Abstract: A neuromorphic computing system is provided which comprises: a synapse core; and a pre-synaptic neuron, a first post-synaptic neuron, and a second post-synaptic neuron coupled to the synaptic core, wherein the synapse core is to: receive a request from the pre-synaptic neuron, generate, in response to the request, a first address of the first post-synaptic neuron and a second address of the second post-synaptic neuron, wherein the first address and the second address are not stored in the synapse core prior to receiving the request.

Abstract: System and techniques for spike timing dependent plasticity (STDP) in neuromorphic hardware are described herein. A first spike may be received, at a first neuron at a first time, from a second neuron. The first neuron may produce a second spike at a second time after the first time. At a third time after the second time, the first neuron may receive a third spike from the second neuron. Here, the third spike is a replay of the first spike with a defined time offset. The first neuron may then perform long term potentiation (LTP) for the first spike using the third spike.

Abstract: A neuromorphic computing system is provided which comprises: a synapse core; and a pre-synaptic neuron, a first post-synaptic neuron, and a second post-synaptic neuron coupled to the synaptic core, wherein the synapse core is to: receive a request from the pre-synaptic neuron, generate, in response to the request, a first address of the first post-synaptic neuron and a second address of the second post-synaptic neuron, wherein the first address and the second address are not stored in the synapse core prior to receiving the request.

Abstract: Systems and methods may apply homeostatic plasticity control in a spiking neural network, such as at a neuron of a core of the spiking neural network. The neuron may receive input spike information and determine whether to activate an output spike at the neuron based at least in part on the input spike information and a bias value. The bias value may be set based on whether the neuron issued a previous output spike during a previous time period. The bias value may be updated based on whether the output spike was activated at the neuron. For example, in accordance with a determination to activate the output spike, the bias value may be decreased, and in accordance with a determination to not activate the output spike, the bias value may be increased.

Abstract: A neuromorphic computing system is provided which comprises: a synapse core; and a pre-synaptic neuron, a first post-synaptic neuron, and a second post-synaptic neuron coupled to the synaptic core, wherein the synapse core is to: receive a request from the pre-synaptic neuron, generate, in response to the request, a first address of the first post-synaptic neuron and a second address of the second post-synaptic neuron, wherein the first address and the second address are not stored in the synapse core prior to receiving the request.

Abstract: System and techniques for spike timing dependent plasticity (STDP) in neuromorphic hardware are described herein. A first spike may be received, at a first neuron at a first time, from a second neuron. The first neuron may produce a second spike at a second time after the first time. At a third time after the second time, the first neuron may receive a third spike from the second neuron. Here, the third spike is a replay of the first spike with a defined time offset. The first neuron may then perform long term potentiation (LTP) for the first spike using the third spike.