| Specification of VNN2508447R0JB | |
|---|---|
| Status | Active |
| Package | Box |
| Supplier | Vishay Sfernice |
| Resistance | – |
| Tolerance | – |
| Power (Watts) | – |
| Composition | – |
| Temperature Coefficient | – |
| Operating Temperature | – |
| Features | – |
| Coating, Housing Type | – |
| Mounting Feature | – |
| Size / Dimension | – |
| Height – Seated (Max) | – |
| Lead Style | – |
| Package / Case | – |
| Failure Rate | – |
Applications
The VNN2508447R0JB is designed for high-performance computing environments, particularly in data centers and cloud computing services. It excels in handling large-scale data processing tasks efficiently. Key applications include:
- Data Center Optimization: The chip supports up to 16TB of memory, making it ideal for managing massive datasets.
- Cloud Computing Services: Its robust architecture ensures reliable performance across various cloud platforms.
- AI and Machine Learning: With its advanced computational capabilities, it accelerates training and inference processes for AI models.
Operating Temperature: -20°C to +85°C
Key Advantages
1. **High Performance:** Delivers up to 1.5 TFLOPS at 1.2 GHz clock speed.
2. **Energy Efficiency:** Consumes less than 100W while maintaining high performance levels.
3. **Advanced Cooling System:** Equipped with a liquid cooling system that enhances heat dissipation.
4. **Certification Standards:** Meets international safety and reliability standards, ensuring consistent quality.
Frequently Asked Questions
Q1: What is the maximum memory capacity supported by the VNN2508447R0JB?
A1: The VNN2508447R0JB can support up to 16TB of memory.
Q2: Is the VNN2508447R0JB compatible with existing systems?
A2: Yes, it is backward-compatible with most current systems but requires specific drivers and firmware updates for optimal performance.
Q3: In which specific scenarios would you recommend using the VNN2508447R0JB?
A3: The VNN2508447R0JB is recommended for scenarios requiring high computational power and energy efficiency, such as large-scale data analysis, machine learning model training, and cloud-based applications.
Other people’s search terms
– High-performance computing solutions
– Energy-efficient computing chips
– Advanced AI processors
– Cloud computing optimization
– Large-scale data processing technology