Improving Power of Cache and Register File through Critical Path Instructions
Bibliographic record
Abstract
As feature size shrinks, power becomes one of the limiting factors in design of modern processors. Cache and register-file are the two power hungry components in processors, consuming more than one third of total processors' power budget. In this work, we propose a new architecture for cache and register-file which exploits critical path instructions to reduce power consumption. In this architecture, we have cache and register-file cells operating at two different voltage levels and we change the structure of the cells so that they dynamically switch between nominal and reduced supply voltages. Those cells that are accessed frequently by critical instructions are assigned to use nominal supply voltage to preserve performance. On the other side, the cells that are rarely accessed by critical instructions are assigned to low supply voltage to reduce power consumption. To reduce performance impact of voltage switching, we monitor critical instructions within long intervals and adjust the voltage of cells only when the intervals are elapsed. Our simulation results reveal that our optimization technique results in significant power saving with negligible effect on performance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".