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Record W4416884679 · doi:10.37665/srziido91071

A Novel Approach To 3D Chip Stacking

2012· article· W4416884679 on OpenAlexaff
Sukhi Binapal, Ron Csermak, Mark Vandermeulen

Bibliographic record

VenueSoldering and Reliability Conferences · 2012
Typearticle
Language
FieldEngineering
Topic3D IC and TSV technologies
Canadian institutionsON Semiconductor (Canada)
Fundersnot available
KeywordsApplication-specific integrated circuitFlexibility (engineering)MiniaturizationStackingIntegrated circuitChipIntegrated circuit packagingProcess (computing)SMT placement equipmentElectronic component

Abstract

fetched live from OpenAlex

ABSTRACT Designers seeking electronic package miniaturization but lacking the resources to utilize custom ASIC or complex 3D integration approaches can now take advantage of chip stacking technology for integrating a range of devices into small, system-in-package (SIP) structures. A robust, innovative approach, suitable for supporting lowto medium-volume applications, has been developed which avoids the cost and/or size penalties typically encountered using traditional multi-chip packaging techniques. Using bare die and vertical interconnect/interposer structures, this stacking technology permits the design of multi-chip assemblies with either identical or dissimilar die, copackaged with discrete and/or integrated passive devices. The approach is independent of ASIC foundry process and does not require through-silicon via (TSV) technology, and is therefore well suited for designs incorporating multiple IC’s from different semiconductor processes or manufacturing sources. Relative to system-on-chip (SOC) ASIC implementations, which carry large upfront NRE costs and long development cycles, 3D co-packaging of heterogeneous devices in customized SIP packages offers a proven, cost-effective alternative with greater design flexibility and reduced time to market. This paper will describe this novel 3D packaging approach and how it can be used in conjunction with discrete and integrated passive components to address package designs where size, weight, and/or performance are at a premium.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.620
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.036
GPT teacher head0.239
Teacher spread0.203 · 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 designOther design
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
Published2012
Admission routes1
Has abstractyes

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