Software-controlled multithreading using informing memory operations
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
To help tolerate the latency of accessing remote data in a shared-memory multiprocessor, we explore a novel approach to switch-on-miss multithreading that is software-controlled rather than hardware-controlled. Our technique uses informing memory operations to trigger the thread switches with sufficiently low over-head that we observe speedups of 10% or more for four out of seven applications, with one application speeding up by 14%. By selectively applying register partitioning to reduce thread switching overhead, we can achieve further gains: e.g. an overall speedup of 23% for FFT. Although this software-controlled approach does not match the performance of hardware-controlled schemes on multithreaded workloads, it requires substantially less hardware support than preview schemes and is nor likely to degrade single-thread performance. As remote memory accesses continue to become more expensive relative to software overheads, we expect software-controlled multithreading to become increasingly attractive in the future.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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