An FPGA prototype for the experimental evaluation of a multizone network cache
Why this work is in the frame
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Bibliographic record
Abstract
Network routers rely on Content Addressable Memories (CAMs) to accelerate the process of looking up the next hop of a packet. We describe our implementation of a versatile prototype for a CAM. This prototype allows the empirical evaluation of the idea of caching lookup results in a multizone cache organized according to the length of the network prefix portion of the addresses. Implementing a cache in an FPGA efficiently required the design of a new cache replacement policy, the Bank Nth Chance policy. In this paper we present results from a functional simulator that allows the comparison of this new policy with existing ones such as LRU, FIFO and Second Chance. We have a complete and functional prototype with pipelined lookups implemented in a Xilinx Virtex 2000E device; we also report frequency of operation and occupation of the device.
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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 | 0.000 |
| Open science | 0.000 | 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