High-Performance Computing<\/strong> (HPC) has proven to be a strong driver for science and technology development, and is increasingly considered indispensable for most scientific disciplines.<\/strong> HPC is making a difference in key topics of great interest such as climate change, personalised medicine, engineering, astronomy, education, economics, industry and public policy, becoming a pillar for the development of any country, and to which the great powers are giving strategic importance and investing billions of dollars<\/strong>, in competition without limits where data is the new gold.<\/p>\n

A country that does not have the computational capacity to solve its own problems will have no alternative but to try to acquire solutions provided by others. One of the most important aspects of sovereignty in the 21st century is the ability to produce mathematical models and to have the capacity to solve them. Today, the availability of computing power commensurate with one’s wealth exponentially increases a country’s capacity to produce knowledge. in the developed world, it is estimated that for every dollar invested in supercomputing, the return to society is of the order of US$<\/strong> 44(1)<\/b> and to the academic world US$ 30(2)<\/b>. For these reasons, HPC occupies an important place on the political and diplomatic agendas of developed countries.\u00a0<\/span><\/p>\n

In Latin America, investment in HPC is very low compared to what’s the US, Asia and Europe are doing. In order to quantify this difference, we present the tables below, which show the accumulated computing capacity in the ranking of the 500 most powerful supercomputers in the world – the TOP500(3) – (Table 1), and the local reality (Table 2). Other data are also included, such as the population (in millions), the number of researchers per 1,000 inhabitants (Res\/1000), the computing capacity per researcher (Gflops\/Res) and the computing capacity per US$ million of GPD. In Table 1, we have grouped the countries by geographical area. America appears as the area with the highest computing capacity, essentially due to the USA, which has almost 45% of the world’s computing capacity in the TOP500. It if followed by Asia and then Europe. Tis TOP500 list includes mainly academic research centres, but also industry ones, typically those used in applied research (many private ones do not wish to publish such information for obvious reasons). For example, in Brazil – which shows good computing capacity with 88,175 TFlops – the vast majority is in the hands of the oil industry and only about 3,000 TFlops are used for basic research. Countries listed in the TOP500 invest in HPC from a few TFlops per million GDP (Belgium 5, Spain 7, Bulgaria 8), through countries investing in the order of hundreds (Italy 176, Japan 151, USA 138), to even thousands, as is the case in Finland with 1,478. For those