Hardware Dataframe Merging for SSD Read-Modify-Write Integrity
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Solution Overview
Problem
As solid-state drives (SSDs) with smaller semiconductor device features become more susceptible to soft errors during read-modify-write operations, existing data storage systems fail to detect and prevent undetectable data errors effectively.
Innovation Solution
A Read Modify Write (RMW) system that merges data frames on-the-fly using a merge mask, performing bit-modifications and error checking to ensure data integrity, shifting from software processes to hardware optimization for improved speed and error detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If software processes are used for read-modify-write operations, then device complexity is reduced, but processing speed and error detection capability deteriorate
Solution Approach 1:
The patent replaces software-based read-modify-write operations with a hardware-based system that includes dedicated circuits for merging data frames, calculating CRC values, and detecting errors. This substitution of software processing with hardware implementation directly resolves the contradiction by achieving both reduced system complexity and improved processing speed through parallel hardware operations.
Solution Approach 2:
The patent introduces intermediate hardware components including merge masks, CRC calculation circuits, and error detection modules that act as mediators between data storage and processing. These intermediaries enable efficient hardware-based error detection and data frame merging while maintaining system organization and avoiding complexity increases.
2Reliability
If hardware-based approaches are used for read-modify-write operations, then processing speed and error detection capability are improved, but device complexity increases
Solution Approach 1:
The patent segments the read-modify-write operation into distinct functional hardware modules: data frame reception units, merge mask generation circuits, CRC calculation modules, and error detection circuits. This segmentation allows each module to perform its specific function efficiently while maintaining overall system manageability and avoiding complexity proliferation.
Solution Approach 2:
The hardware-based RMW system is designed with universal components that can handle multiple operations: the same merge mask circuitry processes both data frame merging and error detection, while CRC calculation circuits serve both validation and error correction functions. This multi-functionality reduces the need for separate dedicated circuits for each operation.
3Productivity
If firmware cycles are minimized through hardware optimization, then productivity is improved, but manufacturing complexity increases
Solution Approach 1:
The patent merges multiple functions into unified hardware circuits: the merge mask generation is combined with data frame merging operations, and CRC calculation is integrated with error detection processes. This merging eliminates the need for separate firmware intervention cycles and achieves high throughput while maintaining manufacturing feasibility through consolidated circuit designs.
Data Source
AI summary
A method of merging data frames includes: receiving a first data frame having a plurality of sectors; receiving a second data frame having a plurality of sectors; generating a merged output data frame by merging, using a plurality of data paths including a plurality of multiplexers, sectors of the second data frame with sectors of the first data frame; and performing an error check on at least one check-data frame having sectors corresponding to those in the first data frame or the second data frame, where at least some of the sectors in the check-data frame are transmitted on a subset of the plurality of data paths that transmits sectors of the merged output data frame, and where the error check verifies the merged output data frame.