Towards Write-Activity-Aware Page Table Management for Non-volatile Main Memories
Bibliographic record
Abstract
Non-volatile memories such as phase change memory (PCM) and memristor are being actively studied as an alternative to DRAM-based main memory in embedded systems because of their properties, which include low power consumption and high density. Though PCM is one of the most promising candidates with commercial products available, its adoption has been greatly compromised by limited write endurance. As main memory is one of the most heavily accessed components, it is critical to prolong the lifetime of PCM. In this article, we present w rite- a ctivity-aware p age t able m anagement (WAPTM), a simple yet effective page table management scheme for reducing unnecessary writes, by redesigning system software and exploiting write-activity-aware features provided by the hardware. We implemented WAPTM in Google Android based on the ARM architecture and evaluated it with real Android applications. Experimental results show that WAPTM can significantly reduce writes in page tables, proving the feasibility and potential of prolonging the lifetime of PCM-based main memory through reducing writes at the OS level.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".