Intel 10M16SCE144I7G
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- 10M16SCE144I7G
- Intel
- IC FPGA 101 I/O 144EQFP
- Embedded - FPGAs (Field Programmable Gate Array)
- 10M16SCE144I7G Datasheet
- 144-LQFP Exposed Pad
- 144-LQFP Exposed Pad
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What is 10M16SCE144I7G
Intel Part Number 10M16SCE144I7G（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.
10M16SCE144I7G 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.
10M16SCE144I7G Specifications
- Part Number10M16SCE144I7G
- CategoryEmbedded - FPGAs (Field Programmable Gate Array)
- ManufacturerIntel
- DescriptionIC FPGA 101 I/O 144EQFP
- Package144-LQFP Exposed Pad
- SeriesMAX® 10
- Voltage - Supply2.85 V ~ 3.465 V
- Operating Temperature-40°C ~ 100°C (TJ)
- Mounting TypeSurface Mount
- Package / Case144-LQFP Exposed Pad
- Supplier Device Package144-EQFP (20x20)
- Number of I/O101
- Number of LABs/CLBs1000
- Number of Logic Elements/Cells16000
- Total RAM Bits562176
Application of 10M16SCE144I7G
10M16SCE144I7G Datasheet
10M16SCE144I7G Datasheet , 144-LQFP Exposed Pad,MAX® 10,2.85 V ~ 3.465 V,-40°C ~ 100°C (TJ),Surface Mount,144-LQFP Exposed Pad,144-EQFP (20x20),101,1000,16000,562176
10M16SCE144I7G Classification
Embedded - FPGAs (Field Programmable Gate Array)
FAQ about Embedded - FPGAs (Field Programmable Gate Array)
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1. Is FPGA a microprocessor?
FPGA is not a microprocessor. FPGA (Field-Programmable Gate Array) is a special digital circuit that is mainly used to implement complex logic functions, while microprocessors are processors used to execute instructions.
FPGA and microprocessors have significant differences in function and use. FPGA is a semi-custom digital circuit that can be programmed during the hardware design stage to implement specific logic functions. FPGA solves the shortcomings of customized circuits and overcomes the shortcomings of the limited number of gate circuits of the original programmable devices. It is suitable for occasions that require highly customized logic functions. In contrast, a microprocessor (such as a CPU) is a general-purpose computing device used to execute instructions stored in it, process data, and perform computing tasks. Microprocessors include MCU (microcontroller), DSP (digital signal processor), etc., each of which has different application scenarios and functional characteristics.
Specifically, FPGA and microprocessor are also different in structure and working mode. FPGA consists of a large number of programmable logic units, and users can program to implement any logic function as needed. Microprocessors contain a central processing unit (CPU), memory, and input and output interfaces to execute predefined instruction sets, process data, and perform computing tasks. In addition, FPGAs are usually used in situations that require high-speed processing and parallel computing, such as communications, image processing, etc., while microprocessors are widely used in various computing devices and systems. -
2. Why use FPGA as a digital controller?
The main reason for using FPGA as a digital controller is its flexibility and programmability. FPGA (Field Programmable Gate Array) is a chip whose internal structure can be changed through programming. It has high flexibility and programmability, which makes FPGA widely used in the field of digital controllers.
The flexibility of FPGA is reflected in the fact that its logic units can be configured to implement different logic functions. Users can use hardware description languages (such as VHDL or Verilog) to write programs to map logic functions to lookup tables (LUTs) and logic units inside FPGA. This flexibility allows FPGAs to adapt to different application requirements and can be reprogrammed as needed to adapt to new application scenarios.
In addition, FPGAs also have high-performance parallel computing capabilities and high-speed data processing capabilities, which makes it play an important role in digital signal processing, image processing, network communication and other fields. The parallel processing capabilities of FPGAs enable it to handle multiple tasks at the same time, improving overall processing efficiency. -
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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