MétaCan
Menu
Back to cohort

A Zero Inductor-Voltage 48V to 12V/70A Converter for Data Centers with 99.1% Peak Efficiency and 2.5kW/in<sup>3</sup> Power Density

2020· article· en· W3037927136 on OpenAlexaff
Samuel Webb, Yan‐Fei Liu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsQueen's University
Fundersnot available
KeywordsServerElectrical engineeringPower (physics)Voltage regulatorInductorVoltageUpstream (networking)Computer scienceTopology (electrical circuits)EngineeringElectronic engineeringComputer networkPhysics

Abstract

fetched live from OpenAlex

The demand for internet and computing resources has led to datacenters and servers being one of the fastest growing consumers of power in the world today. While datacenter power architectures have improved over time, the majority of the loss still occurs at the server power supply, and board level voltage regulators. To attempt to improve this, Google has proposed and implemented a 48 volt server architecture that can significantly reduce both the upstream conversion losses, and the distribution losses within the server racks. Google has estimated that this change can reduce their overall conversion losses by up to 30%, but to fully realize these benefits new technology is needed to convert 48 volts down to the point of load voltage levels. The Intermediate Bus Architecture, where a "bus converter" steps down the 48 volts to a lower bus voltage which is then stepped down by point-of-load regulators is a very attractive option to "bridge the gap" between the 48 volt architecture of cutting edge servers, and the existing 12 volt architecture. The proposed topology is a novel intermediate bus converter that can achieve up to 2500W/in <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> power density, 99.1% peak efficiency, and 97.2% full load efficiency for 70A 12V output. Compared with other cutting edge designs this work achieves higher efficiency, and superior power density without the need for complex control, or a sensitive resonant based design.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.930
Threshold uncertainty score1.000

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 head0.020
GPT teacher head0.223
Teacher spread0.204 · 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.

Study designSimulation or modeling
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

Citations19
Published2020
Admission routes1
Has abstractyes

Explore more

Same topicAdvanced DC-DC ConvertersFrench-language works237,207