Performance studies of the CMS distributed analysis system in the associated Higgs boson production with top quarks

L'obiettivo di questa tesi è studiare la fattibilità dello studio della produzione associata ttH del bosone di Higgs con due quark top nell'esperimento CMS, e valutare le funzionalità e le caratteristiche della prossima generazione di toolkit per l'analisi distribuita a CMS (CRAB versione 3) per effettuare tale analisi. Nel settore della fisica del quark top, la produzione ttH è particolarmente interessante, soprattutto perchè rappresenta l'unica opportunità di studiare direttamente il vertice t-H senza dover fare assunzioni riguardanti possibili contributi dalla fisica oltre il Modello Standard. La preparazione per questa analisi è cruciale in questo momento, prima dell'inizio del Run-2 dell'LHC nel 2015. Per essere preparati a tale studio, le implicazioni tecniche di effettuare un'analisi completa in un ambito di calcolo distribuito come la Grid non dovrebbero essere sottovalutate. Per questo motivo, vengono presentati e discussi un'analisi dello stesso strumento CRAB3 (disponibile adesso in versione di pre-produzione) e un confronto diretto di prestazioni con CRAB2. Saranno raccolti e documentati inoltre suggerimenti e consigli per un team di analisi che sarà eventualmente coinvolto in questo studio. Nel Capitolo 1 è introdotta la fisica delle alte energie a LHC nell'esperimento CMS. Il Capitolo 2 discute il modello di calcolo di CMS e il sistema di analisi distribuita della Grid. Nel Capitolo 3 viene brevemente presentata la fisica del quark top e del bosone di Higgs. Il Capitolo 4 è dedicato alla preparazione dell'analisi dal punto di vista degli strumenti della Grid (CRAB3 vs CRAB2). Nel capitolo 5 è presentato e discusso uno studio di fattibilità per un'analisi del canale ttH in termini di efficienza di selezione.

Evaluation of a cloud infrastructure for the CMS distributed data analysis in the top quark sector at the LHC

Nella fisica delle particelle, onde poter effettuare analisi dati, è necessario disporre di una grande capacità di calcolo e di storage. LHC Computing Grid è una infrastruttura di calcolo su scala globale e al tempo stesso un insieme di servizi, sviluppati da una grande comunità di fisici e informatici, distribuita in centri di calcolo sparsi in tutto il mondo. Questa infrastruttura ha dimostrato il suo valore per quanto riguarda l'analisi dei dati raccolti durante il Run-1 di LHC, svolgendo un ruolo fondamentale nella scoperta del bosone di Higgs. Oggi il Cloud computing sta emergendo come un nuovo paradigma di calcolo per accedere a grandi quantità di risorse condivise da numerose comunità scientifiche. Date le specifiche tecniche necessarie per il Run-2 (e successivi) di LHC, la comunità scientifica è interessata a contribuire allo sviluppo di tecnologie Cloud e verificare se queste possano fornire un approccio complementare, oppure anche costituire una valida alternativa, alle soluzioni tecnologiche esistenti. Lo scopo di questa tesi è di testare un'infrastruttura Cloud e confrontare le sue prestazioni alla LHC Computing Grid. Il Capitolo 1 contiene un resoconto generale del Modello Standard. Nel Capitolo 2 si descrive l'acceleratore LHC e gli esperimenti che operano a tale acceleratore, con particolare attenzione all’esperimento CMS. Nel Capitolo 3 viene trattato il Computing nella fisica delle alte energie e vengono esaminati i paradigmi Grid e Cloud. Il Capitolo 4, ultimo del presente elaborato, riporta i risultati del mio lavoro inerente l'analisi comparata delle prestazioni di Grid e Cloud.

Integrating mobile devices into a scalable Grid Computing architecture designed to perform distributed computations

The idea of Grid Computing originated in the nineties and found its concrete applications in contexts like the SETI@home project where a lot of computers (offered by volunteers) cooperated, performing distributed computations, inside the Grid environment analyzing radio signals trying to find extraterrestrial life. The Grid was composed of traditional personal computers but, with the emergence of the first mobile devices like Personal Digital Assistants (PDAs), researchers started theorizing the inclusion of mobile devices into Grid Computing; although impressive theoretical work was done, the idea was discarded due to the limitations (mainly technological) of mobile devices available at the time. Decades have passed, and now mobile devices are extremely more performant and numerous than before, leaving a great amount of resources available on mobile devices, such as smartphones and tablets, untapped. Here we propose a solution for performing distributed computations over a Grid Computing environment that utilizes both desktop and mobile devices, exploiting the resources from day-to-day mobile users that alternatively would end up unused. The work starts with an introduction on what Grid Computing is, the evolution of mobile devices, the idea of integrating such devices into the Grid and how to convince device owners to participate in the Grid. Then, the tone becomes more technical, starting with an explanation on how Grid Computing actually works, followed by the technical challenges of integrating mobile devices into the Grid. Next, the model, which constitutes the solution offered by this study, is explained, followed by a chapter regarding the realization of a prototype that proves the feasibility of distributed computations over a Grid composed by both mobile and desktop devices. To conclude future developments and ideas to improve this project are presented.

