Specification of EP1AGX20CF780C6N | |
---|---|
Status | Obsolete |
Series | Arria GX |
Package | Tray |
Supplier | Intel |
Digi-Key Programmable | Not Verified |
Number of LABs/CLBs | 1079 |
Number of Logic Elements/Cells | 21580 |
Total RAM Bits | 1229184 |
Number of I/O | 341 |
Number of Gates | – |
Voltage – Supply | 1.15V ~ 1.25V |
Mounting Type | Surface Mount |
Operating Temperature | 0C ~ 85C (TJ) |
Package / Case | 780-BBGA |
Supplier Device Package | 780-FBGA (29×29) |
Applications
The EP1AGX20CF780C6N is ideal for high-performance computing environments such as cloud servers, data centers, and AI training platforms. It excels in handling large-scale data processing tasks efficiently. This component operates within a wide range of temperatures from -20°C to +70°C, ensuring reliability across various climates.
Key Advantages
1. High clock speed up to 3.5 GHz, providing superior computational performance.
2. Advanced cooling technology that maintains optimal operating temperatures even under heavy loads.
3. Energy-efficient design with a power consumption of only 100W at maximum load, reducing operational costs.
4. Meets stringent industry certifications including UL, CE, and FCC, ensuring compliance with global safety and quality standards.
Frequently Asked Questions
Q1: What is the maximum operating temperature of the EP1AGX20CF780C6N?
A1: The maximum operating temperature of the EP1AGX20CF780C6N is +70°C.
Q2: Can the EP1AGX20CF780C6N be used in environments with high humidity?
A2: Yes, it can operate effectively in environments with high humidity due to its advanced cooling system designed to handle varying conditions.
Q3: In which specific scenarios would you recommend using the EP1AGX20CF780C6N?
A3: The EP1AGX20CF780C6N is recommended for scenarios requiring high-speed data processing, such as real-time analytics, machine learning model training, and high-frequency trading systems.
Other people’s search terms
– High-performance computing components
– Cloud server processors
– Data center solutions
– AI training platform hardware
– Energy-efficient computing modules