Instruction Encoding With Predictive Word Omission for Code Density
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Solution Overview
Problem
Existing encoding and decoding methods for instruction sets face challenges in achieving high code density while maintaining flexibility and reducing hardware complexity, particularly when adding new instructions or handling variable length instructions, which can lead to inefficiencies and errors.
Innovation Solution
A method that rearranges instruction bits into a variable number of fixed-length or multiple of fixed-length words, truncating or masking words with predictable values to achieve compression, and uses empirical data and simulation to determine mappings and predicted values for efficient encoding and decoding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If variable length instruction words are used to increase code density, then memory requirements are reduced, but hardware complexity increases due to the need to handle different field omissions and identifier interpretations
Solution Approach 1:
The instruction word is segmented into fixed fields with predetermined bit lengths, where each field has a specific function. By dividing the instruction into structured segments (opcode, operand fields, etc.), the decoder can systematically process each segment without requiring complex variable-length field parsing logic, thus reducing hardware complexity while maintaining compression efficiency.
Solution Approach 2:
The patent changes the parameter of instruction word length from variable to fixed, while achieving compression through selective field omission rather than variable word length. This parameter change simplifies the hardware decoder design as it no longer needs to dynamically determine field boundaries based on variable lengths, while still achieving code density improvement through the identifier mechanism.
2Quantity of substance
If fields are omitted from instructions to compress bit length, then code density increases, but reliability decreases due to potential errors in identifying omitted fields
Solution Approach 1:
The identifier field provides feedback information to the decoder about which fields are omitted. This feedback mechanism allows the decoder to accurately reconstruct the original instruction structure by knowing exactly which fields should be present and which are omitted, thereby maintaining high decoding reliability while achieving compression through field omission.
Solution Approach 2:
The identifier acts as an intermediary between the encoded instruction and the decoder. It carries metadata information about the instruction structure (which fields are omitted) without being part of the operational instruction itself. This intermediary enables the decoder to correctly interpret the compressed instruction format and reliably reconstruct the intended operation.
3Adaptability or versatility
If manual generation of encoding/decoding software and hardware is performed, then adaptability to processor variants is improved, but time consumption and error probability increase
Solution Approach 1:
The patent employs automated generation tools that self-generate the encoding software and decoding hardware descriptions from processor architecture specifications. This self-service approach eliminates the need for manual, error-prone generation processes while maintaining full adaptability to different processor variants. The automated tools can systematically generate correct and consistent encoding/decoding implementations for any processor variant by interpreting the architectural specifications.
Solution Approach 2:
The patent replaces the mechanical/manual process of generating encoding and decoding implementations with an automated computational system. Instead of manually writing and debugging encoder/decoder code for each processor variant, the system uses automated generation tools that computationally produce the correct implementations, significantly reducing development time and error probability while maintaining adaptability.
Data Source
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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.