Scalable interprocedural register allocation for high level synthesis
Why this work is in the frame
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Bibliographic record
Abstract
The success of classical high level synthesis has been limited by the complexity of the applications it can handle, typically not large enough to necessitate the departure from the industrial standard, register transfer level design methodology. Recent advances of micro-architecture model enabled the use of stacked based controller, allowing complex algorithms with multiple procedures to be implemented directly in hardware. Nevertheless, design optimizations across procedure boundaries have not been fully explored. In this paper, we address the problem of interprocedural register allocation in the context of high level synthesis. In contrast to a recently proposed interprocedural register allocation algorithm, which processes an expensive, global, graph representation of the conflict relation of all values to achieve near optimality, we introduce a new method, called color palette propagation (CPP). The key idea behind our method, is to propagate the use of colors, whose number is significantly smaller than the size of the conflict relation, across different procedures. With a complexity comparable to intraprocedural register allocation, we show that our method can scale to very large C programs. For those benchmarks that can be handled by conventional global methods, our method produced nearly the same number of registers, while providing an average speedup factor of 90.
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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 | 0.000 | 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 | 0.001 | 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