A single FeNN FPGA vector core can classify spoken digits as accurately as a 32-bit floating-point SNN simulator while running faster and using less energy than an embedded GPU and a reported Loihi baseline.
Stochastic rounding and reduced-precision fixed-point arithmetic for solving neural ordinary dif- ferential equations
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FeNN: A RISC-V vector processor for Spiking Neural Network acceleration
A single FeNN FPGA vector core can classify spoken digits as accurately as a 32-bit floating-point SNN simulator while running faster and using less energy than an embedded GPU and a reported Loihi baseline.