DynamoSim: a trace-based dynamically compiled instruction set simulator
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
Instruction set simulators are indispensable tools for the architectural exploration and verification of embedded systems. Different techniques have recently been proposed to speed up the simulation over the classical interpretation-based simulators, while maintaining their flexibility. We introduce a suite of techniques inspired by recent advances in dynamic compilers to construct a hybrid simulation framework. Compared with compiled simulators reported earlier, our framework is more flexible, since any instruction can be interpreted; and faster, since only frequently executed instructions are translated on-the-fly into native code for direct execution, and the scope of our translation is extended from basic blocks to traces, and sophisticated register allocation is performed. Comprehensive results on SPEC2000 benchmarks are reported for the standard SimpleScalar processor to demonstrate the efficiency of proposed techniques.
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 | 0.000 |
| 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