RAID Data Multiplication Using Bulk XOR Map Tables
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Solution Overview
Problem
Current RAID systems face inefficiencies in data multiplication operations due to the need for extensive table lookups and calculations, which become bottlenecks as storage sizes increase, especially in RAID6 systems requiring multiple parity calculations.
Innovation Solution
The implementation of a method and controller that generate map tables for Galois Field operations, allowing for simultaneous XOR operations across larger data units, thereby reducing the need for individual byte-level calculations and speeding up data multiplication processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional table lookup method is used for Galois Field multiplication, then correctness of calculation is ensured, but calculation efficiency deteriorates due to extensive table lookups and byte-by-byte processing
Solution Approach 1:
The patent divides data into larger units (e.g., 64-byte blocks) and processes multiple bytes simultaneously using vectorized XOR operations. Instead of processing one byte at a time with separate table lookups, the data is segmented into chunks that can be operated on in parallel, reducing the total number of operations required.
Solution Approach 2:
The patent pre-calculates and stores multiplication results for common Galois Field operations in lookup tables organized by data patterns. When processing actual data, the system first identifies matching patterns and retrieves pre-computed results, avoiding repeated table lookups for identical operations.
Solution Approach 3:
The patent changes the operational parameters from byte-level processing to larger data unit processing (e.g., 64-byte blocks). By adjusting the granularity of processing units and utilizing wider XOR operation units, the system performs multiple multiplications in a single operation cycle, dramatically improving throughput.
2Quantity of substance
If storage size increases to meet growing data demands, then storage capacity is improved, but computational overhead increases due to more extensive data multiplication operations
Solution Approach 1:
The patent segments large storage operations into manageable data blocks that can be processed efficiently. By organizing data into standardized chunks and applying vectorized operations, the computational complexity scales more gracefully with storage capacity rather than linearly increasing with total data volume.
Solution Approach 2:
The patent replaces traditional sequential mechanical-style processing (byte-by-byte calculation) with parallel vectorized operations. This substitution allows the system to handle larger datasets without proportionally increasing computational overhead, as multiple operations execute simultaneously rather than in series.
3Measurement precision
If byte-by-byte calculation is performed for each multiplication operation, then precision of individual operations is maintained, but overall processing speed deteriorates
Solution Approach 1:
The patent segments data into larger units while maintaining the integrity of individual byte-level calculations through systematic XOR operations. The segmentation approach preserves calculation accuracy by ensuring each byte within a block undergoes proper Galois Field multiplication, while the block structure enables parallel processing of multiple bytes simultaneously.
Solution Approach 2:
The patent merges multiple individual byte-level multiplication operations into a single vectorized operation that processes entire data blocks at once. By combining these operations while maintaining the mathematical correctness of each individual multiplication, the system achieves both precision and speed improvements.
Data Source
AI summary
The invention discloses a method and controller for processing data multiplication in a RAID system. Map tables are generated for all values in a field, respectively. The length of an XOR operation unit is chosen to be appropriate w bits (e.g., 332 bits or 64 bits). One or several XOR operation units form a multiplication unit of a data sector. When computing on-line, data in a disk drive of a disk array are performed with XOR operations in accordance with one of the map tables using an XOR operation unit as one unit while computing on the multiplication unit to obtain a product of multiplication. Making use of the RAID system established according to the disclosed method, only XOR operations are required to compute parity data or recover damaged user data. Moreover, several calculations can be performed simultaneously. Therefore, the efficiency of the RAID system can be effectively improved.