Sharing a conceptual model of grid resources and services

Grid technologies aim at enabling a coordinated resource-sharing and problem-solving capabilities over local and wide area networks and span locations, organizations, machine architectures and software boundaries. The heterogeneity of involved resources and the need for interoperability among different grid middlewares require the sharing of a common information model. Abstractions of different flavors of resources and services and conceptual schemas of domain specific entities require a collaboration effort in order to enable a coherent information services cooperation. With this paper, we present the result of our experience in grid resources and services modelling carried out within the Grid Laboratory Uniform Environment (GLUE) effort, a joint US and EU High Energy Physics projects collaboration towards grid interoperability. The first implementation-neutral agreement on services such as batch computing and storage manager, resources such as the hierarchy cluster, sub-cluster, host and the storage library are presented. Design guidelines and operational results are depicted together with open issues and future evolutions.Comment: 4 pages, 0 figures, CHEP 200

Optimization of Italian CMS Computing Centers via MIUR funded Research Projects

In 2012, 14 Italian Institutions participating LHC Experiments (10 in CMS) have won a grant from the Italian Ministry of Research (MIUR), to optimize Analysis activities and in general the Tier2/Tier3 infrastructure. A large range of activities is actively carried on: they cover data distribution over WAN, dynamic provisioning for both scheduled and interactive processing, design and development of tools for distributed data analysis, and tests on the porting of CMS software stack to new highly performing / low power architectures

Improvements of LHC data analysis techniques at Italian WLCG sites. Case-study of the transfer of this technology to other research areas

In 2012, 14 Italian institutions participating in LHC Experiments won a grant from the Italian Ministry of Research (MIUR), with the aim of optimising analysis activities, and in general the Tier2/Tier3 infrastructure. We report on the activities being researched upon, on the considerable improvement in the ease of access to resources by physicists, also those with no specific computing interests. We focused on items like distributed storage federations, access to batch-like facilities, provisioning of user interfaces on demand and cloud systems. R&D on next-generation databases, distributed analysis interfaces, and new computing architectures was also carried on. The project, ending in the first months of 2016, will produce a white paper with recommendations on best practices for data-analysis support by computing centers

Penilaian Kinerja Keuangan Koperasi di Kabupaten Pelalawan

This paper describe development and financial performance of cooperative in District Pelalawan among 2007 - 2008. Studies on primary and secondary cooperative in 12 sub-districts. Method in this stady use performance measuring of productivity, efficiency, growth, liquidity, and solvability of cooperative. Productivity of cooperative in Pelalawan was highly but efficiency still low. Profit and income were highly, even liquidity of cooperative very high, and solvability was good

Severe early onset preeclampsia: short and long term clinical, psychosocial and biochemical aspects

Preeclampsia is a pregnancy specific disorder commonly defined as de novo hypertension and proteinuria after 20 weeks gestational age. It occurs in approximately 3-5% of pregnancies and it is still a major cause of both foetal and maternal morbidity and mortality worldwide1. As extensive research has not yet elucidated the aetiology of preeclampsia, there are no rational preventive or therapeutic interventions available. The only rational treatment is delivery, which benefits the mother but is not in the interest of the foetus, if remote from term. Early onset preeclampsia (<32 weeks’ gestational age) occurs in less than 1% of pregnancies. It is, however often associated with maternal morbidity as the risk of progression to severe maternal disease is inversely related with gestational age at onset2. Resulting prematurity is therefore the main cause of neonatal mortality and morbidity in patients with severe preeclampsia3. Although the discussion is ongoing, perinatal survival is suggested to be increased in patients with preterm preeclampsia by expectant, non-interventional management. This temporising treatment option to lengthen pregnancy includes the use of antihypertensive medication to control hypertension, magnesium sulphate to prevent eclampsia and corticosteroids to enhance foetal lung maturity4. With optimal maternal haemodynamic status and reassuring foetal condition this results on average in an extension of 2 weeks. Prolongation of these pregnancies is a great challenge for clinicians to balance between potential maternal risks on one the eve hand and possible foetal benefits on the other. Clinical controversies regarding prolongation of preterm preeclamptic pregnancies still exist – also taking into account that preeclampsia is the leading cause of maternal mortality in the Netherlands5 - a debate which is even more pronounced in very preterm pregnancies with questionable foetal viability6-9. Do maternal risks of prolongation of these very early pregnancies outweigh the chances of neonatal survival? Counselling of women with very early onset preeclampsia not only comprises of knowledge of the outcome of those particular pregnancies, but also knowledge of outcomes of future pregnancies of these women is of major clinical importance. This thesis opens with a review of the literature on identifiable risk factors of preeclampsia

Progetto CloudVeneto.it - Status Report

Dalla fine del 2015 è attiva e a disposizione degli utenti dell’Università di Padova una infrastruttura di calcolo chiamata CloudVeneto.it. Si tratta di un servizio Cloud di tipo IaaS (Infrastructure as a Service), che utilizza il middleware OpenStack ed è stata realizzata mettendo a frutto finanziamenti universitari e l’esperienza acquisita negli ultimi anni dal gruppo Cloud dell’INFN di Padova e Legnaro. CloudVeneto.it permette agli utenti di istanziare con pochi comandi le Virtual Machine che possono poi essere utilizzate per le proprie esigenze di calcolo. Le Virtual Machine possono essere impiegate in diversi modi, permettendo ad esempio: ● l’esecuzione di applicazioni interattive, ● il dispiegamento di servizi accessibili da remoto, ● la configurazione di cluster per l’esecuzione di istanze multiple di applicazioni di calcolo in modalità batch, ● l’esecuzione di applicazioni di calcolo parallelo che richiedono l’impiego simultaneo di più macchine virtuali. Per l’utente diventa così possibile configurare all’occorrenza e con facilità sistemi di calcolo anche complessi, personalizzati per le proprie esigenze e in grado di velocizzare drasticamente i tempi di esecuzione. Il sistema attualmente mette a disposizione 240 core fisici (corrispondenti a circa 1900 Virtual CPU) e circa 70 TB di storage, che può essere acceduto dalle Virtual Machine istanziate nella Cloud. I servizi di CloudVeneto.it sono stati configurati in alta affidabilità , per assicurarne la massima disponibilità, anche in presenza di guasti o malfunzionamenti di singoli componenti. I servizi inoltre sono stati resi sicuri attraverso l’adozione della tecnologia SSL. E` possibile accedere alle funzionalità di CloudVeneto.it attraverso command line tool, o attraverso una dashboard web-based, autenticandosi attraverso il sistema di Single Sign-On (SSO) dell’Università di Padova o l’Identity Provider dell’INFN (INFN-AAI). Dopo alcuni mesi di utilizzo da parte di alcuni utenti dei dipartimenti coinvolti, l’infrastruttura è ormai entrata in funzionamento a regime e gli utenti possono beneficiare, oltre che della documentazione messa a disposizione, anche del supporto dei sistemisti dell’Università e dell’INFN

Search for dijet resonances in proton-proton collisions at root s=13 TeV and constraints on dark matter and other models

Correction: DOI:10.1016/j.physletb.2017.09.029Peer reviewe