An Area-efficient Memory-based Architecture for P4-programmable Streaming Parsers in FPGAs
Bibliographic record
Abstract
Moving toward software-defined networking and function virtualization, flexibility and reconfigurability of the network have become more and more critical. Packet parsing, the first processing stage of programmable switches, requires high performance and reconfigurability to allow implementing low-latency and highly flexible data networks. This paper proposes an overlay architecture for an FPGA-based P4-programmable streaming packet parser. The purpose of this architecture is to allow supporting different functionality with a fixed hardware design by changing a program stored in an embedded memory. This program is derived from the parser section of a P4 code, describing a parsing graph. This approach eliminates a pipeline of parsing blocks in favor of a single parsing block, thereby reducing the design's complexity. Our architecture offers an 11 Gb/s data rate on a Xilinx Virtex-7 XC7VX690 FPGA, while its implementation requires 312 LUTs and 1135 FFs.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".