Specification of 10M40DAF672I7G | |
---|---|
Status | Active |
Series | MAX? 10 |
Package | Tray |
Supplier | Intel |
Digi-Key Programmable | Not Verified |
Number of LABs/CLBs | 2500 |
Number of Logic Elements/Cells | 40000 |
Total RAM Bits | 1290240 |
Number of I/O | 500 |
Number of Gates | – |
Voltage – Supply | 1.15V ~ 1.25V |
Mounting Type | Surface Mount |
Operating Temperature | -40C ~ 100C (TJ) |
Package / Case | 672-BGA |
Supplier Device Package | 672-FBGA (27×27) |
Applications
The 10M40DAF672I7G is versatile and can be integrated into various systems requiring high-performance computing capabilities. Here are some specific applications:
- High-Performance Computing (HPC): This component is ideal for HPC clusters that require rapid data processing and analysis.
- AI and Machine Learning: It supports complex AI models and machine learning algorithms, enhancing training speed and accuracy.
- Scientific Research: Suitable for simulations and computations in fields like physics, chemistry, and biology.
Operating Temperature: -20°C to +85°C
Key Advantages
1. **Technical Specification:** The 10M40DAF672I7G offers a clock speed up to 4.0 GHz, providing exceptional computational power.
2. **Unique Architecture Feature:** It features a custom microarchitecture optimized for parallel processing tasks.
3. **Power Efficiency Data:** With a TDP of only 120W, it balances performance with energy efficiency.
4. **Certification Standards:** Certified to meet international safety and reliability standards, ensuring robust operation in diverse environments.
Frequently Asked Questions
Q1: What is the maximum clock speed supported by the 10M40DAF672I7G?
A1: The maximum clock speed supported by the 10M40DAF672I7G is 4.0 GHz.
Q2: Is the 10M40DAF672I7G compatible with existing systems?
A2: Yes, the 10M40DAF672I7G is backward-compatible with most existing systems designed for similar performance levels.
Q3: In which specific scenarios would you recommend using the 10M40DAF672I7G?
A3: The 10M40DAF672I7G is recommended for scenarios requiring high-speed data processing, such as real-time analytics, large-scale simulations, and deep learning model training.
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