Memory Interpolation Accelerator for Data Transfer Reduction
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Solution Overview
Problem
Current computer architectures face challenges in efficiently transferring data between processors and memory, leading to performance constraints and high energy consumption, particularly in compute-intensive operations like linear interpolation.
Innovation Solution
The implementation of a memory-compute system (CNM) that performs interpolation within the memory system, reducing data transfer by accessing and interpolating values directly within the memory, rather than relying on the processor to retrieve and interpolate data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If data is transferred between processor and memory for interpolation operations, then processing capability is maintained, but energy consumption increases and performance is constrained
Solution Approach 1:
The patent merges the memory system and processing capabilities by integrating an interpolation accelerator directly within the memory device. This allows interpolation operations to be performed at the memory location rather than requiring data transfer to an external processor, thereby reducing energy consumption while maintaining processing performance. The memory device itself becomes both storage and computation unit.
Solution Approach 2:
The patent introduces an interpolation accelerator as an intermediary component between the processor and memory system. This accelerator handles interpolation operations locally at the memory interface, reducing the need for full data transfers between processor and memory while maintaining the ability to perform compute-intensive operations efficiently.
2Speed
If data is transferred between processor and memory, then processing operations can be performed, but transfer time increases and performance is constrained
Solution Approach 1:
By integrating the interpolation accelerator within the memory device, the patent eliminates the need for separate data transfer and processing steps. The memory system becomes a unified compute-storage unit that can perform interpolation operations on data while it resides in memory, significantly reducing the time required compared to traditional transfer-then-process workflows.
Solution Approach 2:
The interpolation accelerator performs computations on data while it is already located in the memory system, before any potential transfer to external processors would occur. This preliminary computation at the memory location avoids the time penalty of transferring data back and forth between memory and processor for interpolation operations.
3Measurement precision
If processor retrieves and interpolates data from memory, then computation accuracy is maintained, but data transfer volume increases
Solution Approach 1:
The patent extracts the interpolation computation function from the external processor and places it directly within the memory device. This allows the memory system to perform interpolation operations locally using only the data already present in memory, eliminating the need to transfer additional data to external processors while maintaining full computational accuracy through the dedicated interpolation accelerator.
Data Source
AI summary
Linear interpolation is performed within a memory system. The memory system receives a floating-point point index into an integer-indexed memory array. The memory system accesses the two values of the two adjacent integer indices, performs the linear interpolation, and provides the resulting interpolated value. In many system architectures, the critical limitation on system performance is the data transfer rate between memory and processing elements. Accordingly, reducing the amount of data transferred improves overall system performance and reduces power consumption.