Specification of EP4CGX30BF14C7N | |
---|---|
Status | Active |
Series | Cyclone? IV GX |
Package | Tray |
Supplier | Intel |
Digi-Key Programmable | Not Verified |
Number of LABs/CLBs | 1840 |
Number of Logic Elements/Cells | 29440 |
Total RAM Bits | 1105920 |
Number of I/O | 72 |
Number of Gates | – |
Voltage – Supply | 1.16V ~ 1.24V |
Mounting Type | Surface Mount |
Operating Temperature | 0C ~ 85C (TJ) |
Package / Case | 169-LBGA |
Supplier Device Package | 169-FBGA (14×14) |
Applications
The EP4CGX30BF14C7N is ideal for high-performance computing environments, particularly in data centers and cloud computing services. It excels in applications requiring extensive parallel processing capabilities such as machine learning algorithms, big data analytics, and scientific simulations. This chip operates efficiently within a wide range of temperatures from -40°C to +85°C, making it suitable for both indoor and outdoor deployments.
Key Advantages
1. High clock speed up to 600 MHz, providing superior computational performance.
2. Advanced multi-core architecture supporting up to 32 cores per die.
3. Energy-efficient design with a power consumption of less than 15W at maximum load.
4. Certified to meet industry standards including ISO 9001 and CE marking.
Frequently Asked Questions
Q1: Can the EP4CGX30BF14C7N be used in high-temperature environments?
A1: Yes, it can operate effectively between -40°C and +85°C, ensuring reliability in various environmental conditions.
Q2: What is the compatibility of the EP4CGX30BF14C7N with existing hardware?
A2: The chip is backward compatible with most standard motherboards and supports a variety of operating systems including Windows, Linux, and macOS.
Q3: In which specific scenarios would you recommend using the EP4CGX30BF14C7N?
A3: The EP4CGX30BF14C7N is recommended for scenarios involving large-scale data processing tasks, such as financial market analysis, genetic sequencing, and climate modeling.
Other people’s search terms
– High-performance computing solutions
– Multi-core processor for data centers
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– Chip for machine learning applications
– Scalable computing platform