Improving energy efficiency of asymmetric chip multithreaded multiprocessors through reduced OS noise scheduling
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Bibliographic record
Abstract
Abstract The performance of the emerging chip multithreaded symmetric multiprocessors (SMPs) is of great importance to the high performance computing community. However, the growing power consumption of such systems is of increasing concern, and techniques that can be used to increase the overall system power efficiency while sustaining the performance are very desirable. Operating system (OS) noise can have a dramatic effect on the system performance. Effectively handling the smaller OS tasks while simultaneously preserving application thread synchronicity leads to gains in the overall system efficiency. Recently, under a fixed power budget, asymmetric multiprocessors (AMP) have been proposed to improve the performance of multithreaded applications. An AMP in this context is a multiprocessor system in which its processors are not operating at the same frequency. This paper proposes two simple scheduling methods that reduce the impact of OS noise, while simultaneously taking advantage of an opportunity to increase the overall machine energy efficiency on AMP servers. Prototyping AMPs on a commercial 2‐way dual‐core Hyper‐Threaded (HT) Intel Xeon SMP server, using real power measurements across six SPEC OpenMP applications, indicates that the first proposed scheduler performs better on average for HT‐enabled systems, whereas the second scheduler is superior on average for HT‐disabled systems. Copyright © 2009 John Wiley & Sons, Ltd.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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 it