Power-performance efficiency of asymmetric multiprocessors for multi-threaded scientific applications
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Recently, under a fixed power budget, asymmetric multiprocessors (AMP) have been proposed to improve the performance of multi-threaded applications compared to symmetric multiprocessors. An AMP is a multiprocessor system in which its processors are not operating at the same frequency. Power consumption has become an important design constraint in servers and high-performance server clusters. This paper explores the power-performance efficiency of Hyper-Threaded (HT) AMP servers, and proposes a new scheduling algorithm that can be used to reduce the overall power consumption of a server while maintaining a high level of performance. Prototyping AMPs on a commercial 4-way SMP server, we show that on average 15.6 % energy savings and 6.1 % slowdown for the HT-disabled case, and 7.1 % energy savings and 4.8% slowdown for the HT-enabled case can be achieved across NAS and SPEC OpenMP applications. 1.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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