Hardware trace reconstruction of runtime compiled code
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
Summary Hardware tracing has emerged as a low‐cost technique to analyze systems at a very fine granularity, thus mitigating the need for software‐only trace approaches for performance analysis. State‐of‐the‐art trace hardware on modern Intel and ARM processors allows recording change‐of‐flow instructions in executable binaries, such as branches, for off‐line reconstruction. This conventional userspace–based trace reconstruction, however, is not robust enough in the common scenarios where runtime code is being generated, compiled, and executed. We therefore propose a novel kernel‐assisted mechanism called FlowJIT to reconstruct hardware traces with a low overhead of around 1.3 μ s per code page modification event. We further show the efficacy or our technique with the help of 2 illustrative usecases that cover the JIT compiled code scenario and a same‐page instruction modification scenario. Our implementation has been open sourced as a patch for the Linux kernel.
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 | 0.001 |
| 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 | 0.003 |
| 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