FPGA acceleration of enhanced boolean constraint propagation for SAT solvers
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
We propose a hardware architecture to accelerate boolean constraint propagation (BCP). Although satisfiability (SAT) solvers in software use varying search and learning strategies, BCP is a fundamental component and by far consumes the most CPU time. Our field-programmable gate array (FPGA) design uses on-chip SRAM to facilitate the acceleration of BCP. We discuss many insights to our innovative hardware memory layout, which is very compact and enables extremely fast BCP. It also supports multithreading to minimize the idle time in hardware and to fully utilize the multicore processor host. Additionally, many industrial SAT instances encode logic gates as constraints. We compact these to simultaneously reduce the hardware memory usage as well as speed up the computation (enhanced BCP). We implemented our enhanced BCP core and integrated it with a simple software SAT solver which communicates over PCI Express. Hardware performance counters show that a single processing engine is up to 4x faster than a state-of-the-art software SAT solver.
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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 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