Cache Block Precision Hints for Lower-Power Memory Access
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Solution Overview
Problem
Conventional computing systems inefficiently transfer and process data in uniform high-precision formats, leading to increased power consumption, reduced bandwidth, and computational delays, as they assume all data requires the same precision without considering the actual needs of computational tasks.
Innovation Solution
Implement data-driven precision techniques that allow processors to hint at runtime about the required precision of data, enabling system components to transfer and process data in lower-precision formats with minimal accuracy loss, thus optimizing compute throughput and reducing data movement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If data is stored and transferred in uniform high-precision formats, then measurement precision is maintained, but use of energy increases and productivity decreases
Solution Approach 1:
The patent applies local quality by allowing different data elements within the same dataset to be stored and transferred in different precision formats based on their individual requirements. Instead of uniformly applying high precision to all data, the system dynamically determines the appropriate precision level for each data element, thereby reducing overall power consumption while maintaining necessary measurement precision where required.
Solution Approach 2:
The patent implements parameter changes by dynamically adjusting the precision parameter of data representations based on computational context and requirements. The system can switch between different precision levels (e.g., full precision, reduced precision, compressed precision) for different data elements, allowing optimization of power consumption without permanently sacrificing measurement precision when high precision is actually needed for computational accuracy.
2Measurement precision
If data is stored and transferred in uniform high-precision formats, then measurement precision is maintained, but bandwidth usage increases
Solution Approach 1:
The patent applies local quality by enabling different precision formats for different data elements based on their specific requirements. This allows the system to transmit only the necessary amount of data for each element, reducing overall bandwidth consumption while maintaining measurement precision for data elements that require it.
Solution Approach 2:
The patent implements parameter changes by dynamically adjusting the precision parameter during data transmission. The system can change the representation format of data (e.g., from full precision to reduced precision) based on contextual information, thereby optimizing bandwidth usage without permanently degrading measurement precision when high precision is computationally required.
3Measurement precision
If data is processed in uniform high-precision formats, then measurement precision is maintained, but productivity decreases
Solution Approach 1:
The patent applies local quality by allowing different computational operations to use different precision levels based on their specific requirements. Critical computations that require high accuracy use full precision, while less critical operations can use reduced precision formats, thereby increasing overall compute throughput while maintaining computational accuracy where necessary.
Solution Approach 2:
The patent implements parameter changes by dynamically adjusting the precision parameter during computational processing. The system can switch between different precision levels for different data elements and computational operations, allowing higher productivity through the use of lower-precision formats for operations that don't require full precision, while maintaining computational accuracy for operations that do require it.
4Use of energy by moving object
If data is transferred in lower-precision formats, then power consumption decreases and productivity increases, but measurement precision is lost
Solution Approach 1:
The patent implements parameter changes by dynamically adjusting the precision parameter based on computational context. The system can switch between different precision levels (full precision, reduced precision, compressed precision) for different data elements and operations, allowing power consumption to be reduced when lower precision is acceptable, while maintaining data accuracy when high precision is computationally required.
Solution Approach 2:
The patent applies dynamics by making the precision level of data representations flexible and adaptable rather than static. The system can dynamically change the precision format of data during storage, transfer, and processing based on contextual requirements, allowing optimization of power consumption without permanently sacrificing data accuracy when needed for computational correctness.
Data Source
AI summary
Systems and techniques for data-driven precision memory access of cache block data are described. Computing system components are informed as to instances where access operations involve deducing a necessary precision of the data format and expressing the requested data in a lower-precision data format with minimal to no accuracy loss. In one example, executable code for a computational task includes hints that identify when memory requests involve accessing data in a numeric data format based on a deduced precision of the stored data during memory access. The described techniques thus overcome conventional drawbacks facing systems that transmit and compute data in a higher-precision data format than required by the stored values.