{"id":542,"date":"2021-09-02T12:44:31","date_gmt":"2021-09-02T12:44:31","guid":{"rendered":"http:\/\/cloud.ic.uff.br\/?page_id=542"},"modified":"2023-08-17T10:53:03","modified_gmt":"2023-08-17T10:53:03","slug":"2-wcloud-hpc","status":"publish","type":"page","link":"https:\/\/cloud.ic.uff.br\/index.php\/pt\/2-wcloud-hpc\/","title":{"rendered":"2\u00ba WCloud-HPC (Online)"},"content":{"rendered":"\n
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Venha participar do nosso 2\u00ba Workshop Virtual de Cloud e HPC (WCloud-HPC)!
Link de inscri\u00e7\u00e3o: clique aqui!<\/a><\/p>\n\n\n\n

O 2\u00ba WCloud-HPC faz parte da Escola de Inverno 2021<\/a> do Programa de P\u00f3s-Gradua\u00e7\u00e3o em Computa\u00e7\u00e3o (PPGC\/UFF).<\/p>\n\n\n\n

A Escola de Inverno do PPGC\/UFF tem como principal objetivo oferecer cursos e tutoriais sobre tecnologias, ferramentas, m\u00e9todos ou processos que possam contribuir para o desenvolvimento de pesquisas de mestrado e doutorado, nas diversas \u00e1reas de concentra\u00e7\u00e3o. Al\u00e9m do curso de Metodologia de Pesquisa em Computa\u00e7\u00e3o, que apresenta no\u00e7\u00f5es b\u00e1sicas de metodologias aplicadas \u00e0 pesquisa cient\u00edfica em computa\u00e7\u00e3o, juntamente com ferramentas de apoio, s\u00e3o oferecidos tutoriais e minicursos, que abordam t\u00f3picos complementares, e um ciclo de semin\u00e1rios que apresenta t\u00f3picos de pesquisa em Computa\u00e7\u00e3o.<\/p>\n\n\n\n

O evento seguir\u00e1 o hor\u00e1rio de Bras\u00edlia (GMT -3) e contar\u00e1 com as seguintes atividades:<\/p>\n\n\n\n

Cronograma de atividades para o primeiro dia (16\/09\/2021)<\/h2>\n\n\n\n
Hor\u00e1rio<\/th>Atividade<\/th><\/tr><\/thead>
13:00<\/td>Abertura<\/td><\/tr>
13:10<\/td>
Palestra: Efficient Data Management on a Cloud with Geo-Distributed Data Centers (Claude Tadonki<\/span>)<\/summary>

Abstract: Cloud computing has emerged as a flexible support for high-performance computing activities. There are several reasons or arguments for choosing this paradigm that mainly come from the standpoint of costs and technical safety. However, in any case, the main concern in high-performance computing is the runtime efficiency, which includes both the efficiency of the tasks and that of the corresponding data accesses. The latter is critical in the context of geographically distributed data centers because they are typically located in different places far from each other, which might imply a heavy network activity to have the data available at the right location whenever they are needed by the running tasks. One of the advantages of Cloud computing from the user standpoint is that, through the virtualization, explicit scheduling details are seamlessly managed on the provider\u2019s side. This is also the case of data management, which includes physical storage strategies and explicit migrations. In order to avoid the severe penalty of an inadequate default data management mechanism in the context of geo-distributed centers, it is worth considering a more skillful organization. We first propose an efficient data placement strategy by considering the characteristics of the tasks and their allocation onto the data centers. Then, we suggest a dynamic procedure for data provisioning using explicit redundancy and efficient choice of the providers. This talk will present the context and the problem, followed by our solutions and related thoughts.<\/p><\/details><\/em>Dispon\u00edvel em: https:\/\/youtu.be\/ZHt4__nog20<\/a><\/td><\/tr>

14:00<\/td>Coffee Break<\/td><\/tr>
14:30<\/td>Sess\u00e3o de Apresenta\u00e7\u00e3o de Trabalhos de P\u00f3s-Doutorado e P\u00f3s-Gradua\u00e7\u00e3o

– Understanding the I\/O bottlenecks of an HPC system<\/em> (Luan Teylo<\/span>)
– Towards Optimizing Computational Costs of Federated Learning in Clouds<\/em> (Rafaela Brum<\/span>)
– Fluid Computing<\/em> (Rui Rodrigues)
– Diff Sequences Spark: SARS-CoV-2 Sequences Comparison on Amazon EC2 Cloud<\/em> (Alan L. Nunes<\/span>)<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
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Cronograma de atividades para o segundo dia (17\/09\/2021)<\/h2>\n\n\n\n
Hor\u00e1rio<\/th>Atividade<\/th><\/tr><\/thead>
12:00<\/td>
Palestra: Towards Next-Generation Stream Processing Systems (Gabriele Mencagli)<\/summary>

Abstract: Data Stream Processing is an emerging computing paradigm characterized by the continuous analysis of data streams. Several application domains are of special interest for stream processing, such as financial trading, sensor networks, environmenal monitoring, network analysis and many others. Modern Stream Processing Systems are designed to exploit at best scale-out environments such as a Cloud, where horizontal scalability is addressed by spreading the applications in multiple nodes. However, there is the urgent need to target different computing environments like scale-up servers and machines equipped with co-processors (e.g., GPUs and FPGAs), both in the form of traditional hosts as well as resource-constrained edge and IoT embedded devices. This talk will try to explain the most promising research perspectives in this stream processing evolution, with a special focus on the ongoing research conducted for this purpose at the University of Pisa.<\/p><\/details><\/em>Dispon\u00edvel em: https:\/\/youtu.be\/PvqUTseL6PI<\/a><\/td><\/tr>

13:00<\/td>Break<\/td><\/tr>
14:00<\/td>Sess\u00e3o de Apresenta\u00e7\u00e3o de Trabalhos de P\u00f3s-Gradua\u00e7\u00e3o e Inicia\u00e7\u00e3o Cient\u00edfica

– Elasticidade de Recursos em Nuvens<\/em> (Daniel Sodr\u00e9 e Jos\u00e9 Victor Silva)
– Alinhamento M\u00faltiplo de Sequ\u00eancias Gen\u00e9ticas<\/em> (Mario Jo\u00e3o Junior)
– Moving HPC Workloads to the Cloud: DNA Sequence Comparison Case<\/em> (Diego Soares)<\/td><\/tr><\/tbody><\/table><\/figure>\n