Switched-Capacitor Matrix Multiplier With Parallel SAR MACs
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Solution Overview
Problem
Current computational methods for matrix multiplication, particularly in machine learning applications, are limited by high computational complexity and power inefficiency due to serial computations and limited memory bandwidth.
Innovation Solution
A switched capacitor matrix multiplier is developed, utilizing successive approximation registers (SAR) operating in parallel, with Analog Multiply-and-Accumulate (MAC) units for bit-wise multiplication and accumulation, and a comparator and state machine for control, which performs matrix multiplication with reduced power consumption and increased efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If serial computations are used on general-purpose CPUs, then implementation simplicity is maintained, but throughput and power efficiency are limited
Solution Approach 1:
The matrix multiplication operation is segmented into multiple parallel MAC units, each handling specific elements of the computation. This segmentation enables simultaneous execution of multiple operations, dramatically increasing throughput while maintaining manageable complexity through modular design
Solution Approach 2:
The patent transitions from serial time-based computation to parallel spatial computation by introducing multiple MAC units operating simultaneously. This dimensional shift from one-dimensional sequential processing to two-dimensional parallel processing architecture enables exponential throughput improvement
2Use of energy by moving object
If digital domain computations are performed, then precision is maintained, but power consumption increases due to data communication requirements
Solution Approach 1:
Analog signals serve as intermediaries between weight storage and accumulation operations. By performing multiply-accumulate operations in the analog domain using capacitor charges, the system eliminates power-intensive digital data communication while maintaining computational precision through controlled analog processing
Solution Approach 2:
The patent replaces digital electronic computation with analog capacitor-based computation. Electrical charges on capacitors represent numerical values, and arithmetic operations are performed through physical charge accumulation and redistribution, dramatically reducing power consumption compared to digital switching operations
3Productivity
If memory bandwidth is limited, then system simplicity is maintained, but maximum throughput is constrained
Solution Approach 1:
The patent merges memory storage and computation functions by implementing weight storage locally within or near each MAC unit. This fusion of storage and processing eliminates the need for high-bandwidth external memory interfaces, enabling high throughput through local parallel access while reducing overall system complexity
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The switched capacitor matrix multiplier achieves significant power efficiency and throughput by performing multiply-and-accumulate operations in the analog domain and storing weights locally, thereby reducing the need for power-intensive data communication and enhancing computational efficiency.
Implementation Method 1
the comparator compares a reference voltage Via to an output voltage of the plurality of MAC circuits
Implementation Method 2
the bit-wise multiplication of a digital weight matrix with a digital input vector is performed by the successive approximation registers (SAR) using only the successive approximation register (SAR) capacitors
Data Source
AI summary
Methods and apparatuses enable a general-purpose low power analog vector-matrix multiplier. A switched capacitor matrix multiplier may comprise a plurality of successive approximate registers (SAR) operating in parallel, each SAR having a SAR digital output; and a plurality of Analog Multiply-and-Accumulate (MAC) units for multiplying and accumulating and scaling bit-wise products of a digital weight matrix with a digital input vector, wherein each MAC unit is connected in series to a SAR of the plurality of SARs.