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Record W2318422608 · doi:10.1109/hpca.2016.7446076

The runahead network-on-chip

2016· article· en· W2318422608 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInterconnection Networks and Systems
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsComputer scienceComputer networkMicroarchitectureLatency (audio)Network on a chipNetwork packetRouterEmbedded systemSource routingRouting protocolRouting tableTelecommunications

Abstract

fetched live from OpenAlex

With increasing core counts and higher memory demands from applications, it is imperative that networks-on-chip (NoCs) provide low-latency, power-efficient communication. Conventional NoCs tend to be over-provisioned for worst-case bandwidth demands leading to ineffective use of network resources and significant power inefficiency; average channel utilization is typically less than 5% in real-world applications. In terms of performance, low-latency techniques often introduce power and area overheads and incur significant complexity in the router microarchitecture. We find that both low latency and power efficiency are possible by relaxing the constraint of lossless communication. This is inspired from internetworking where best effort delivery is commonplace. We propose the Runahead NoC, a lightweight, lossy network that provides single-cycle hops. Allowing for lossy delivery enables an extremely simple bufferless router microarchitecture that performs routing and arbitration within the same cycle as link traversal. The Runahead NoC operates either as a power-saver that is integrated into an existing conventional NoC to improve power efficiency, or as an accelerator that is added on top to provide ultra-low latency communication for select packets. On a range of PAR-SEC and SPLASH-2 workloads, we find that the Runahead NoC reduces power consumption by 1.81 as a power-saver and improves runtime and packet latency by 1.08× and 1.66× as an accelerator.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.970
Threshold uncertainty score0.760

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.015
GPT teacher head0.223
Teacher spread0.208 · 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

Citations24
Published2016
Admission routes2
Has abstractyes

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