Analog Devices,inc.

William Bradley

Jeffrey G Bernstein

Benjamin Vigoda

Alexander Alexeyev

David C Reynolds

Eric G Nestler

Vladimir Zlatkovic

Jeffrey Venuti

Shawn Hershey

Theophane Weber

Circuitry for stochastic computation includes processing nodes, including a first processing node and a second processing node, each configured to process an outcome stream having a plurality of outcomes, each outcome being in one of a plurality of states, wherein an outcome from said outcome stream is in a particular state with a particular probability; communication links configured to transmit outcome streams between pairs of said processing nodes; and a delay module on each of said communication links, said delay module configured to delay outcome streams traversing said communication link by an assigned delay; wherein said first and second processing nodes are connected by a plurality of data paths, at least one of which comprises a plurality of communication links, each of said data paths causing an aggregate delay to an outcome stream traversing said data path; wherein no two aggregate delays impose the same delay on an outcome stream.

Selective delay of data receipt in stochastic computation

A storage device includes a storage array having a group of storage elements. Each storage element can written to a discrete set of physical states. A read circuit selects one or more storage elements and generates, for each selected storage element, an analog signal representative of the physical state of the selected storage element. A signal processing circuit processes the analog signal to generate a plurality of outputs, with each output representing a degree of an association of the selected storage element with a different subset of one or more of the discrete set of physical states.

Storage devices with soft processing

A processor implements a network of functional nodes and communication paths between the nodes. The processor includes a plurality of circuit implementations of the functional nodes of the processor; and a plurality of signal paths implementing the communication paths linking the circuit implementations of the nodes. At least some of the signal paths are configured to pass signal values represented according to temporal patterns of signal levels on the signal paths. The processor also includes a plurality of circuit components for conversion between a signal value represented as a signal level (e.g., voltage or current level) and a signal value represented as a temporal pattern.

Mixed signal stochastic belief propagation

Some general aspects relate to systems and methods of analog computation using numerical representation with uncertainty. For example, a specification of a group of variables is accepted, with each variable having a set of at least N possible values. The group of variables satisfies a set of one or more constraints, and each variable is specified as a decomposition into a group of constituents, with each constituent having a set of M (e.g., M&#x3c;N) possible constituent values that can be determined based on the variable values. The method also includes forming a specification for configuring a computing device that implements a network representation of the constraints based on the specification of the group of variables. The network representation includes a first set of nodes corresponding to the groups of constituents, a second set of nodes corresponding to the set of constraints, and interconnections between the first and the second sets of nodes for passing continuous-valued data.

Analog computation using numerical representations with uncertainty

An approach to converting an analog value based on a partition of an input range produces probabilities that the input is found within each of the regions based, for example, on a noisy version of the input. In some examples, iterative and/or pipelined application of comparison circuitry is used to accumulate a set of analog representations of the output probabilities. The circuitry can be adapted or configured according to the characteristics of the degradation (e.g., according to the variance of an additive noise) and/or prior information about the distribution of the clean input (e.g., a distribution over a discrete set of exemplar values, uniformly distributed etc.).

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Somerville, MA, United States of America

William Bradley