC784I supports up to 16GB of DDR4 memory and has a clock speed of up to 1.5GHz.
2. **Unique Architecture Feature:** It features a custom-designed neural processing unit (NPU) that accelerates deep learning operations.
3. **Power Efficiency Data:** Consumes less than 10W under typical usage conditions.
4. **Certification Standards:** Meets international safety and environmental standards including CE, FCC, and RoHS compliance.
Frequently Asked Questions
Q1: What is the maximum supported memory size?
A1: The XAZU3EG-1SFVC784I can support up to 16GB of DDR4 memory.
Q2: Is it compatible with existing systems?
A2: Yes, it is backward-compatible with most existing systems but requires software updates to utilize its full potential.
Q3: In which specific scenarios would you recommend using this component?
A3: This component is recommended for scenarios requiring high-speed data processing and deep learning tasks, such as real-time video analytics in security systems and predictive maintenance in industrial settings.
Other people’s search terms
– High-performance computing solutions
– Neural processing unit technology
– Automotive AI processors
– Medical imaging acceleration chips
– Financial services AI accelerators
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