System and methods for mixed -signal computing

Abstract

Systems and methods of implementing a mixed-signal integrated circuit includes sourcing, by a reference signal source, a plurality of analog reference signals along a shared signal communication path to a plurality of local accumulators; producing an electrical charge, at each of the plurality of local accumulators, based on each of the plurality of analog reference signals; adding or subtracting, by each of the plurality of local accumulators, the electrical charge to an energy storage device of each of the plurality of local accumulators over a predetermined period; summing along the shared communication path the electrical charge from the energy storage device of each of the plurality of local accumulators at an end of the predetermined period; and generating an output based on a sum of the electrical charge from each of the plurality of local accumulators.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS[0001]This application claims the benefit of U.S. Provisional Application No. 62 / 559,354, filed 15 Sep. 2017, which is incorporated in its entirety by this reference.TECHNICAL FIELD[0002]The inventions herein relate generally to the integrated circuitry architecture field, and more specifically to new and useful mixed-signal integrated circuits and methods of computing mixed-signals in the integrated circuitry architecture field.BACKGROUND[0003]Today, the various implementations of artificial intelligence are driving innovation in many fields of technology. Artificial intelligence (AI) systems and artificial intelligence models (including algorithms) are defined by many system architectures and models that enable machine learning (deep learning), reasoning, inferential capacities, and large data processing capabilities of a machine (e.g., a computer and / or a computing server). These AI systems and models are often trained intensively to perform...

AI Technical Summary

Benefits of technology

The patent describes a mixed-signal integrated circuit that includes a reference signal source and a plurality of local signal accumulators. The reference signal source generates a plurality of analog reference signals based on a digital input and distributes them to the local signal accumulators. The local signal accumulators collect the analog reference signals and store them as a sum of electrical charges over a predetermined number of clock cycles. The circuit also includes programmable current sources and amplifiers to control the amount of electrical charges. The technical effect of this circuit is to provide a more efficient and accurate reference signal for a neural network implementation.

Problems solved by technology

Still, while neural network models or algorithms may not require a same amount of compute resources, as required in a training phase, deploying a neural network model or algorithm in the field continues to require significant circuitry area, energy, and compute power to classify data and infer or predict a result.

However, latency problems are manifest when these remote artificial intelligence processing systems are used in computing inferences and the like for remote, edge computing devices or in field devices.

That is, when these traditional remote systems seek to implement a neural network model for generating inferences to be used in remote field devices, there are unavoidable delays in receiving input data from the remote field devices because the input data must often be transmitted over a network with varying bandwidth and subsequently, inferences generated by the remote computing system must be transmitted back to the remote field devices via a same or similar network.

However, attempts to implement some of these traditional AI computers and systems at an edge device (e.g. remote field device) may result in a bulky system with many circuits, as mentioned above, that consumes significant amounts of energy due to the required complex architecture of the computing system used in processing data and generating inferences.

Thus, such a proposal without more may not be feasible and / or sustainable with current technology.

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