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Record W4402593055 · doi:10.1109/mm.2024.3462351

Interconnect Design for Heterogeneous Integration of Chiplets in the AMD Instinct MI300X Accelerator

2024· article· en· W4402593055 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

VenueIEEE Micro · 2024
Typearticle
Languageen
FieldComputer Science
TopicEmbedded Systems Design Techniques
Canadian institutionsAdvanced Micro Devices (Canada)
Fundersnot available
KeywordsInstinctComputer scienceInterconnectionComputer architectureEmbedded systemSoftware engineeringTelecommunications

Abstract

fetched live from OpenAlex

The semiconductor industry has deployed chiplet-based system-on-chip architectures for several years. Central to a successful chiplet-based product is the die-to-die interconnect technology between the chiplets. Based on product requirements, some chiplet designs can utilize a single interconnect technology such as 2-D signals over an organic substrate or higher-density 2.5-D integration technologies. With increasing demands on compute and memory capabilities, high-performance products are now moving to heterogeneous integration, which combines multiple advanced packaging technologies all within a single system on chip. To address the market demands for high-performance artificial intelligence solutions, AMD has introduced the AMD Instinct MI300X accelerator. This article details the chiplet interconnect design required to support a sophisticated package that takes high-volume heterogeneous integration to a new level.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.827
Threshold uncertainty score0.450

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 communication0.0000.000
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 head0.069
GPT teacher head0.311
Teacher spread0.242 · 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