countries where we were able to find data on the number of researchers, these range from a few Gflops per researcher (Belgium 19, Spain 24, Hungary 52) to close to 1,000 GFlops, i.e. 1 TFlop (USA 970, Italy 966), with Finland surpassing this barrier with 4,647. Note that, unlike what happens locally, countries with a certain degree of development invest every 3-4 years in supercomputing, so the data we are showing will soon be updated and there will be variations in the list. For example, this year a new supercomputer will come into operation in Spain(4), which, with an investment of some 150 million euros, will give Spain one of the most powerful supercomputers in Europe – and the world.<\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n

Country<\/b><\/td>\n	Rpeak\u00a0<\/b><\/p>\n (TFlops)<\/b><\/td>\n	Population<\/b><\/p>\n (millions)<\/b><\/td>\n	Res\/1000<\/b><\/td>\n	GFlops\/Res<\/b><\/td>\n	Tflops\/M US$<\/b><\/td>\n<\/tr>\n
United States<\/b><\/td>\n	3.216.124<\/span><\/td>\n	335<\/span><\/td>\n	9.9<\/span><\/td>\n	969.7<\/span><\/td>\n	138.0<\/span><\/td>\n<\/tr>\n
Canada<\/b><\/td>\n	71.911<\/span><\/td>\n	39<\/span><\/td>\n	8.8<\/span><\/td>\n	209.5<\/span><\/td>\n	40.0<\/span><\/td>\n<\/tr>\n
Brazil<\/b><\/td>\n	88.175<\/span><\/td>\n	216<\/span><\/td>\n	1.1<\/span><\/td>\n	371.1\u00a0<\/span><\/td>\n	51.9<\/span><\/td>\n<\/tr>\n
AMERICA<\/b><\/td>\n	3.376.211<\/span><\/td>\n	590<\/span><\/td>\n	\u00a0<\/span><\/td>\n	\u00a0<\/span><\/td>\n	\u00a0<\/span><\/td>\n<\/tr>\n
\u00a0<\/b><\/td>\n	\u00a0<\/span><\/td>\n	\u00a0<\/span><\/td>\n	\u00a0<\/span><\/td>\n	\u00a0<\/span><\/td>\n	\u00a0<\/span><\/td>\n<\/tr>\n
China<\/b><\/td>\n	1.132.071<\/span><\/td>\n	1400<\/span><\/td>\n	\u00a0<\/span><\/td>\n	\u00a0<\/span><\/td>\n	67.4<\/span><\/td>\n<\/tr>\n
Japan<\/b><\/td>\n	815.667<\/span><\/td>\n	124<\/span><\/td>\n	10.0<\/span><\/td>\n	657.8<\/span><\/td>\n	151.0<\/span><\/td>\n<\/tr>\n
South Korea<\/b><\/td>\n	128.264<\/span><\/td>\n	52<\/span><\/td>\n	16.6<\/span><\/td>\n	148.6<\/span><\/td>\n	71.3<\/span><\/td>\n<\/tr>\n
Saudi Arabia<\/b><\/td>\n	98.982<\/span><\/td>\n	35<\/span><\/td>\n	\u00a0<\/span><\/td>\n	\u00a0<\/span><\/td>\n	141.4<\/span><\/td>\n<\/tr>\n
Taiwan<\/b><\/td>\n	19.562<\/span><\/td>\n	23<\/span><\/td>\n	\u00a0<\/span><\/td>\n	\u00a0<\/span><\/td>\n	21.7<\/span><\/td>\n<\/tr>\n
Singapore<\/b><\/td>\n	15.785<\/span><\/td>\n	6<\/span><\/td>\n	\u00a0<\/span><\/td>\n	\u00a0<\/span><\/td>\n	52.6<\/span><\/td>\n<\/tr>\n
Thailand<\/b><\/td>\n	13.773<\/span><\/td>\n	70<\/span><\/td>\n	\u00a0<\/span><\/td>\n	\u00a0<\/span><\/td>\n	27.5<\/span><\/td>\n<\/tr>\n
United Arab Emirates<\/b><\/td>\n	12.164<\/span><\/td>\n	10<\/span><\/td>\n	\u00a0<\/span><\/td>\n	\u00a0<\/span><\/td>\n	15.2<\/span><\/td>\n<\/tr>\n
India<\/b><\/td>\n	12.082<\/span><\/td>\n	1380<\/span><\/td>\n	\u00a0<\/span><\/td>\n	\u00a0<\/span><\/td>\n	4.0<\/span><\/td>\n<\/tr>\n
