Analog MAC Input Encoding for Lower DAC Energy Use
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Solution Overview
Problem
Existing analog accelerators for multiplication and accumulation computations are energy-intensive, particularly during digital to analog conversions, and energy expenditure varies with input magnitude, leading to inefficiencies in deep learning applications.
Innovation Solution
The implementation of an energy usage optimizer that transforms input parameters to adjust their magnitude, using techniques such as bitwise shifting and signal amplification, to reduce energy expenditure in analog accelerators, while maintaining computational accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If analog accelerators are used to accelerate multiplication and accumulation computations, then computational speed is improved, but energy consumption increases
Solution Approach 1:
The patent transforms input parameters by adjusting their magnitude (scaling) before processing in the analog accelerator. By changing the parameter range of inputs, the system optimizes energy consumption while maintaining computational speed. The transformation unit scales input values to match optimal ranges for the analog computing elements, reducing energy expenditure during multiplication and accumulation operations.
2Measurement precision
If input magnitude is increased to improve signal quality, then computational accuracy is improved, but energy consumption increases
Solution Approach 1:
The system dynamically adjusts input parameter magnitudes to optimal ranges that balance signal quality and energy consumption. Rather than always using high magnitudes for signal quality, the transformation unit scales inputs to match the optimal operating range of the analog accelerator, achieving good computational accuracy with reduced energy expenditure.
Solution Approach 2:
The patent implements a feedback mechanism where the system monitors computational results and adjusts input transformations accordingly. The transformation unit uses feedback from computational outcomes to optimize subsequent input scaling, maintaining accuracy while minimizing energy consumption through adaptive parameter adjustment.
3Speed
If digital to analog conversion is performed to enable analog computation, then computational acceleration is achieved, but energy consumption increases
Solution Approach 1:
The system performs preliminary transformation of input parameters to digital representations optimized for analog conversion before the actual digital-to-analog conversion process. By pre-processing inputs to match optimal conversion ranges, the system reduces the energy required for DAC operations while maintaining the computational acceleration benefits of analog processing.
Data Source
AI summary
A device having: memory cells configured to store a set of first parameters as an input for an operation of multiplication and accumulation; digital to analog converters; an analog section of the operation of multiplication and accumulation; analog to digital converters; and a controller configured to analyze the set of first parameters to identify an encoding parameter for reduced energy consumption in processing the input. The device generates, using the digital to analog converters and according to the set of first parameters, analog inputs to the analog section of the operation of multiplication and accumulation. The analog section generates analog outputs responsive to the analog input. The device determines, using the analog to digital converters and according to the encoding parameter and the analog outputs, a set of second parameters as an output responsive to the input for the operation of multiplication and accumulation.