Adaptive Matrix Multiplier for Deep Learning Latency
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Solution Overview
Problem
Machine learning applications, particularly deep neural networks, face significant performance bottlenecks due to the high computational requirements of matrix multiplications, which often dominate the running time of these systems.
Innovation Solution
An adaptive matrix multiplier system is designed, comprising multiple multiplying units, memory load circuits, and buffer circuits that enable efficient matrix multiplication by loading data in burst mode and utilizing adder circuits to form and sum products, with the ability to handle various multiplication scenarios such as matrix-matrix, matrix-transpose, and matrix-vector products, and adaptable configurations for optimal performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional matrix multiplication methods are used, then computational accuracy is maintained, but processing time becomes excessively long due to sequential operations
Solution Approach 1:
The matrix multiplication task is divided into multiple independent multiplying units, each handling specific element computations simultaneously. This segmentation enables parallel processing of matrix elements, transforming sequential operations into concurrent operations that complete much faster while maintaining computational accuracy.
Solution Approach 2:
The patent introduces an outer buffer circuit that operates at a higher organizational level, coordinating multiple multiplying units and managing data flow between memory and computation units. This dimensional addition of coordination layers enables efficient resource utilization and reduces latency by optimizing the overall computational architecture.
2Productivity
If multiple multiplying units are added to improve performance, then computational speed increases, but device complexity increases
Solution Approach 1:
Each multiplying unit is designed as a universal module that can perform multiple functions: computing dot products, accumulating results, and interacting with the outer buffer circuit. This multi-functionality reduces the need for specialized dedicated circuits for each operation, thereby managing complexity while maintaining high throughput.
Solution Approach 2:
The outer buffer circuit serves as an intermediary between memory and the multiple multiplying units, coordinating data access and computation. This intermediary layer simplifies the overall architecture by centralizing control logic and data management, making the system more manageable despite having multiple parallel computing units.
3Productivity
If data is loaded sequentially from memory, then memory access simplicity is maintained, but computational efficiency decreases due to data bottlenecks
Solution Approach 1:
The memory load circuit performs preliminary actions by loading data into the outer buffer circuit before the multiplying units need it. This advance data preparation ensures that computation units receive data efficiently without waiting for sequential memory access, thereby reducing computational latency and improving overall processing efficiency.
Solution Approach 2:
The system maintains continuous useful action by keeping the outer buffer circuit and multiplying units continuously engaged in computation. The memory load circuit continuously supplies data to the buffer, ensuring no computational cycles are wasted waiting for data, thus maximizing productivity while minimizing memory access bottlenecks.
Data Source
AI summary
An adaptive matrix multiplier. In some embodiments, the matrix multiplier includes a first multiplying unit a second multiplying unit, a memory load circuit, and an outer buffer circuit. The first multiplying unit includes a first inner buffer circuit and a second inner buffer circuit, and the second multiplying unit includes a first inner buffer circuit and a second inner buffer circuit. The memory load circuit is configured to load data from memory, in a single burst of a burst memory access mode, into the first inner buffer circuit of the first multiplying unit; and into the first inner buffer circuit of the second multiplying unit.