Ghent University Academic Bibliography (Ghent University) · 2006 · 29 citations · 5 references
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EngineeringComputer EngineeringComputer ScienceComputer ArchitectureField-programmable Gate ArraysReconfigurable ComputingField-programmable Gate Array ArchitectureFpga ArchitectureHardware AccelerationParallel ArchitecturesParallel Computer ArchitectureSpiking Neural NetworksNeuromorphic HardwareParallel Computing ArchitecturesParallel ProcessingSpiking Network ArchitecturesSpiking Neural Network ModelsSpiking Neuron Models
Current digital, directly mapped implementations of spiking neural networks use serial processing and parallel arithmetic. On a standard CPU, this might be the good choice, but when using a Field Programmable Gate Array (FPGA), other implementation architectures are possible. This work present a hardware implementation of a broad class of integrate and fire spiking neurons with synapse models using parallel processing and serial arithmetic. This results in very fast and compact implementations of spiking neurons on FPGA.
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