Proceedings of the 2016 annual ACM Conference on SIGSIM Principles of Advanced Discrete Simulation
Notice bibliographique
Résumé
Welcome to the annual ACM Conference on Principles of Advanced Discrete Simulation (SIGSIM-PADS), the flagship conference for ACM's Special Interest Group on Simulation and Modeling (SIGSIM). The conference dates back to the annual PADS conference which began in 1985. Originally focusing exclusively on parallel and distributed simulation technologies and applications, the conference has since broadened its scope to encompass all aspects of modeling and simulation, including parallel and distributed execution, focusing on topics at the intersection of modeling and simulation and computer science. We are pleased to hold this year's conference in Banff, Alberta Canada. Banff provides a wonderful setting for the conference and offers many opportunities for outdoor activities and recreation. We hope you will enjoy the conference, the town of Banff, and the surrounding mountains. We wish to thank the many individuals who help make this year's conference possible. First, we thank the program committee members and additional external referees who provided timely reviews of the paper submissions, and participated in discussions concerning paper selection. In addition, we recognize the other members of the organizing committee for their contributions to the conference, including Jason Liu (Proceedings Chair), Philip Wilsey (Ph.D. Colloquium Chair), Dong (Kevin) Jin (Publicity Chair), and Holly Rush (Registration Chair and administrative support). Osman Balci did a terrific job with the web site, providing updates as soon as they were submitted. We thank the ACM Special Interest Group on Simulation both for their continued support, and for providing fellowships to students to help enable them to attend the conference. Finally, we wish to express special thanks to our two keynote speakers, Frederica Darema and David Jefferson for sharing their thoughts and insights with conference attendees. We have an excellent program to offer our attendees this year. New this year is a special interest in data-driven simulation with several sessions dedicated to this emerging topic. All papers submitted to the conference were rigorously reviewed with all papers receiving 3 referee reports. We thank the program committee and additional referees for their diligent efforts to provide timely, critical reviews and feedback to the authors. This process resulted in a total of 20 submissions accepted as full papers and 6 papers accepted as short papers. We expect everyone will appreciate the high-quality papers and presentations in the conference this year. This year's candidates for the best paper award are listed below. As is customary, the winning paper will be announced at the conference itself. Selected papers from the conference will also be invited to be extended to create a special issue of the ACM Transactions on Modeling and Computer Simulation (TOMACS) journal. DSSnet: A Smart Grid Modeling Platform Combining Electrical Power Distribution System Simulation and Software Defined Networking Emulation by Christopher Hannon, Jiaqi Yan and Dong Jin Modeling a Million-Node Slim Fly Network using Parallel Discrete Event Simulation by Noah Wolfe, Misbah Mubarak, Christopher D. Carothers, Philip Carns, and Robert Ross Automated Memoization for Parameter Studies Implemented in Impure Languages by Mirko Stoffers, Daniel Schemmel, Oscar Soria Dustmann and Klaus Wehrle We congratulate the authors of the paper winning the best paper award for the 2015 conference. Well done! FatTreeSim: Modeling a Large-scale Fat-Tree Network for HPC Systems and Data Centers Using Parallel and Discrete Event Simulation by Ning Liu, Adnan Haider, Xian-He Sun and Dong Jin. This year's Ph.D. Colloquium included eight students who prepared brief presentations as well as posters concerning their research. The Ph.D. Colloquium speaker was Dong (Kevin) Jin whose keynote presentation was entitled Early Career Experiences. We thank Kevin for his presentation as well as the students for their participation. The meeting this year will include many interesting presentations as well as excellent opportunities for networking. We hope you enjoy the conference!
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 | 0,003 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,004 | 0,002 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,101 | 0,036 |
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; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».