  Neuromorphic architectures such as IBM's TrueNorth and Intel's Loihi have
been introduced as platforms for energy efficient spiking neural network
execution. However, there is no framework that allows for rapidly experimenting
with neuromorphic architectures and studying the trade space on hardware
performance and network accuracy. Fundamentally, this creates a barrier to
entry for hardware designers looking to explore neuromorphic architectures. In
this paper we present an open-source FPGA based emulation environment for
neuromorphic computing research. We prototype IBM's TrueNorth architecture as a
reference design and discuss FPGA specific design decisions made when
implementing and integrating it's core components. We conduct resource
utilization analysis and realize a streaming-enabled TrueNorth architecture on
the Zynq UltraScale+ MPSoC. We then perform functional verification by
implementing networks for MNIST dataset and vector matrix multiplication (VMM)
in our emulation environment and present an accuracy-based comparison based on
the same networks generated using IBM's Compass simulation environment. We
demonstrate the utility of our emulation environment for hardware designers and
application engineers by altering the neuron behavior for VMM mapping, which
is, to the best of our knowledge, not feasible with any other tool including
IBM's Compass environment. The proposed parameterized and configurable
emulation platform serves as a basis for expanding its features to support
emerging architectures, studying hypothetical neuromorphic architectures, or
rapidly converging to hardware configuration through incremental changes based
on bottlenecks as they become apparent during application mapping process.
