Design and Characterization of a Digital Delay Locked Loop Synthesized from Black Box Standard Cells
Bibliographic record
Abstract
A delay locked loop (DLL) is a feedback control system that equalizes the phase of two delayed copies of the same clock signal. The DLL is useful for compensating for the clock distribution delays that arise in many system configurations. Our motivation for designing an all-digital DLL was to ensure that the clock signal (and hence input vectors) received from off-chip via the pad circuits would be synchronized with the distributed and buffered clock signal at the flip-flops (and hence the synchronous datapath signals) within the core of a 250-MHz CMOS integrated circuit (IC) implemented in 180-nm, six-metal technology. Due to an aggressive design schedule and a limited number of designers, it was decided to synthesize the entire IC, including the DLL, from a VHDL model down to black box standard cells. This necessitated a robust, structural-level DLL design that would operate over a broad frequency range while tolerating a range of gate delays. Multiple fall-back operating modes and test features were included to increase the characterizability of the design. The digital delay line was implemented as a cascade containing 256 inverter pairs. Altogether the DLL occupied 28200 sq.microns, which was only 0.405% of the 6.92 sq.mm core of the IC. The fabricated DLL was verified to operate from 14 MHz up to the 166 MHz maximum frequency of the available tester
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".