Bit String Lookup Data Structure for Computing Tile Memory Efficiency
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Solution Overview
Problem
Current computing systems face limitations in memory efficiency and performance due to the finite memory resources available for storing operands, particularly when using the floating-point format, which can lead to increased processing time and power consumption during arithmetic and logical operations.
Innovation Solution
The implementation of a bit string lookup data structure using a computing tile architecture that converts bit strings between formats, such as floating-point and posit formats, allowing for improved precision, accuracy, and reduced storage requirements, enabling faster operations and reduced clock cycles through the use of posit bit strings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If floating-point format is used for storing operands, then compatibility and ease of operation are improved, but memory efficiency deteriorates and processing time increases
Solution Approach 1:
The patent creates a lookup table that stores pre-computed results of arithmetic and logical operations. Instead of performing operations in real-time using floating-point arithmetic, the system copies the result directly from the lookup table based on the operands, dramatically reducing processing time while maintaining accuracy.
Solution Approach 2:
The patent pre-computes and stores all possible operation results in a lookup table before actual computation is needed. By preparing the results in advance and organizing them by operand patterns, the system eliminates the need for time-consuming floating-point operations during actual computation.
2Ease of operation
If floating-point format is used for storing operands, then compatibility and ease of operation are improved, but memory efficiency deteriorates
Solution Approach 1:
The patent uses a compact lookup table that stores only the essential result information rather than full floating-point operands. This copying approach stores results in a space-efficient format that requires fewer memory resources compared to storing complete floating-point numbers.
Solution Approach 2:
The patent extracts only the necessary information from floating-point operations and stores it in a condensed format in the lookup table. By taking out only the essential result data and organizing it efficiently, the system achieves better memory efficiency while maintaining operational ease.
3Measurement precision
If higher precision is achieved using floating-point format, then accuracy is improved, but memory requirements increase and overflow/underflow issues occur
Solution Approach 1:
The patent copies pre-computed high-precision results from the lookup table directly to the output, achieving high accuracy without requiring large memory buffers for intermediate calculations. The lookup table stores results in a compact format that avoids the memory overhead of traditional high-precision floating-point storage.
4Productivity
If lookup table is implemented, then processing speed is improved, but device complexity increases
Solution Approach 1:
The patent segments the lookup table into multiple smaller tables organized by different operation types and operand patterns. This segmentation reduces the complexity of any single lookup table while maintaining the overall processing speed advantage, as the system can quickly determine which segment to query based on the operation being performed.
Data Source
AI summary
Systems, apparatuses, and methods related to bit string operations using a computing tile are described. An example apparatus includes computing device (or “tile”) that includes a processing unit and a memory resource configured as a cache for the processing unit. A data structure can be coupled to the computing device. The data structure can be configured to receive a bit string that represents a result of an arithmetic operation, a logical operation, or both and store the bit string that represents the result of the arithmetic operation, the logical operation, or both. The bit string can be formatted in a format different than a floating-point format.