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Record W3008972875 · doi:10.1145/3373087.3375371

Unleashing the Power of FPGAs as Programmable Switches

2020· article· en· W3008972875 on OpenAlexaff
Thomas Luinaud, Thibaut Stimpfling, Jeferson Santiago da Silva, Yvon Savaria, J. M. Pierre Langlois

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInterconnection Networks and Systems
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsField-programmable gate arrayComputer scienceFlexibility (engineering)ArchitectureComputer architectureLimit (mathematics)Network packetEmbedded systemComputer network

Abstract

fetched live from OpenAlex

The P4 language and the PISA architecture have revolutionized the field of networking. Thanks to P4 and PISA, new networking applications and protocols can be rapidly evaluated on high performance switches. While P4 allows the expression of a wide range of packet processing algorithms, current programmable switch architecture limit the overall processing flexibility. To address this shortcoming recent work have proposed to implement PISA on FPGAs. However, little effort has been devoted to analyze whether FPGAs are good candidates to implement PISA. In this work, we take a step back and evaluate the micro-architecture efficiency of various PISA blocks. Using a theoretical analysis and experiments, we demonstrate that current FPGA architecture drastically limit the performance of a few PISA blocks. Thus, we explore two avenues to alleviate these shortcomings. First, we identify some network applications that are well tailored to current FPGAs. Second, to support a wider range of networking applications, we propose modifications to the FPGA architecture which can also be of interest outside the networking field.

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.

How this classification was reachedexpand

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)0.000
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.957
Threshold uncertainty score0.127

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.022
GPT teacher head0.229
Teacher spread0.207 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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