Variable-Length Instruction Encoding Using Predictive Word Masks
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Solution Overview
Problem
Existing methods for encoding and decoding instructions from an instruction set face challenges in achieving high code density and flexibility, particularly when using variable length instruction words, which can increase hardware complexity and make it difficult to add new instructions without reducing code density and efficiency.
Innovation Solution
The method involves re-ordering and grouping bits in instructions into variable-length instruction words based on empirical or simulation data, omitting words that match predicted values to create a compressed version, allowing for different instructions to use different numbers of words, and using a mask to selectively remove words, thereby improving code density and flexibility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If variable length instruction words are used to increase code density, then code density is improved, but hardware complexity increases
Solution Approach 1:
The instruction is divided into multiple fixed-length words (e.g., 32-bit words) that can be selectively omitted. Instead of using truly variable-length encoding, the patent segments the instruction into fixed-size units and uses a compact representation that indicates which segments are present, thereby reducing hardware complexity while maintaining code density improvements.
Solution Approach 2:
The patent uses a partial action approach by selectively omitting certain instruction words based on a compact mask or encoding scheme. Not all possible words are included in every instruction, allowing the hardware to process only the necessary portions, which reduces the complexity of handling fully variable-length instructions while still achieving compression.
2Quantity of substance
If variable length instruction words are used to improve code density, then code density is improved, but difficulty in adding new instructions increases
Solution Approach 1:
By segmenting instructions into fixed-length words with a systematic encoding scheme, the patent creates a modular structure that makes it easier to add new instructions. New instructions can be constructed by combining different segments or modifying existing ones without requiring complete redesign of the variable-length encoding system.
Solution Approach 2:
The encoding scheme is designed to be universal, supporting both common and less common instructions through the same mechanism. The compact representation and selective omission approach works for all instruction types, providing a unified framework that facilitates adding new instructions without creating special cases.
3Quantity of substance
If shorter instruction words are used to increase code density, then code density is improved, but functionality of the instruction set is limited
Solution Approach 1:
The patent uses segmentation to overcome the functionality limitation of short instruction words. By dividing instructions into multiple fixed-length segments, the system can represent complex functionality across multiple segments while maintaining compact individual word sizes. This allows the instruction set to retain full functionality without requiring each individual word to be long.
Data Source
AI summary
Methods of encoding and decoding are described which use a variable number of instruction words to encode instructions from an instruction set, such that different instructions within the instruction set may be encoded using different numbers of instruction words. To encode an instruction, the bits within the instruction are re-ordered and formed into instruction words based upon their variance as determined using empirical or simulation data. The bits in the instruction words are compared to corresponding predicted values and some or all of the instruction words that match the predicted values are omitted from the encoded instruction.