Large-scale data processing, made possible by the dissemination of very powerful computers, is a formidable tool for many fields of research.\u00a0 Supercomputers with the capacity to process millions of lines of code per second are being used in the most diverse fields of knowledge to solve problems and make projections.<\/p>\n
Brazil\u2019s status among the world ranking of the 500 highest-performing computers is the topic of the report on page 37<\/a>.\u00a0 Three of the four Brazilian systems on the list are part of a cluster located in a charming building inspired by the hat of Santos Dumont, at the facilities of the National Scientific Computing Laboratory (LNCC), in Petr\u00f3polis, Rio de Janeiro State.\u00a0 The fourth is located at the Center for Integrated Manufacturing and Technology of the National Industrial Training Service (SENAI-CIMATEC), in Salvador, Bahia.<\/p>\n The current state of Brazil\u2019s supercomputing is rather gloomy.\u00a0 In 2004, Brazil achieved a 9th<\/sup> place ranking, with nine systems in operation. Today it finds itself in 17th<\/sup> place. Besides the setback in terms of international comparisons, another source of concern identified in the report is the under-utilization of supercomputers that are currently operating in Brazil, due in part to the high costs involved in their operation and maintenance.\u00a0 Essential for advancing science and developing technology, these systems require a well thought-out national policy of acquisition and use.<\/p>\n Supercomputers are used in a broad array of fields such as defense and health as well as in climate analysis \u2013 from forecasts of daily rainfall to the possibility of near-future temperature changes on Earth. This month\u2019s cover story<\/a>\u00a0discusses the findings of simulations conducted using two climate models processed on high-performance computers.<\/p>\n Initial computer models created to simulate earth\u2019s environment used only data on the physical elements of climate, such as water, air and sunlight.\u00a0 With advances in the models\u2019 data processing and programming capacity, it became possible to increase the degree of detail, estimating for example, how changes in the oceans\u2019 acidity caused by the increase in carbon dioxide in the air affect marine food chains.<\/p>\n One of the difficulties faced by researchers who work with climate modeling is an apparent paradox:\u00a0 since increasingly more variables are considered in the simulations, and each element is subject to variation, this could lead to greater variation in simulation results. A different forecast of temperature variation or rainfall pattern could result from simulations in models that focus on different elements.<\/p>\n The simulations presented in the cover story used two global climate models to basically predict the increase or decrease in temperature and rainfall volume.\u00a0 Along with these two models, a regional-scale model developed by the National Institute for Space Research was then run.\u00a0 The objective went beyond projecting an increase or reduction in rainfall and temperature in Brazil: researchers sought to predict the impact of these changes.\u00a0 More precipitation in forests can have negligible effects, while in metropolitan areas similar amounts of rainfall can be catastrophic.\u00a0 This is why data about economic, social and environmental conditions of all Brazilian municipalities were included. The resulting projections by the two simulations are similar for about 80% of the Brazilian territory, lending weight to the results.<\/p>\n An interesting and useful application of the capacity for processing large quantities of data is described in the report about the genealogy of Brazilian academics<\/a> conducted from information found in the CNPq\u2019s Lattes Platform. The federal data extracted from 4.5 million curricula were supplemented by information from databases compiled by Capes and the Brazilian Academy of Sciences.\u00a0 Besides being of historical and sociological interest, methodologies based on academic genealogies could be used in the future in the field of evaluation, where they can measure a researcher\u2019s influence on the training of younger generations.
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\nStarting with this issue, the magazine will be a little different:\u00a0 the Data and Projects section will now be made up exclusively of Data. Recently-approved research under the grant mechanisms Thematic Projects and Young Investigators will be highlighted on the Virtual Library page<\/a> of the FAPESP Documentation and Information Center.\u00a0 The BV, as we call it, is a reference source for research supported by the Foundation: as of 11\/5\/2016, it contained information about 89,841 research grants and 126,804 scholarships in Brazil and abroad awarded by FAPESP (www.bv.fapesp.br).<\/p>\n","protected":false},"excerpt":{"rendered":"Computers and data","protected":false},"author":586,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_exactmetrics_skip_tracking":false,"_exactmetrics_sitenote_active":false,"_exactmetrics_sitenote_note":"","_exactmetrics_sitenote_category":0,"footnotes":""},"categories":[158],"tags":[],"coauthors":[1549],"class_list":["post-237764","post","type-post","status-publish","format-standard","hentry","category-editorial-en"],"acf":[],"_links":{"self":[{"href":"https:\/\/revistapesquisa.fapesp.br\/en\/wp-json\/wp\/v2\/posts\/237764","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/revistapesquisa.fapesp.br\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/revistapesquisa.fapesp.br\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/revistapesquisa.fapesp.br\/en\/wp-json\/wp\/v2\/users\/586"}],"replies":[{"embeddable":true,"href":"https:\/\/revistapesquisa.fapesp.br\/en\/wp-json\/wp\/v2\/comments?post=237764"}],"version-history":[{"count":0,"href":"https:\/\/revistapesquisa.fapesp.br\/en\/wp-json\/wp\/v2\/posts\/237764\/revisions"}],"wp:attachment":[{"href":"https:\/\/revistapesquisa.fapesp.br\/en\/wp-json\/wp\/v2\/media?parent=237764"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/revistapesquisa.fapesp.br\/en\/wp-json\/wp\/v2\/categories?post=237764"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/revistapesquisa.fapesp.br\/en\/wp-json\/wp\/v2\/tags?post=237764"},{"taxonomy":"author","embeddable":true,"href":"https:\/\/revistapesquisa.fapesp.br\/en\/wp-json\/wp\/v2\/coauthors?post=237764"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}