International Business Machines Corporation

Manuel Le Gallo

Abu Sebastian

Tomas Tuma

Evangelos Stavros Eleftheriou

Angeliki Pantazi

Irem Boybat Kara

Tuma Tomas

Giovanni Cherubini

A method and system providing a multi-memristive synaptic element for a cognitive computing system. The multi-memristive synaptic element comprises an array of memristive devices. The method comprises arbitrating a synaptic weight allocation, a related synaptic weight being represented by a synaptic weight variable of said multi-memristive synaptic element, updating said synaptic weight variable by a delta amount, and assigning said memristive devices to elements of a clock-like ordered circular list for selecting a particular memristor of said memristive devices requiring to be updated by a deterministic, periodic global clock that points to a different memristor at every clock tick, such that said multi-memristive synaptic element has a larger dynamic range and a more linear conductance response than a single memristor synaptic element.

Multi-memristive synapse with clock-arbitrated weight update

A device for performing a multiplication of a matrix with a vector. The device comprises a plurality of memory elements, a signal generator and a readout circuit. The signal generator is configured to apply programming signals to the memory elements. The signal generator is further configured to control a first signal parameter of the programming signals in dependence on matrix elements of the matrix and to control a second signal parameter of the programming signals in dependence on vector elements of the vector. The readout circuit is configured to read out memory values of the memory elements. The memory values represent result values of vector elements of a product vector of the multiplication. The memory elements may be in particular resistive memory elements or photonic memory elements. Additionally there is provided a related method and design structure for performing the multiplication of a matrix with a vector.

Memory device for matrix-vector multiplications

A computing system having a computational memory and a method configured to perform computations using an approximate message passing process. The system exploits memcomputing which is a prominent non-von Neumann computational approach expected to significantly improve an energy efficiency of computing systems. The computational memory includes at least one memristive array comprising a plurality of memristive devices arranged in a crossbar topology and the computing system may further comprise digital combinational control circuitry adapted to perform read and write operations on the at least one memristive array and to store at least one state variable of the approximate message passing process. An output of the at least one memristive array represents a result of a computation of the approximate message passing process. The control circuitry may comprise circuitry to iteratively perform computations that may not require high precision.

Non-von neumann optimization based on approximate message passing

A neuromorphic processing device has a device input, for receiving an input data signal, and an assemblage of neuron circuits. Each neuron circuit comprises a resistive memory cell which is arranged to store a neuron state, indicated by cell resistance, and to receive neuron input signals for programming cell resistance to vary the neuron state, and a neuron output circuit for supplying a neuron output signal in response to cell resistance traversing a threshold. The device includes an input signal generator, connected to the device input and the assemblage of neuron circuits, for generating neuron input signals for the assemblage in dependence on the input data signal. The device further includes a device output circuit, connected to neuron output circuits of the assemblage, for producing a device output signal dependent on neuron output signals of the assemblage, whereby the processing device exploits stochasticity of resistive memory cells of the assemblage.

Neuromorphic processing devices

Method to produce a neuromorphic synapse apparatus comprising a memelement for storing a synaptic weight, and programming logic. The memelement is adapted to exhibit a desired programming characteristic. The programming logic is responsive to a stimulus prompting update of the synaptic weight for generating a programming signal for programming the memelement to update said weight. The programming logic may be responsive to an input signal indicating an input weight-change value &#x394;W, and may be adapted to generate a programming signal dependent on the input weight-change value &#x394;W. The programming logic is adapted such that the programming signals exploit the programming characteristic of the memelement to provide a desired weight-dependent synaptic update efficacy.

Neuromorphic synapses

Neuromorphic synapse apparatuscomprises a memelementfor storing a synaptic weight, and programming logic. The memelementis adapted to exhibit a desired programming characteristic. The programming logicis responsive to a stimulus prompting update of the synaptic weight for generating a programming signal for programming the memelementto update said weight. The programming logicmay be responsive to an input signal indicating an input weight-change value &#x394;W, and may be adapted to generate a programming signal dependent on the input weight-change value &#x394;W. The programming logicis adapted such that the programming signals exploit the programming characteristic of the memelementto provide a desired weight-dependent synaptic update efficacy.

Embodiments include a random number generation entity having at least one switching cell comprising a pair of electrodes and a chalcogenide layer arranged between the pair of electrodes and a pulse generating entity coupled with the electrodes of the switching cell. The pulse generating entity is configured to provide an excitation pulse to the switching cell. The random number generation entity also includes a detection entity configured to provide a detection signal indicating whether an electrical property measured at the switching cell exceeds or falls below a threshold value due to applying the excitation pulse to the switching cell and a random number generation entity adapted to generate a random number based on the detection signal of the detection entity.

Random number generation using threshold switching mechanism

A system, method and computer program product for achieving a collective task. The system comprises a plurality of elements representative of a first hierarchy level, each element comprises a plurality of sub-elements. The system comprises also an arbitration module for selecting one of the sub-elements of each element at a point in time based on a global clock, wherein each sub-element relates to one list element of an ordered circular list, and a combination module adapted for a combination of sub-actions performed by a portion of the sub-elements of one of the elements over a predefined period of time, wherein each sub-element performs one of the sub-actions.

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Zurich, Switzerland

Manuel Le Gallo