Notice bibliographique
Résumé
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
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,005 | 0,002 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,003 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,899 | 0,888 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; l’étiquette directe de Gemma et le classifieur distillé Codex s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».