WCET-Driven Dynamic Data Scratchpad Management With Compiler-Directed Prefetching
Why this work is in the frame
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Bibliographic record
Abstract
In recent years, the real-time community has produced a variety of approaches targeted at managing on-chip memory (scratchpads and caches) in a predictable way. However, to obtain safe WCET bounds, such techniques generally assume that the processor is stalled while waiting to reload the content of the on-chip memory; hence, they are less effective at hiding main memory latency compared to speculation-based techniques, such as hardware prefetching, that are largely used in general-purpose systems. In this work, we introduce a novel compiler-directed prefetching scheme for scratchpad memory that effectively hides the latency of main memory accesses by overlapping data transfers with the program execution. We implement and test an automated program compilation and optimization flow within the LLVM framework, and we show how to obtain improved WCET bounds through static analysis.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.007 | 0.003 |
| 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