Integrated retiming and placement for field programmable gate arrays
Why this work is in the frame
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Bibliographic record
Abstract
Retiming is a synchronous circuit transformation that can optimize the delay of a synchronous circuit by moving registers across combinational circuit elements. The combinational structure remains unchanged and the observable behavior of the circuit is identical to the original.In this paper, we address the problem of applying retiming techniques to circuits implemented in Field Programmable Gate Arrays (FPGAs). FPGAs contain prefabricated and configurable routing elements that allow us to easily implement a variety of circuits. However this interconnect contributes greatly to the overall delay in the implemented circuit. If a circuit is retimed prior to the placement and routing phases of the CAD flow, then it has no information about the delays introduced by the configurable interconnect. Our fundamental experiment is to determine whether there are any gains in tightly coupling retiming and placement so that the retiming algorithm has some estimate of the routing delays.Specifically, we introduce a post-placement retiming algorithm that understands how to take advantage of FPGA architectural features. This retiming algorithm may introduce extra registers into the circuit. These new registers need to be placed in some location in the FPGA. Retiming register placement is accomplished by a novel incremental clustering and placement algorithm. The incremental algorithm builds upon the placement of the non-retimed circuit to intelligently sift in the newly-introduced registers.In addition, we explore making the placement algorithms "retiming aware." These placement algorithms try to place logic blocks in such a way that the subsequent retiming produces better speed results. These techniques include the identification of retiming-critical cycles during placement.Our experiments show that the integration of retiming with placement results in 19% better clock periods in comparison to the application of retiming before the place and route steps.
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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 | 0.000 |
| 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