Abstract-Bluehive is a custom 64-FPGA machine targeted at scientific simulations with demanding communication requirements. Bluehive is designed to be extensible with a reconfigurable communication topology suited to algorithms with demanding high-bandwidth and low-latency communication, something which is unattainable with commodity GPGPUs and CPUs. We demonstrate that a spiking neuron algorithm can be efficiently mapped to Bluehive using Bluespec SystemVerilog by taking a communication-centric approach. This contrasts with many FPGA-based neural systems which are very focused on parallel computation, resulting in inefficient use of FPGA resources. Our design allows 64k neurons with 64M synapses per FPGA and is scalable to a large number of FPGAs.