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Record W2281100802 · doi:10.1109/fpt.2015.7393125

Bringing programmability to the data plane: Packet processing with a NoC-enhanced FPGA

2015· article· en· W2281100802 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInterconnection Networks and Systems
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsComputer scienceField-programmable gate arrayComputer architectureApplication-specific integrated circuitLatency (audio)Network packetEmbedded systemArchitectureForwarding planeFlexibility (engineering)Packet processingNetwork on a chipBandwidth (computing)Network processorComputer networkTelecommunications

Abstract

fetched live from OpenAlex

Modern computer networks need components that can evolve to support both the latest bandwidth demands and new protocols and features. To address this need, we propose a new programmable packet processor architecture built from an FPGA containing an embedded Network-on-Chip (NoC). The architecture is highly flexible, providing more programmability than is possible in an ASIC-based design, while supporting throughputs of 400 and 800 Gb/s. Additionally, we show that our design is 1.7× and 3.2× more area efficient, and achieves 1.5× and 3.7× lower latency than the best previously proposed FPGA-based packet processor on complex and simple applications, respectively. Lastly, we explore various ways a designer can take advantage of the flexibility available in this architecture.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.963
Threshold uncertainty score0.574

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.072
GPT teacher head0.286
Teacher spread0.214 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Quick stats

Citations16
Published2015
Admission routes1
Has abstractyes

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