Abstract: There is provided a neurosynaptic processing core with spike time dependent plasticity (STDP) learning for a spiking neural network, including: a spiking neuron block including a pre-synaptic block and a post-synaptic block; a synapse block communicatively coupled to the spiking neuron block; a STDP learning block communicatively coupled to the spiking neuron block and the synapse block, the STDP learning block including a pre-synaptic event accumulator including a pre-synaptic spike event memory block and a pre-synaptic spike parameter modifier; a post-synaptic event accumulator including a post-synaptic spike event memory block and a post-synaptic spike parameter modifier, a weight change accumulator, and a weight change parameter modifier; a learning error modulator; and a synaptic weight modifier configured to modify a synaptic weight parameter based on a weight change parameter and a learning error corresponding to the synaptic weight parameter.

Abstract: There is provided a neural network processor system including: a plurality of neural processing units, including a first neural processing unit and a second neural processing unit, whereby each neural processing unit comprises an array of neural processing core blocks, each neural processing core block comprising a neural processing core; and at least one central processing unit communicatively coupled to the plurality of neural processing units and configured to coordinate the plurality of neural processing units for performing neural network computations. In particular, the first and second neural processing units have a different structural configuration to each other. There is also provided a corresponding method of operating and a corresponding method of forming the neural network processor system.

Abstract: There is provided a neural network processor system including: a neural processing unit including a plurality of neural processing cores; a router network including a plurality of routers communicatively coupled to the plurality of neural processing cores, respectively; and a host processing unit communicatively coupled to the neural processing unit based on the router network and configured to coordinate the neural processing unit for performing neural network computations.

Abstract: This document describes a spatial light modulator that comprises a pixel array having a plurality of pixels whereby each pixel in this array is communicatively coupled to a digital pixel circuit which are in turn all coupled to a bit-plane control circuit. The bit-plane control circuit is configured to generate, using a Pulse Code Modulation (PCM) algorithm, bit-plane signals that are used to control the sample and hold functions performed by each of the digital pixel circuits so that the pixel array may carry out its scanning function accurately and in a power efficient manner.

Abstract: This document describes a spatial light modulator that comprises a pixel array having a plurality of pixels whereby each pixel in this array is communicatively coupled to a digital pixel circuit which are in turn all coupled to a bit-plane control circuit. The bit-plane control circuit is configured to generate, using a Pulse Code Modulation (PCM) algorithm, bit-plane signals that are used to control the sample and hold functions performed by each of the digital pixel circuits so that the pixel array may carry out its scanning function accurately and in a power efficient manner.

Abstract: There is provided a neurosynaptic processing core with spike time dependent plasticity (STDP) learning for a spiking neural network, including: a spiking neuron block including a pre-synaptic block and a post-synaptic block; a synapse block communicatively coupled to the spiking neuron block; a STDP learning block communicatively coupled to the spiking neuron block and the synapse block, the STDP learning block including a pre-synaptic event accumulator including a pre-synaptic spike event memory block and a pre-synaptic spike parameter modifier; a post-synaptic event accumulator including a post-synaptic spike event memory block and a post-synaptic spike parameter modifier, a weight change accumulator, and a weight change parameter modifier; a learning error modulator; and a synaptic weight modifier configured to modify a synaptic weight parameter based on a weight change parameter and a learning error corresponding to the synaptic weight parameter.

Abstract: There is provided a neural network processor system including: a plurality of neural processing units, including a first neural processing unit and a second neural processing unit, whereby each neural processing unit comprises an array of neural processing core blocks, each neural processing core block comprising a neural processing core; and at least one central processing unit communicatively coupled to the plurality of neural processing units and configured to coordinate the plurality of neural processing units for performing neural network computations. In particular, the first and second neural processing units have a different structural configuration to each other. There is also provided a corresponding method of operating and a corresponding method of forming the neural network processor system.

Abstract: Various embodiments may provide a circuit arrangement. The circuit arrangement may include a first spin-orbit torque magnetic tunnel junction cell, a second spin-orbit torque magnetic tunnel junction cell, a first driver circuit arrangement, a second driver circuit arrangement, and a read circuit arrangement. The circuit arrangement allows for the operation of a non-volatile flip-flop based on spin-orbit torque effect.

Abstract: Various embodiments may provide a circuit arrangement. The circuit arrangement may include a first spin-orbit torque magnetic tunnel junction cell, a second spin-orbit torque magnetic tunnel junction cell, a first driver circuit arrangement, a second driver circuit arrangement, and a read circuit arrangement. The circuit arrangement allows for the operation of a non-volatile flip-flop based on spin-orbit torque effect.

Abstract: According to embodiments of the present invention, a writing circuit for a magnetoresistive memory cell is provided. The writing circuit includes a first connecting terminal configured to provide a first electrical signal to switch a variable magnetization orientation of the free magnetic layer from a first magnetization orientation to a second magnetization orientation; a second connecting terminal configured to provide a second electrical signal to switch the magnetization orientation from the second magnetization orientation to the first magnetization orientation; and a sourcing switch configured to provide for a write operation a connection of the first or second connecting terminal to a node coupleable to the magnetoresistive memory cell. The first and second electrical signals have different amplitudes, and the first and second electrical signals are of the same polarity. Further embodiments relate to a memory cell arrangement and a method of writing into a target magnetoresistive memory cell.

Abstract: According to embodiments of the present invention, a writing circuit for a magnetoresistive memory cell is provided. The writing circuit includes a first connecting terminal configured to provide a first electrical signal to switch a variable magnetization orientation of the free magnetic layer from a first magnetization orientation to a second magnetization orientation; a second connecting terminal configured to provide a second electrical signal to switch the magnetization orientation from the second magnetization orientation to the first magnetization orientation; and a sourcing switch configured to provide for a write operation a connection of the first or second connecting terminal to a node coupleable to the magnetoresistive memory cell. The first and second electrical signals have different amplitudes, and the first and second electrical signals are of the same polarity. Further embodiments relate to a memory cell arrangement and a method of writing into a target magnetoresistive memory cell.