Bibliographic record
Abstract
Welcome to the 32 nd Electrical Performance of Electronic Packaging and Systems (EPEPS) conference!This year's conference is held at Sonesta San Jose at Milpitas, CA, USA from Oct. 15 -18, 2023.Over the years the EPEPS conference technical area coverage has grown to cover the most pertinent areas needing innovations in the field of electronic packaging including: system, board, package and on chip interconnects; electromagnetic modeling techniques and algorithms; signal, thermal and power integrity; high-speed link design; chip and package co-design; heterogeneous integration, TSVs and MCMs; machine learning; advanced and parallel CAD techniques for signal, power and thermal integrity analysis; macro-modeling and model order reduction; quantum computing.The solutions to many problems encountered by the technical community over the years have been brought about through research presented at past EPEPS conferences.The research at EPEPS has been enriched due to EPEPS being a global participation conference bringing together members of the technical community from Academia, Industry and Government Laboratories.The program prepared for EPEPS 2023 is very strong with technical novelty and diversity covering a wide spectrum of topics associated with electronic packaging.The technical paper sessions include 60 papers selected after a robust and thorough review process by the technical program committee (TPC) assisted by the paper review committee (PRC).The conference technical events include three keynote presentations on future outlooks and pertinent efforts on electronic packaging and systems given by: Prof. Jose Cobos of Universidad Politécnica de Madrid (also Founder of the company DPx) on Surface Power Delivery for HPC hardware, Dr. Albert Ruehli of Missouri University of Science and Technology on 50 years of PEEC and Dr. Lester Lampert of Intel Corp on quantum computing challenges.Furthermore, the first day of the conference includes seven technical tutorials given by highly respected experts from the industry and academia.Other events at EPEPS 2023 include special sessions on EPS benchmark, high-speed interconnects, electromagnetics, PEEC methods, model order reduction and machine learning techniques.Part of the success of EPEPS over its history has been due to its partnership with industry which is sometimes portrayed through sponsorships and sponsor events.EPEPS 2023 is sponsored by: Samsung [Gold Sponsor], AMD [Silver Sponsor], Nvidia [Silver Sponsor], Qualcomm [Silver Sponsor], Keysight [Silver Sponsor], Xpeedic [Silver Sponsor], Cadence [Silver Sponsor], Siemens EDA [Silver Sponsor] and Texas Instruments [Silver Sponsor].In addition to the sponsor and exhibitor booths, there are several 10 minutes product demonstrations by the sponsors.Four paper awards were at this year's conference.These are the best conference paper award, the best student paper award, the best poster paper award, and the best benchmark paper award.The winning papers are decided after a thorough evaluation by the EPEPS 2023 awards committee.Furthermore, two raffle prize awards will be given for participation in each of the sponsor events.Finally, we would like to thank and acknowledge the contributions of: EPEPS TPC, EPEPS PRC, EPEPS 2023 Executive Committee -Kemal Aygun, Jose Hejase, Xu Chen, Zhen Peng and Vaishnav Srinivas.We would also like to thank IEEE MCE for helping us with major conference logistics including helping with conference registration services.Last but not least, we greatly appreciate and recognize the support of our IEEE society sponsors: the IEEE Microwave Theory and Techniques
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.899 | 0.888 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".