Resolving the Reliability Issues of Open Blocks for 3-D NAND Flash: Observations and Strategies
Bibliographic record
Abstract
While the block size of 3-D NAND flash memory increases with the density and capacity, the raw bit-error rates (RBER) of open blocks could be significantly increased. This article conducts a systematic study over reliability issues caused by open blocks, and reports several new observations. We found that the reliability degradation, due to long open time in writing a block, could happen over all layers in a 3-D NAND block, even after the block is closed. To address the reliability issues of open blocks, this article first proposes to adaptively allocate active blocks to serve write requests based on the workload characteristics for open time reduction. We then propose a partial-block refreshing strategy to alleviate the amplified RBER variations in open blocks and, thus, avoid unnecessary refreshing operations in low-RBER layers. Experimental results show that the proposed method can reduce the RBER by 43% through the reduction of the open time by 28% on average, and reduce the extra write operations for refreshing by 23% on average.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".