International Business Machines Corporation

Seonghoon Woo

Mingu Kang

Seyoung Kim

Eun Kyung Lee

Kyu-hyoun Kim

Matthias Georg Gottwald

Sukjay Chey

An electronic circuit includes word lines; bit lines intersecting the word lines at a plurality of grid points; and resistive processing units located at the grid points. Baseline stochastic pulse input units are coupled to the word lines; differential stochastic pulse input units are coupled to the word lines; and bitline stochastic pulse input units are coupled to the bit lines. Control circuitry coupled to the pulse input units is configured to cause each of the baseline stochastic pulse input units to generate a baseline pulse train using base input data, each of the differential stochastic pulse input units to generate a differential pulse train using differential input data defining differences from the base input data, and each of the bitline stochastic pulse input units to generate a bitline pulse train using bit line input data. Neural network weights can thus be stored in the resistive processing units.

Enabling hierarchical data loading in a resistive processing unit (RPU) array for reduced communication cost

Techniques for performing improved machine learning using decision trees are disclosed. In one example, a system includes a plurality of decision tree structures, and configuration logic operatively coupled to the plurality of decision tree structures. The configuration logic selectively configures the plurality of decision tree structures to form at least one of: one or more combined decision tree structures, wherein a combined decision tree structure comprises multiple interconnected ones of the plurality of decision tree structures; and one or more individual decision tree structures, wherein an individual decision tree structure comprises a single one of the plurality of decision tree structures.

Machine learning accelerator with decision tree interconnects

A system comprises a floating-point computation unit configured to perform a dot-product operation in accordance with a first floating-point value and a second floating-point value, and detection logic operatively coupled to the floating-point computation unit. The detection logic is configured to compute a difference between fixed-point summations of exponent parts of the first floating-point value and the second floating-point value and, based on the computed difference, detect the presence of a condition prior to completion of the dot-product operation by the floating-point computation unit. In response to detection of the presence of the condition, the detection logic is further configured to cause the floating-point computation unit to avoid performing a subset of computations otherwise performed as part of the dot-product operation. Such techniques serve as a predictor that the avoided subset of computations would have resulted in a dot product of the two floating-point values being below a threshold value.

Floating-point computation with threshold prediction for artificial intelligence system

A resistive memory device includes a magnetic tunnel junction structure. The magnetic tunnel junction structure includes a free magnetic layer. The free magnetic layer includes a magnetic material configurable to host topological spin textures to tune a conductance state of the resistive memory device.

Resistive memory device with magnetic layer having topological spin textures for tuning

A mixed-signal logic processor is provided. The mixed-signal logic processor includes a plurality of mixed-signal multiplier branches. Each of the plurality of mixed-signal multiplier branches has a set of branch-dedicated switches and a single branch-dedicated capacitor. The mixed-signal logic further includes a common switch. The common switch is external and common to each of the plurality of mixed-signal multiplier branches. The mixed-signal logic also includes a first shared branch-external capacitor and a second shared branch-external capacitor. The first and the second shared branch-external capacitors are external to and shared by each of the plurality of mixed-signal multiplier branches. Various settings of the set of switches and the common switch enable various modes of the mixed-signal dot product processor.

Mixed-signal dot product processor with single capacitor per multiplier

A differential mixed-signal logic processor is provided. The differential mixed-signal logic processor includes a plurality of mixed-signal multiplier branches for multiplication of an analog value A and a N-bit digital value B. Each of the plurality of mixed-signal multiplier branches include a first capacitor connected across a second capacitor and a third capacitor to provide a differential output across the second and third capacitors. A capacitance of the first capacitor is equal to half a capacitance of the second and third capacitors.

Differential mixed signal multiplier with three capacitors

A top pinned magnetic tunnel junction (MTJ) stack containing a magnetic pinned layered structure including a second magnetic pinned layer having strong perpendicular magnetic anisotropy (PMA) is provided. In the present application, the magnetic pinned layered structure includes a crystal grain growth controlling layer located between a first magnetic pinned layer having a body centered cubic (BCC) texture and the second magnetic pinned layer. The presence of the crystal grain growth controlling layer facilitates formation of a second magnetic pinned layer having a face centered cubic (FCC) texture or a hexagonal closed packing (HCP) texture which, in turn, promotes strong PMA to the second magnetic pinned layer of the magnetic pinned layered structure.

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New York, NY, United States of America

Seonghoon Woo