Grid computing solutions for distributed repositories of protein folding and unfolding simulations

The P-found protein folding and unfolding simulation repository is designed to allow scientists to perform analyses across large, distributed simulation data sets. There are two storage components in P-found: a primary repository of simulation data and a data warehouse. Here we demonstrate how grid technologies can support multiple, distributed P-found installations. In particular we look at two aspects, first how grid data management technologies can be used to access the distributed data warehouses; and secondly, how the grid can be used to transfer analysis programs to the primary repositories --- this is an important and challenging aspect of P-found because the data volumes involved are too large to be centralised. The grid technologies we are developing with the P-found system will allow new large data sets of protein folding simulations to be accessed and analysed in novel ways, with significant potential for enabling new scientific discoveries.

Use of scenario analysis in studying emerging technology – Case Grid computing

Tutkimuksen selvitettiin miten skenaarioanalyysia voidaan käyttää uuden teknologian tutkimisessa. Työssä havaittiin, että skenaarioanalyysin soveltuvuuteen vaikuttaa eniten teknologisen muutoksen taso ja saatavilla olevan tiedon luonne. Skenaariomenetelmä soveltuu hyvin uusien teknologioiden tutkimukseen erityisesti radikaalien innovaatioiden kohdalla. Syynä tähän on niihin liittyvä suuri epävarmuus, kompleksisuus ja vallitsevan paradigman muuttuminen, joiden takia useat muut tulevaisuuden tutkimuksen menetelmät eivät ole tilanteessa käyttökelpoisia. Työn empiirisessä osiossa tutkittiin hilaverkkoteknologian tulevaisuutta skenaarioanalyysin avulla. Hilaverkot nähtiin mahdollisena disruptiivisena teknologiana, joka radikaalina innovaationa saattaa muuttaa tietokonelaskennan nykyisestä tuotepohjaisesta laskentakapasiteetin ostamisesta palvelupohjaiseksi. Tällä olisi suuri vaikutus koko nykyiseen ICT-toimialaan erityisesti tarvelaskennan hyödyntämisen ansiosta. Tutkimus tarkasteli kehitystä vuoteen 2010 asti. Teorian ja olemassa olevan tiedon perusteella muodostettiin vahvaan asiantuntijatietouteen nojautuen neljä mahdollista ympäristöskenaariota hilaverkoille. Skenaarioista huomattiin, että teknologian kaupallinen menestys on vielä monen haasteen takana. Erityisesti luottamus ja lisäarvon synnyttäminen nousivat tärkeimmiksi hilaverkkojen tulevaisuutta ohjaaviksi tekijöiksi.

A novel grid computing approach for probabilistic small signal analysis

Grid computing is an advanced technique for collaboratively solving complicated scientific problems using geographically and organisational dispersed computational, data storage and other recourses. Application of grid computing could provide significant benefits to all aspects of power system that involves using computers. Based on our previous research, this paper presents a novel grid computing approach for probabilistic small signal stability (PSSS) analysis in electric power systems with uncertainties. A prototype computing grid is successfully implemented in our research lab to carry out PSSS analysis on two benchmark systems. Comparing to traditional computing techniques, the gird computing has given better performances for PSSS analysis in terms of computing capacity, speed, accuracy and stability. In addition, a computing grid framework for power system analysis has been proposed based on the recent study.

RSA-Grid: A grid computing based framework for power system reliability and security analysis

Grid computing is an emerging technology for providing the high performance computing capability and collaboration mechanism for solving the collaborated and complex problems while using the existing resources. In this paper, a grid computing based framework is proposed for the probabilistic based power system reliability and security analysis. The suggested name of this computing grid is Reliability and Security Grid (RSA-Grid). Then the architecture of this grid is presented. A prototype system has been built for further development of grid-based services for power systems reliability and security assessment based on probabilistic techniques, which require high performance computing and large amount of memory. Preliminary results based on prototype of this grid show that RSA-Grid can provide the comprehensive assessment results for real power systems efficiently and economically.

