A Utility-based Approach to Cost-Aware Caching in Heterogeneous Storage Systems
Bibliographic record
Abstract
Modern single and multi-processor computer systems incorporate, either directly or through a LAN, a number of storage devices with diverse performance characteristics. These storage devices have to deal with workloads with unpredictable burstiness. Storage aware caching scheme - that partitions the cache among the disks, and aims at balancing the work across the diskssnecessary in this environment. Moreover, maintaining proper size for these partitions is crucial. The existing storage aware caching schemes assume linear relationship between cache size and hit ratio. But, in practice a (disk) partition may accumulate cache blocks (thus, choke the remaining disks) without increasing the hit ratio significantly. This disk choking phenomenon may degenerate the performance of the disk system. In this paper, we address this issue of disk choking and present a repartitioning framework based on the notion of marginal gains. Experimental results shows the effectiveness of our approach. We show that our scheme outperforms the existing storage-aware caching schemes while supplied with a workload showing the non-linear relationship between cache size and hit ratio.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 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".