Mapping Arbitrary Logic Functions into Synchronous Embedded Memories For Area Reduction on FPGAs
Bibliographic record
Abstract
This work describes a new mapping technique, RAM-MAP, that identifies parts of circuits that can be efficiently mapped into the synchronous embedded memories found on field programmable gate arrays (FPGAs). Previous techniques developed for mapping into asynchronous embedded memories cannot be used because modern FPGAs do not have asynchronous embedded memories. After technology mapping, an area-prediction cost function is used to guide the selection of logic cones to be placed in embedded memories. Extra logic is added to compensate for missing asynchronous functionality on the synchronous memories. Experiments conducted on Altera's Stratix device family indicate that this embedded memory mapping technique can provide an average area reduction of 6.2% and up to 32.5% on a large set of industrial designs. A small architecture change that increases the size of the FPGA fabric by 0.05% can increase the average area reduction to 14.1% and up to 59.1% on the same design set
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".