Memory Controller Write Aggregation to Bypass Read-Modify-Write
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Solution Overview
Problem
Existing memory sub-systems, particularly NAND flash memory, face inefficiencies and resource wastage due to the read-modify-write method, which slows down performance and reduces storage capacity by frequently rewriting large blocks for small data updates, leading to increased wear and tear and power consumption.
Innovation Solution
A memory controller aggregates multiple write requests until they reach a bundle unit size before transferring the data to memory components, bypassing the need for a read operation, thus expediting the write process and optimizing resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the read-modify-write method is used for write operations, then data can be updated in memory components, but the process becomes slow and consumes more time due to frequent reading and rewriting of large blocks
Solution Approach 1:
The system performs preliminary actions by aggregating multiple write requests into a buffer before executing the actual write operation to memory components. This allows the controller to accumulate data from multiple host write requests and issue a single optimized write operation, eliminating the need for read-modify-write cycles and significantly reducing write time.
Solution Approach 2:
The patent introduces an intermediary buffer between the host system and memory components. This buffer receives and aggregates write requests from the host, then transfers the accumulated data to memory components in optimized batches. This intermediary layer decouples the host write operations from the memory write operations, allowing independent optimization of both interfaces.
2Productivity
If the read-modify-write method is used, then data updates can be performed, but storage capacity is reduced due to frequent rewriting of large blocks for small data updates
Solution Approach 1:
The system applies partial action by selectively aggregating only the necessary data from multiple write requests into the buffer, rather than reading and rewriting entire blocks. This allows the system to update only the specific portions of data that need to be modified, reducing the amount of data rewritten and thereby preserving more usable storage capacity.
3Productivity
If the read-modify-write method is used, then data can be updated, but wear and tear on memory components increases
Solution Approach 1:
By performing preliminary aggregation of write requests in a buffer, the system consolidates multiple small write operations into fewer, larger optimized write operations. This reduces the total number of write cycles to memory components, directly decreasing wear and tear and extending memory lifespan.
4Productivity
If the read-modify-write method is used, then data updates can be performed, but power consumption increases
Solution Approach 1:
The system performs preliminary data aggregation in a buffer, consolidating multiple write operations into fewer optimized write cycles. Since each optimized write operation transfers more data in a single operation rather than performing read-modify-write cycles, the total energy consumption is reduced while maintaining data update functionality.
Data Source
AI summary
A system component, such as a memory sub-system controller, aggregates multiple sequential write requests. The controller receives an individual write request from a host system to program a set of data and determines that an aggregation cache has space remaining for the set of data. The controller aggregates the set of data into the aggregation cache in response to determining that the aggregation cache has space remaining for the set of data and transfers data stored in the aggregation cache to a portion of a set of memory components instead of modifying a block of data read from the set of memory components in response to determining that an amount of data stored in the aggregation cache has reached a specified size.