Intel EP4CGX75DF27C6N
- EP4CGX75DF27C6N
- Intel
- IC FPGA 310 I/O 672FBGA
- Embedded - FPGAs (Field Programmable Gate Array)
- EP4CGX75DF27C6N Datasheet
- 672-BGA
- 672-BGA
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Lead free / RoHS Compliant - 1960
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What is EP4CGX75DF27C6N
Intel Part Number EP4CGX75DF27C6N(Embedded - FPGAs (Field Programmable Gate Array)), developed and manufactured by Intel, distributed globally by Jinftry. We distribute various electronic components from world-renowned brands and provide one-stop services, making us a trusted global electronic component distributor.
EP4CGX75DF27C6N is one of the part numbers distributed by Jinftry, and you can learn about its specifications/configurations, package/case, Datasheet, and other information here. Electronic components are affected by supply and demand, and prices fluctuate frequently. If you have a demand, please do not hesitate to send us an RFQ or email us immediately [email protected] Please inquire about the real-time unit price, Data Code, Lead time, payment terms, and any other information you would like to know. We will do our best to provide you with a quotation and reply as soon as possible.
EP4CGX75DF27C6N Specifications
- Part NumberEP4CGX75DF27C6N
- CategoryEmbedded - FPGAs (Field Programmable Gate Array)
- ManufacturerIntel
- DescriptionIC FPGA 310 I/O 672FBGA
- Package672-BGA
- SeriesCyclone® IV GX
- Voltage - Supply1.16 V ~ 1.24 V
- Operating Temperature0°C ~ 85°C (TJ)
- Mounting TypeSurface Mount
- Package / Case672-BGA
- Supplier Device Package672-FBGA (27x27)
- Number of I/O310
- Number of LABs/CLBs4620
- Number of Logic Elements/Cells73920
- Total RAM Bits4257792
Application of EP4CGX75DF27C6N
EP4CGX75DF27C6N Datasheet
EP4CGX75DF27C6N Datasheet , 672-BGA,Cyclone® IV GX,1.16 V ~ 1.24 V,0°C ~ 85°C (TJ),Surface Mount,672-BGA,672-FBGA (27x27),310,4620,73920,4257792
EP4CGX75DF27C6N Classification
Embedded - FPGAs (Field Programmable Gate Array)
FAQ about Embedded - FPGAs (Field Programmable Gate Array)
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1. What is the hardware of FPGA?
FPGA (Field Programmable Gate Array) is a highly flexible programmable logic chip that users can program to achieve specific logic functions according to their needs. The main uses of FPGA include communications and networks, digital signal processing, automotive and aerospace, industrial automation, high-performance computing, smart Internet of Things and many other aspects.
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2. Is FPGA a controller or a processor?
FPGA is a programmable integrated circuit. It is neither a traditional controller nor a traditional processor, but a device between the two. FPGAs are programmed with hardware description languages and can customize circuits according to requirements, making them suitable for application scenarios that require flexible configuration and high performance.
The difference between FPGAs and microcontrollers (MCUs) and central processing units (CPUs) lies in their flexibility and application scenarios. MCUs and CPUs are usually microcontrollers and processors with preset functions, suitable for environments that perform single tasks and require efficient execution. FPGAs, on the other hand, have higher flexibility and reconfigurability, can be programmed and reprogrammed according to specific applications, and are suitable for applications that require high customization and optimized performance.
The advantages of FPGAs include their high flexibility and reconfigurability, which makes them ideal for applications that require frequent updates or optimization of logic. Compared with application-specific integrated circuits (ASICs), FPGAs do not require permanent design fixes on silicon, so new features can be developed and tested or bugs can be fixed more quickly.
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3. Is FPGA good for AI ?
FPGAs are good for AI. FPGAs offer a variety of advantages in the field of AI, including high performance, low latency, cost-effectiveness, energy efficiency and flexibility.
The main advantages of FPGAs in the field of AI include:
High performance and low latency: FPGAs offer low latency as well as deterministic latency, which is critical for many applications with strict deadlines, such as real-time applications such as speech recognition, video streaming and action recognition.
Cost-effectiveness: FPGAs can be reprogrammed for different data types and functions after manufacturing, which creates value compared to replacing applications with new hardware. By integrating additional functions onto the same chip, designers can reduce costs and save board space.
Energy efficiency: FPGAs enable designers to fine-tune hardware according to application requirements, using techniques such as INT8 quantization to reduce memory and computing requirements, thereby reducing energy consumption.
Flexibility and customization: FPGA can be optimized at the hardware level for specific algorithms, reducing unnecessary computing and storage overhead. For example, AMD's Alveo V80 accelerator card uses Versal FPGA adaptive SoC and HBM technology to provide efficient computing power.
In summary, FPGA has significant advantages in the field of AI, including high performance, low latency, cost-effectiveness, energy efficiency and flexibility, making it an ideal solution in AI applications.
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