Functional units power gating in SMT processors
Bibliographic record
Abstract
Power consumption has emerged as a primary concern in processor design constraints. Power-aware techniques are being applied at all levels of circuit and system design. These techniques aim at reducing power or energy dissipation in all types of computer equipments while meeting a desired throughput. At the architectural level, power-aware design has been an active area of research in the last decade for superscalar processors. Simultaneous multithreading processor (SMT), introduced as a complementary architecture to superscalar to increase throughput, has received less attention in the context of low-power design techniques. In SMT processors functional units are one of the major power consumers. In this paper we first study the opportunity for reducing the power consumption of functional units. Our results show that functional units are idle for a significant portion of the total execution cycle. Then we reuse and evaluate a microarchitectural technique to reduce functional unit power through power gating which has been recently proposed for superscalar processors. We show that in SMT processors, this technique can reduce floating point unit power considerably while maintaining performance.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".