The main difference between the two is that FPGAs are programmable and can be used for a variety of tasks, while GPUs are specialized for graphics-related tasks. In terms of performance, FPGAs are generally faster than GPUs. However, GPUs are generally more power efficient.
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What is FPGA?
FPGA stands for field programmable gate array. FPGA is a programmable logic device that harbors a complex architecture that allows them a high logic capacity, making them ideal for high gate count designs such as server applications, and video encoders/decoders. Due to the fact of FPGA consist of a large number of gates the internal delay in this chip is sometimes unpredictable.
FPGA Vs GPU | Difference between FPGA and GPU:
- FPGA stands for field programmable gate array, and GPU stands for the graphics processing unit.
- FPGAs offer low latency than GPUs, While GPUs have relatively high latency than FPGAs.
- FPGA is a better energy-efficient solution compared to GPU. While GPUs are similarly power-efficient, SIMD streams are the only ones.
- FPGA is not good at floating-point computation. GPUs are excellent at performing floating-point operations.
- FPGA are difficult to program. While GPU has a mature ecosystem.
- Hardware description languages or HDL, such as VHDL and Verilog can be used to program FPGAs. programming languages for general-purpose software such as C, C++, Java, Python, etc, can be used to set up GPUs.