A Multi-ported Memory Compiler Utilizing True Dual-Port BRAMs
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
Recent work has shown how multi-ported RAMs can be built out of dual-ported RAMs. Such techniques combine two structures: a set of "data banks" to hold the data, and a method for selecting the bank containing the last-written data, often called a live-value table (LVT). Most previous work has focused on the design of the LVT to reduce area and improve performance. In this paper, we instead reduce area by optimizing the design of the "data banks" portion. The optimization is embedded into a memory compiler that solves a set cover problem. When the set cover problem is solved optimally, the data banks use minimum area. Our technique applies to multi-ported RAMs that have a structural pattern we describe as "switched ports". Switched ports are a generalization of true ports, where a certain number of write ports can be dynamically switched into a possibly different number of read ports using one common read/write control signal. Furthermore, a given application may have multiple sets, each set with a different read/write control. While previous work generates multi-port RAM solutions that contain only true ports, or only simple ports, we contend that using only these two models is too limiting and prevents optimizations from being applied. Experimental results on 10 random instances of multi-port RAMs show 17% BRAM reduction on average compared to the best of other approaches. The compiler and a fully parameterized Verilog implementation is released as an open source library. The library has been extensively tested using Altera's EDA tools.
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 | 0.000 | 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 | 0.001 | 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