P-found: grid-enabling distributed repositories of protein folding and unfolding simulations for data mining

The P-found protein folding and unfolding simulation repository is designed to allow scientists to perform data mining and other analyses across large, distributed simulation data sets. There are two storage components in P-found: a primary repository of simulation data that is used to populate the second component, and a data warehouse that contains important molecular properties. These properties may be used for data mining studies. Here we demonstrate how grid technologies can support multiple, distributed P-found installations. In particular, we look at two aspects: firstly, how grid data management technologies can be used to access the distributed data warehouses; and secondly, how the grid can be used to transfer analysis programs to the primary repositories — this is an important and challenging aspect of P-found, due to the large data volumes involved and the desire of scientists to maintain control of their own data. The grid technologies we are developing with the P-found system will allow new large data sets of protein folding simulations to be accessed and analysed in novel ways, with significant potential for enabling scientific discovery.

An Islanding Detection Method based on Impedance Estimation and Grid Identification for Grid-Tie Distributed Power Generation Systems

Power system policies are broadly on track to escalate the use of renewable energy resources in electric power generation. Integration of dispersed generation to the utility network not only intensifies the benefits of renewable generation but also introduces further advantages such as power quality enhancement and freedom of power generation for the consumers. However, issues arise from the integration of distributed generators to the existing utility grid are as significant as its benefits. The issues are aggravated as the number of grid-connected distributed generators increases. Therefore, power quality demands become stricter to ensure a safe and proper advancement towards the emerging smart grid. In this regard, system protection is the area that is highly affected as the grid-connected distributed generation share in electricity generation increases. Islanding detection, amongst all protection issues, is the most important concern for a power system with high penetration of distributed sources. Islanding occurs when a portion of the distribution network which includes one or more distributed generation units and local loads is disconnected from the remaining portion of the grid. Upon formation of a power island, it remains energized due to the presence of one or more distributed sources. This thesis introduces a new islanding detection technique based on an enhanced multi-layer scheme that shows superior performance over the existing techniques. It provides improved solutions for safety and protection of power systems and distributed sources that are capable of operating in grid-connected mode. The proposed active method offers negligible non-detection zone. It is applicable to micro-grids with a number of distributed generation sources without sacrificing the dynamic response of the system. In addition, the information obtained from the proposed scheme allows for smooth transition to stand-alone operation if required. The proposed technique paves the path towards a comprehensive protection solution for future power networks. The proposed method is converter-resident and all power conversion systems that are operating based on power electronics converters can benefit from this method. The theoretical analysis is presented, and extensive simulation results confirm the validity of the analytical work.

Sistemas distribuídos: serviços Grid Computing

A necessidade de poder computacional é crescente nas diversas áreas de actuação humana, tanto na indústria, como em ambientes académicos. Grid Computing permite a ligação de recursos computacionais dispersos de maneira a permitir a sua utilização mais eficaz, fornecendo aos utilizadores um acesso simplificado ao poder computacional de diversos sistemas. Os primeiros projectos de Grid Computing implicavam a ligação de máquinas paralelas ou aglomerados de alto desempenho e alto custo, disponíveis apenas em algumas instituições. Contrastando com o elevado custo dos super-computadores, os computadores pessoais e a Internet sofreram uma evolução significativa nos últimos anos. O uso de computadores dispersos em uma WAN pode representar um ambiente muito interessante para processamento de alto desempenho. Os sistemas em Grid fornecem a possibilidade de se utilizar um conjunto de computadores pessoais de modo a fornecer uma computação que utiliza recursos que de outra maneira estariam omissos. Este trabalho consiste no estudo de Grid Computing a nível de conceito e de arquitectura e numa análise ao seu estado actual hoje em dia. Como complemento foi desenvolvido um componente que permite o desenvolvimento de serviços para Grids (Grid Services) mais eficaz do que o modelo de suporte a serviços actualmente utilizado. Este componente é disponibilizado sob a forma um plug-in para a plataforma Eclipse IDE.

Private cloud computing platforms. Analysis and implementation in a Higher Education Institution

The constant evolution of the Internet and its increasing use and subsequent entailing to private and public activities, resulting in a strong impact on their survival, originates an emerging technology. Through cloud computing, it is possible to abstract users from the lower layers to the business, focusing only on what is most important to manage and with the advantage of being able to grow (or degrades) resources as needed. The paradigm of cloud arises from the necessity of optimization of IT resources evolving in an emergent and rapidly expanding and technology. In this regard, after a study of the most common cloud platforms and the tactic of the current implementation of the technologies applied at the Institute of Biomedical Sciences of Abel Salazar and Faculty of Pharmacy of Oporto University a proposed evolution is suggested in order adorn certain requirements in the context of cloud computing.