Abstract:
A neuromorphic multi-bit digital weight cell configured to store a series of potential weights for a neuron in an artificial neural network. The neuromorphic multi-bit digital weight cell includes a parallel cell including a series of passive resistors in parallel and a series of gating transistors. Each gating transistor of the series of gating transistors is in series with one passive resistor of the series of passive resistors. The neuromorphic cell also includes a series of programming input lines connected to the series of gating transistors, an input terminal connected to the parallel cell, and an output terminal connected to the parallel cell.
Abstract:
A weight cell and device are herein disclosed. The weight cell includes a first field effect transistor (FET) and a first resistive memory element connected to a drain of the first FET, a second FET and a second resistive memory element connected to a drain of the second FET, the drain of the first FET being connected to a gate of the second FET and the drain of the second FET is connected to a gate of the first FET, a third FET and a third resistive memory element connected to a drain of the third FET, and a fourth FET and a fourth resistive memory element connected to a drain of the fourth FET, the drain of the third FET is connected to a gate of the fourth FET and the drain of the fourth FET being connected to a gate of the third FET.
Abstract:
A circuit element. In some embodiments, the circuit element includes a first terminal, a second terminal, and a layered structure. The layered structure may include a first conductive layer connected to the first terminal, a first piezoelectric layer on the first conductive layer, a second piezoelectric layer on the first piezoelectric layer, and a second conductive layer connected to the second terminal. The first piezoelectric layer may have a first piezoelectric tensor and a first permittivity tensor, and the second piezoelectric layer may have a second piezoelectric tensor and a second permittivity tensor, one or both of the second piezoelectric tensor and a second permittivity tensor differing, respectively, from the first piezoelectric tensor and the first permittivity tensor.
Abstract:
A hardware cell and method for performing a digital XNOR of an input signal and weights are described. The hardware cell includes input lines, a plurality of pairs of magnetic junctions, output transistors and at least one selection transistor coupled with the output transistors. The input lines receive the input signal and its complement. The magnetic junctions store the weight. Each magnetic junction includes a reference layer, a free layer and a nonmagnetic spacer layer between the reference layer and the free layer. The free layer has stable magnetic states and is programmable using spin-transfer torque and/or spin-orbit interaction torque. The first magnetic junction of a pair receives the input signal. The second magnetic junction of the pair receives the input signal complement. The output transistors are coupled with the magnetic junctions such that each pair of magnetic junctions forms a voltage divider. The output transistors form a sense amplifier.
Abstract:
A system of unipolar digital logic. Ferroelectric field effect transistors having channels of a first polarity, are combined, in circuits, with simple field effect transistors having channels of the same polarity, to form logic gates and/or memory cells.
Abstract:
Integrated circuit devices including strained channel regions and methods of forming the same are provided. The integrated circuit devices may include enhancement-mode field effect transistors. The enhancement-mode field effect transistors may include a quantum well channel region having a well thickness Tw sufficient to yield a strain-induced splitting of a plurality of equivalent-type electron conduction states therein to respective unequal energy levels including a lowermost energy level associated with a lowermost surface roughness scattering adjacent a surface of the channel region when, the surface is biased into a state of inversion.
Abstract:
A neuromorphic multi-bit digital weight cell configured to store a series of potential weights for a neuron in an artificial neural network. The neuromorphic multi-bit digital weight cell includes a parallel cell including a series of passive resistors in parallel and a series of gating transistors. Each gating transistor of the series of gating transistors is in series with one passive resistor of the series of passive resistors. The neuromorphic cell also includes a series of programming input lines connected to the series of gating transistors, an input terminal connected to the parallel cell, and an output terminal connected to the parallel cell.
Abstract:
A neuromorphic multi-bit digital weight cell configured to store a series of potential weights for a neuron in an artificial neural network. The neuromorphic multi-bit digital weight cell includes a parallel cell including a series of passive resistors in parallel and a series of gating transistors. Each gating transistor of the series of gating transistors is in series with one passive resistor of the series of passive resistors. The neuromorphic cell also includes a series of programming input lines connected to the series of gating transistors, an input terminal connected to the parallel cell, and an output terminal connected to the parallel cell.
Abstract:
A hardware cell and method for performing a digital XNOR of an input signal and weights are described. The hardware cell includes input lines, a plurality of pairs of magnetic junctions, output transistors and at least one selection transistor coupled with the output transistors. The input lines receive the input signal and its complement. The magnetic junctions store the weight. Each magnetic junction includes a reference layer, a free layer and a nonmagnetic spacer layer between the reference layer and the free layer. The free layer has stable magnetic states and is programmable using spin-transfer torque and/or spin-orbit interaction torque. The first magnetic junction of a pair receives the input signal. The second magnetic junction of the pair receives the input signal complement. The output transistors are coupled with the magnetic junctions such that each pair of magnetic junctions forms a voltage divider. The output transistors form a sense amplifier.
Abstract:
A circuit element. In some embodiments, the circuit element includes a first terminal, a second terminal, and a layered structure. The layered structure may include a first conductive layer connected to the first terminal, a first piezoelectric layer on the first conductive layer, a second piezoelectric layer on the first piezoelectric layer, and a second conductive layer connected to the second terminal. The first piezoelectric layer may have a first piezoelectric tensor and a first permittivity tensor, and the second piezoelectric layer may have a second piezoelectric tensor and a second permittivity tensor, one or both of the second piezoelectric tensor and a second permittivity tensor differing, respectively, from the first piezoelectric tensor and the first permittivity tensor.