pCache: An Observable L1 Data Cache Model for FPGA Prototyping of Embedded Systems
Bibliographic record
Abstract
This paper presents a configurable and observable model of L1 data cache memory and a novel method for integrating the model into an FPGA prototype. Embedded system software designers use in-circuit emulation on FPGA platforms to validate the functionality and performance of embedded software. Data cache, particularly L1, has a major impact of system performance, yet remains unobservable during software debugging and analysis. Our solution is to model the data cache as an on-chip hardware peripheral that can be integrated into the processor system and can display the state of the data cache at any given time. The model is synthesized on Xilinx Virtex 5 FPGA and validated using several benchmarks. The experimental results show that the model can accurately track cache hits and misses and can estimate the run time of an embedded software application with an average error of only 5.4%, and a worst case error of only 13.7%.
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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 | 0.000 |
| 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 | 0.001 |
| 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 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".