Generalized Dot Product Circuit for Computer Vision
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Solution Overview
Problem
Conventional computer vision systems are inefficient due to separate operations for dot product, matrix multiplication, and other array operations, which hinders their performance in applications requiring generalized dot product calculations.
Innovation Solution
A hardware implementation that uses a local buffer to reduce bandwidth, upconverts arrays to match dimensions, performs matrix multiplication, and enables multi-dimensional generalized dot-product operations, allowing operands to be represented as dense or sparse arrays, and is suitable for integration into camera systems or integrated circuits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If separate operations are implemented for dot product, matrix multiplication, and other array operations, then each operation can be optimized independently, but the overall system complexity increases and efficiency decreases
Solution Approach 1:
The patent combines multiple separate array operations (dot product, matrix multiplication, and other array operations) into a single unified generalized dot product operation. This merging eliminates the need for separate operation implementations, reducing system complexity while maintaining or improving overall operation efficiency through a consolidated processing framework.
Solution Approach 2:
The generalized dot product operation serves multiple functions simultaneously, handling dot products, matrix multiplications, and other array operations through a single universal mechanism. This multi-functionality allows the system to perform diverse operations without requiring separate specialized operations, thereby reducing complexity while enhancing productivity.
2Adaptability or versatility
If a unified generalized dot product operation is implemented, then system complexity is reduced and versatility is improved, but bandwidth requirements may increase
Solution Approach 1:
The unified generalized dot product operation is implemented with segmentation that processes data in a structured manner, dividing the computation into manageable stages that optimize data flow and reduce redundant bandwidth consumption while maintaining versatility across different operation types.
Data Source
AI summary
An apparatus includes a memory and a circuit coupled to the memory. The memory may be configured as a local buffer to store all or a portion of a first array of values and all or a portion of a second array of values. The circuit may be configured to (i) calculate an intermediate array of values by multiplying a converted version of the first array by a converted version of the second array and (ii) calculate an output array comprising a plurality of output values based on values of the intermediate array and a predefined dimensional reduction.