SIMD Character Counting for Variable-Length Encoded Data
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Solution Overview
Problem
Determining the validity and character count in data encoded in variable-length formats, such as CESU-8, is inefficient and resource-intensive, especially when errors may be present due to improper encoding or transmission, and existing techniques like Lemire's are limited to two-byte sequences and do not handle surrogate pairs effectively.
Innovation Solution
Utilizing SIMD techniques with lookup tables to efficiently validate encoded data by analyzing sequences of bytes, identifying errors through combined lookup results, and counting continuation bytes to determine the number of characters, which can handle surrogate pairs and multiple-byte sequences efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If variable-length encoding formats (such as CESU-8) are used to support diverse character sets, then the adaptability and character set coverage are improved, but the complexity of determining character count and validating encoding increases
Solution Approach 1:
The patent segments the encoding validation process into distinct lookup tables for different byte sequence patterns. Each lookup table handles specific encoding scenarios (1-byte, 2-byte, 3-byte, 4-byte sequences), breaking down the complex validation task into manageable, pre-computed segments that can be quickly referenced without full decoding.
Solution Approach 2:
The patent performs preliminary action by pre-computing and storing valid encoding patterns in lookup tables before runtime validation. These tables contain pre-analyzed byte sequence patterns and their corresponding validity status, allowing the system to quickly validate encoded data without performing complex real-time analysis of each byte sequence.
2Measurement precision
If full decoding is performed to determine character count in variable-length formats, then the measurement precision of character count is improved, but the processing time and resource consumption increase
Solution Approach 1:
The patent extracts only the necessary information for character counting from the encoded data without performing full decoding. By using lookup tables that map byte sequence patterns directly to character count contributions, the system extracts character count information efficiently without needing to fully interpret or decode the entire data set.
Solution Approach 2:
The patent substitutes the mechanical process of sequential decoding with a table-lookup-based validation and counting mechanism. Instead of mechanically processing each byte through decoding logic, the system uses pre-computed lookup tables to rapidly determine character counts, replacing complex computational mechanics with simpler memory access operations.
3Reliability
If encoding validation is performed to ensure data integrity, then the reliability of processed data is improved, but the resource intensity and processing overhead increase
Solution Approach 1:
The patent performs preliminary action by pre-computing and storing valid encoding patterns in lookup tables before runtime validation. These tables contain pre-analyzed byte sequence patterns and their corresponding validity status, allowing the system to quickly validate encoded data without performing complex real-time analysis of each byte sequence.
Solution Approach 2:
The patent substitutes the mechanical process of sequential decoding with a table-lookup-based validation and counting mechanism. Instead of mechanically processing each byte through decoding logic, the system uses pre-computed lookup tables to rapidly determine character counts, replacing complex computational mechanics with simpler memory access operations.
4Device complexity
If existing validation techniques (such as Lemire's) are used, then the validation process is simplified, but the handling of surrogate pairs and multi-byte sequences is limited
Solution Approach 1:
The patent implements universality by designing a lookup table system that handles multiple encoding scenarios within a unified framework. The same lookup table mechanism processes 1-byte sequences, 2-byte sequences, 3-byte sequences, 4-byte sequences, and surrogate pairs, making the validation system versatile without increasing operational complexity.
Solution Approach 2:
The patent segments the encoding validation process into distinct lookup tables for different byte sequence patterns. Each lookup table handles specific encoding scenarios (1-byte, 2-byte, 3-byte, 4-byte sequences), breaking down the complex validation task into manageable, pre-computed segments that can be quickly referenced without full decoding.
Data Source
AI summary
Technologies and solutions are also provided for determining a number of characters in encoded data, particularly for encoding formats that have variable byte lengths. Bytes in the encoding format can have different types, including at least one type that represents a continuation byte. That is, rather than having all data for a character being in a single byte, the data is encoded using two or more bytes. The number of continuation bytes can be counted and subtracted from a total number of bytes in a data set to determine the number of characters in the data set. Optionally, the validity of the data set with respect to an encoding format can be determined prior to, or concurrently with, determining a number of characters in the data set. SIMD techniques can be used with the character counting/validation processes to improve their performance.