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Enregistrement W113453355 · doi:10.2172/883740

ISCR FY2005 Annual Report

2006· report· en· W113453355 sur OpenAlexfundno aff
David E. Keyes, James R. McGraw

Notice bibliographique

Revuenon disponible
Typereport
Langueen
DomaineDecision Sciences
ThématiqueSimulation Techniques and Applications
Établissements canadiensnon disponible
Organismes subventionnairesInstitute of Circulatory and Respiratory HealthU.S. Department of CommerceLawrence Livermore National LaboratoryU.S. Department of Energy
Mots-clésNational laboratoryComputer scienceNational securityOperations researchData scienceEngineeringPolitical scienceEngineering physics

Résumé

récupéré en direct d'OpenAlex

Large-scale scientific computation and all of the disciplines that support and help validate it have been placed at the focus of Lawrence Livermore National Laboratory (LLNL) by the Advanced Simulation and Computing (ASC) program of the National Nuclear Security Administration (NNSA) and the Scientific Discovery through Advanced Computing (SciDAC) initiative of the Office of Science of the Department of Energy (DOE). The maturation of simulation as a fundamental tool of scientific and engineering research is underscored in the President's Information Technology Advisory Committee (PITAC) June 2005 finding that ''computational science has become critical to scientific leadership, economic competitiveness, and national security''. LLNL operates several of the world's most powerful computers--including today's single most powerful--and has undertaken some of the largest and most compute-intensive simulations ever performed, most notably the molecular dynamics simulation that sustained more than 100 Teraflop/s and won the 2005 Gordon Bell Prize. Ultrascale simulation has been identified as one of the highest priorities in DOE's facilities planning for the next two decades. However, computers at architectural extremes are notoriously difficult to use in an efficient manner. Furthermore, each successful terascale simulation only points out the need for much better ways of interacting with the resulting avalanche of data. Advances in scientific computing research have, therefore, never been more vital to the core missions of LLNL than at present. Computational science is evolving so rapidly along every one of its research fronts that to remain on the leading edge, LLNL must engage researchers at many academic centers of excellence. In FY 2005, the Institute for Scientific Computing Research (ISCR) served as one of LLNL's main bridges to the academic community with a program of collaborative subcontracts, visiting faculty, student internships, workshops, and an active seminar series. The ISCR identifies researchers from the academic community for computer science and computational science collaborations with LLNL and hosts them for both brief and extended visits with the aim of encouraging long-term academic research agendas that address LLNL research priorities. Through these collaborations, ideas and software flow in both directions, and LLNL cultivates its future workforce. The Institute strives to be LLNL's ''eyes and ears'' in the computer and information sciences, keeping the Laboratory aware of and connected to important external advances. It also attempts to be the ''hands and feet'' that carry those advances into the Laboratory and incorporate them into practice. ISCR research participants are integrated into LLNL's Computing Applications and Research (CAR) Department, especially into its Center for Applied Scientific Computing (CASC). In turn, these organizations address computational challenges arising throughout the rest of the Laboratory. Administratively, the ISCR flourishes under LLNL's University Relations Program (URP). Together with the other four institutes of the URP, the ISCR navigates a course that allows LLNL to benefit from academic exchanges while preserving national security. While it is difficult to operate an academic-like research enterprise within the context of a national security laboratory, the results declare the challenges well met and worth the continued effort. The pages of this annual report summarize the activities of the faculty members, postdoctoral researchers, students, and guests from industry and other laboratories who participated in LLNL's computational mission under the auspices of the ISCR during FY 2005.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,005
score de la tête « metaresearch » (Gemma)0,002
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesCharge utile insuffisante (le modèle a refusé de juger)
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Autre · Signal consensuel: Autre
Score de désaccord entre enseignants0,050
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0050,002
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0060,001

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.

Tête enseignante Opus0,234
Tête enseignante GPT0,520
Écart entre enseignants0,286 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

Devis d'étudeSans objet
Domainenon disponible
GenreAutre

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2006
Routes d'admission1
Résumé présentoui

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