Memory Quantization Unit for Neural Network Data Processing
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Solution Overview
Problem
Accessing large volumes of data stored in memory can be a bottleneck in data-intensive applications due to bandwidth limitations between memory devices and computational units, particularly in deep neural networks where processing numerous data sets requires significant hardware resources.
Innovation Solution
Implementing a memory control unit with a quantization unit that reduces the bit length of weight values stored in memory, allowing for efficient communication of quantized data values between memory banks and data requesting units, thereby reducing memory bandwidth requirements and hardware complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If large volumes of data are accessed from memory, then data processing capability is improved, but memory bandwidth requirements increase
Solution Approach 1:
The patent applies parameter changes by converting weight values from high-precision floating-point format to low-precision quantized format (e.g., 8-bit integers). This changes the data representation parameter to reduce the quantity of data that needs to be transferred through memory bandwidth, while maintaining sufficient accuracy for neural network computations.
Solution Approach 2:
The patent segments the data processing pipeline into distinct stages: data loading from memory, quantization processing, and computational operations. By separating the quantization step from the data loading step, the system can load data once in its original format and then quantize it locally, reducing the repeated bandwidth consumption that would occur if full-precision data were loaded for every computation.
2Measurement precision
If weight values are stored in high-precision format in memory, then computational accuracy is improved, but hardware resource utilization increases
Solution Approach 1:
The patent changes the data precision parameter from high-precision floating-point (e.g., 32-bit or 64-bit) to low-precision quantized format (e.g., 8-bit integers). This parameter change reduces the hardware resources required for data storage and processing while maintaining adequate computational accuracy through carefully designed quantization schemes that preserve the essential characteristics of weight values.
Solution Approach 2:
The patent creates a quantized copy of the weight values rather than using the original high-precision values directly. This copy process transforms the data representation to a more efficient format that requires fewer hardware resources, while the quantization algorithm ensures that the copy maintains sufficient accuracy for the computational task at hand.
3Reliability
If full-precision data is transmitted between memory and computational units, then data integrity is maintained, but energy consumption increases
Solution Approach 1:
The patent changes the data transmission parameter by reducing the bit-width of data transmitted between memory and computational units through quantization. This parameter change reduces the volume of data that must be transmitted, thereby reducing energy consumption associated with data movement while maintaining data integrity through proper quantization that preserves essential information.
Solution Approach 2:
The patent performs quantization as a preliminary action before data is used in computational operations. By quantizing data in advance and storing the quantized versions in memory, the system avoids the need to repeatedly transmit and re-quantize full-precision data, thereby reducing cumulative energy consumption while maintaining data integrity through consistent quantization application.
Data Source
AI summary
A memory control unit for handling data stored in a memory device includes a first interface to an interconnection with at least one memory bank; a second interface for communicating with a data requesting unit; and a memory quantization unit. The memory quantization unit is configured to: obtain, via the first interface, a first weight value from the at least one memory bank; quantize the first weight value to generate at least one quantized weight value having a shorter bit length than a bit length of the first weight value; and communicate the at least one quantized weight value to the data requesting unit via the second interface.