Impact of compiler optimizations on voltage droops and reliability of an SMT, multi-core processor
Bibliographic record
Abstract
In ultra-low power era, one of the most effective ways of reducing power consumption is to lower supply voltage level. When programs execute on processors, voltage fluctuations can occur due to sudden changes in current draw between successive instructions. Such voltage fluctuations can reduce the voltage levels below acceptable levels and cause unreliable operation in microprocessors. Voltage droops due to di/dt effects have been studied in the past, however no prior work studies the effect of compiler optimizations on voltage droops. Past work has studied the impact of compiler optimizations on performance and power, but not reliability. In this paper, we analyze voltage droops with different compiler optimization levels. We also report corresponding performance, power and energy results to put the results into perspective. No clear trends could be observed regarding the effect of compiler optimizations on voltage droops. We conclude that dynamic voltage noise mitigation is necessary because we cannot guarantee voltage noise reduction with static compiler optimization.
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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".