Run-time power-gating in caches of GPUs for leakage energy savings
Why this work is in the frame
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Bibliographic record
Abstract
In this paper, we propose a novel microarchitectural technique for run-time power-gating caches of GPUs to save leakage energy. The L1 cache (private to a core) can be put in a low-leakage sleep mode when there are no ready threads to be scheduled, and the L2 cache can be put in sleep mode when there is no memory request. The sleep mode is state-retentive, which precludes the necessity to flush the caches after they are woken up. The primary reason for the effectiveness our technique lies in the fact that the latency of detecting cache inactivity, putting a cache to sleep and waking it up before it is accessed, is completely hidden microarchitecturally. The technique incurs insignificant overheads in terms of power and area. Experiments were performed using the GPGPU-Sim simulator on benchmarks that was set up using the CUDA framework. The power and latency modeling of the cache arrays for measuring the wake-up latency and the break-even periods is performed using a 32-nm SOI IBM technology model. Based on experiments on 16 different GPU workloads, the average energy savings achieved by the proposed technique is 54%.
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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 | 0.001 | 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 | 0.000 |
| 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 it