Front-end Offload of Storage Hash and Compression
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Solution Overview
Problem
Content-based storage solutions face challenges in efficiently managing duplicate data blocks and optimizing storage system performance, particularly in handling small write operations and processing-intensive tasks like hash signature calculations and data compression.
Innovation Solution
The implementation of a content addressable storage system with front-end offloading, where a front-end device calculates hash digests and performs compression for incoming write operations, reducing the processing load on storage controllers and optimizing data storage by utilizing hash-based mapping and compression techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If content-based storage solution is implemented, then storage capacity efficiency is improved, but processing load on storage system increases
Solution Approach 1:
The patent segments the storage system into multiple storage nodes, each independently handling content-based storage operations. This distribution of processing load across multiple nodes allows the system to maintain high storage capacity efficiency through content-based deduplication while preventing any single node from becoming a processing bottleneck.
Solution Approach 2:
The patent introduces a cache layer as an intermediary between the host and storage nodes. This cache handles processing-intensive operations such as hash calculations and compression, reducing the processing burden on the main storage system while maintaining the benefits of content-based storage for capacity efficiency.
2Adaptability or versatility
If hash signature calculations and data compression are performed by storage controller, then content-based storage functionality is achieved, but processor utilization increases
Solution Approach 1:
The patent extracts the processing-intensive hash signature calculations and data compression operations from the main storage controller and relocates them to dedicated processing units or cache memory. This separation allows the storage controller to maintain content-based storage functionality while reducing overall processor utilization by offloading computational tasks.
Solution Approach 2:
The patent performs hash calculations and compression operations in advance during the data write process, before data is committed to permanent storage. This preliminary processing reduces the computational burden on the storage controller during critical path operations, thereby reducing processor utilization while maintaining full content-based storage functionality.
3Reliability
If small write operations are processed through full content-based storage workflow, then data integrity is maintained, but write cache efficiency decreases
Solution Approach 1:
The patent applies partial content-based storage processing to small write operations, performing only essential hash calculations and selective compression rather than the complete content-based storage workflow. This partial processing maintains sufficient data integrity for small writes while significantly improving write cache efficiency by reducing processing overhead.
Data Source
AI summary
A storage system in one embodiment comprises a front-end device and a first storage node corresponding to the front-end device. The first storage node comprises a processor that is separate from the front-end device. The front-end device is configured to obtain a write operation that comprises at least a first block of data and to calculate a hash digest based at least in part on the first block of data. The front-end device is configured to provide the hash digest to the processor. The processor is configured to identify a first data page that comprises a second block of data that is a target for replacement by the first block of data and to identify a second storage node based at least in part on the first data page. The processor is configured to transmit the hash digest to the second storage node.