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FPGAs are programmable like GPUs or CPUs but are aimed at parallel, low-latency, high-throughput problems like inference and Deep Neural Networks.

FPGAs have a number of benefits, the most notable of which is speed. While FPGAs run at a slow clock speed relative to modern CPUs, they are fundamentally concurrent, rather than running streams of sequential instructions, with data flowing optimally between these concurrent operations, resulting in a dramatic net increase in performance. There is the potential for applications to run up to 100 times faster over the same code running on traditional CPUs.

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