Abstract:
A method performs XNOR-equivalent operations by adjusting column thresholds of a compute-in-memory array of an artificial neural network. The method includes adjusting an activation threshold generated for each column of the compute-in-memory array based on a function of a weight value and an activation value. The method also includes calculating a conversion bias current reference based on an input value from an input vector to the compute-in-memory array, the compute-in-memory array being programmed with a set of weights. The adjusted activation threshold and the conversion bias current reference are used as a threshold for determining the output values of the compute-in-memory array.
Abstract:
A method of forming fins of different materials includes providing a substrate with a layer of a first material having a top surface, masking a first portion of the substrate leaving a second portion of the substrate exposed, etching a first opening at the second portion, forming a body of a second material in the opening to a level of the top surface of the layer of the first material, removing the mask, and forming fins of the first material at the first portion and forming fins of the second material at the second portion. A finFET device having fins formed of at least two different materials is also disclosed.
Abstract:
An OTP memory array includes a plurality of differential P-channel metal oxide semiconductor (PMOS) OTP memory cells programmable and readable in predetermined states of program and read operations, and is capable of providing sufficient margins against global process variations and temperature variations while being compatible with standard logic fin-shaped field effect transistor (FinFET) processes to obviate the need for additional masks and costs associated with additional masks.
Abstract:
Non-volatile memory devices and logic devices are fabricated using processes compatible with high dielectric constant/metal gate (HK/MG) processes for increased cell density and larger scale integration. A doped oxide layer, such as a silicon-doped hafnium oxide (HfO2) layer, is implemented as a ferroelectric dipole layer in a non-volatile memory device
Abstract:
Methods for fabricating devices on a die, and devices on a die. A method may include patterning a first region to create a first gate having a first gate length and a first contacted polysilicon pitch (CPP) with a first process. The first CPP is smaller than a single pattern lithographic limit. The method also includes patterning the first region to create a second gate having a second gate length or a second CPP with a second process. The second CPP is smaller than the single pattern lithographic limit. The second gate length is different than the first gate length.
Abstract:
An integrated circuit (IC) is described. The IC includes a first die having a first semiconductor layer, a first active device layer and a first back-end-of-line (BEOL) layer. The IC also includes a second die having a second semiconductor layer, a second active device layer and a second back-end-of-line (BEOL) layer, and on the first die. The IC further includes a through substrate via (TSV) extending through the first die and the second die.
Abstract:
Certain aspects generally relate to performing machine learning tasks, and in particular, to computation-in-memory architectures and operations. One aspect provides a circuit for in-memory computation. The circuit generally includes multiple bit-lines, multiple word-lines, an array of compute-in-memory cells, and a plurality of accumulators, each accumulator being coupled to a respective one of the multiple bit-lines. Each compute-in-memory cell is coupled to one of the bit-lines and to one of the word-lines and is configured to store a weight bit of a neural network.
Abstract:
Certain aspects provide an apparatus for performing machine learning tasks, and in particular, to computation-in-memory architectures. One aspect provides a circuit for in-memory computation. The circuit generally includes: a plurality of memory cells on each of multiple columns of a memory, the plurality of memory cells being configured to store multiple bits representing weights of a neural network, wherein the plurality of memory cells on each of the multiple columns are on different word-lines of the memory; multiple addition circuits, each coupled to a respective one of the multiple columns; a first adder circuit coupled to outputs of at least two of the multiple addition circuits; and an accumulator coupled to an output of the first adder circuit.
Abstract:
Certain aspects of the present disclosure provide a circuit for in-memory computation. The circuit generally includes a memory cell having a bit-line and a complementary bit-line, a first capacitive element coupled to the bit-line, a second capacitive element coupled to the complementary bit-line, a processing circuit, a first switch coupled between a first input of the processing circuit and the bit-line, and a second switch coupled between a second input of the processing circuit and the complementary bit-line
Abstract:
Aspects generally relate to a complimentary MOS capacitor with improved linearity. A complimentary MOS capacitor includes an n-type MOS capacitor and a p-type MOS capacitor coupled in parallel. The p-type MOS capacitor biased to an opposite voltage polarity of the n-type MOS capacitor.