#4046 Neural Networks on FPGAs
#4046 Neural Networks on FPGAs #4046 Can FPGA's be used for neural networks? Yes, absolutely. In the world of hardware acceleration, FPGAs (Field Programmable Gate Arrays) have carved out a significant niche for neural networks, particularly for inference —the phase where a trained model is actually put to work in the real world. While GPUs remain the kings of training massive models due to their raw throughput, FPGAs are often the "secret weapon" for specialized, real-time applications. Why FPGAs? The "Magic Three" FPGAs offer three distinct advantages that make them highly attractive for specific AI workloads: Ultra-Low Latency: Unlike GPUs, which usually process data in "batches" to stay efficient, FPGAs can process data in a streaming fashion (pixel-by-pixel or packet-by-packet). This is critical for time-sensitive tasks like autonomous driving or high-frequency trading. Energy Efficiency: Because you can program the hardware to do exactly ...