ASIA<\/b><\/td>\n	2.248.353<\/span><\/td>\n	3100<\/span><\/td>\n	\u00a0<\/span><\/td>\n	\u00a0<\/span><\/td>\n	\u00a0<\/span><\/td>\n<\/tr>\n
\u00a0<\/b><\/td>\n	\u00a0<\/span><\/td>\n	\u00a0<\/span><\/td>\n	\u00a0<\/span><\/td>\n	\u00a0<\/span><\/td>\n	\u00a0<\/span><\/td>\n<\/tr>\n
Finland<\/b><\/td>\n	443.391<\/span><\/td>\n	6<\/span><\/td>\n	15.9<\/span><\/td>\n	4647.7<\/span><\/td>\n	1478.0<\/span><\/td>\n<\/tr>\n
Italy<\/b><\/td>\n	370.262<\/span><\/td>\n	59<\/span><\/td>\n	6.5<\/span><\/td>\n	965.5<\/span><\/td>\n	176.3<\/span><\/td>\n<\/tr>\n
Germany<\/b><\/td>\n	331.231<\/span><\/td>\n	85<\/span><\/td>\n	10.1<\/span><\/td>\n	385.8<\/span><\/td>\n	78.9<\/span><\/td>\n<\/tr>\n
France<\/b><\/td>\n	251.166<\/span><\/td>\n	65<\/span><\/td>\n	11.4<\/span><\/td>\n	339.0<\/span><\/td>\n	83.7<\/span><\/td>\n<\/tr>\n
Russia<\/b><\/td>\n	101.737<\/span><\/td>\n	145<\/span><\/td>\n	\u00a0<\/span><\/td>\n	\u00a0<\/span><\/td>\n	59.8<\/span><\/td>\n<\/tr>\n
United Kingdom<\/b><\/td>\n	92.563<\/span><\/td>\n	68<\/span><\/td>\n	9.6<\/span><\/td>\n	141.8<\/span><\/td>\n	29.9<\/span><\/td>\n<\/tr>\n
Netherlands<\/b><\/td>\n	56.740<\/span><\/td>\n	18<\/span><\/td>\n	10.6<\/span><\/td>\n	297.4<\/span><\/td>\n	56.7<\/span><\/td>\n<\/tr>\n
Switzerland<\/b><\/td>\n	38.600<\/span><\/td>\n	9<\/span><\/td>\n	9.4<\/span><\/td>\n	456.3<\/span><\/td>\n	48.3<\/span><\/td>\n<\/tr>\n
Sweden<\/b><\/td>\n	32.727<\/span><\/td>\n	10<\/span><\/td>\n	15.8<\/span><\/td>\n	207.1<\/span><\/td>\n	54.5<\/span><\/td>\n<\/tr>\n
Ireland<\/b><\/td>\n	26.320<\/span><\/td>\n	5<\/span><\/td>\n	10.6<\/span><\/td>\n	496.6<\/span><\/td>\n	65.8<\/span><\/td>\n<\/tr>\n
Luxembourg<\/b><\/td>\n	18.291<\/span><\/td>\n	0.6<\/span><\/td>\n	\u00a0<\/span><\/td>\n	\u00a0<\/span><\/td>\n	365.8<\/span><\/td>\n<\/tr>\n
Poland<\/b><\/td>\n	17.099<\/span><\/td>\n	38<\/span><\/td>\n	7.6<\/span><\/td>\n	59.2<\/span><\/td>\n	28.5<\/span><\/td>\n<\/tr>\n
Norway<\/b><\/td>\n	17.031<\/span><\/td>\n	6<\/span><\/td>\n	13.0<\/span><\/td>\n	218.3<\/span><\/td>\n	34.1<\/span><\/td>\n<\/tr>\n
Czech Republic<\/b><\/td>\n	12.914<\/span><\/td>\n	10<\/span><\/td>\n	8.3<\/span><\/td>\n	155.6<\/span><\/td>\n	43.0<\/span><\/td>\n<\/tr>\n
Spain<\/b><\/td>\n	10.296<\/span><\/td>\n	47<\/span><\/td>\n	7.4<\/span><\/td>\n	29.6<\/span><\/td>\n	7.4<\/span><\/td>\n<\/tr>\n
Slovenia<\/b><\/td>\n	10.047<\/span><\/td>\n	2<\/span><\/td>\n	9.9<\/span><\/td>\n	507.4<\/span><\/td>\n	167.5<\/span><\/td>\n<\/tr>\n
Austria<\/b><\/td>\n	6.809<\/span><\/td>\n	9<\/span><\/td>\n	11.6<\/span><\/td>\n	65.2<\/span><\/td>\n	13.6<\/span><\/td>\n<\/tr>\n
Bulgaria<\/b><\/td>\n	5.942<\/span><\/td>\n	6<\/span><\/td>\n	\u00a0<\/span><\/td>\n	\u00a0<\/span><\/td>\n	8.5<\/span><\/td>\n<\/tr>\n
Hungary<\/b><\/td>\n	4.669<\/span><\/td>\n	10<\/span><\/td>\n	9.0<\/span><\/td>\n	51.9<\/span><\/td>\n	23.3<\/span><\/td>\n<\/tr>\n
Belgium<\/b><\/td>\n	3.094<\/span><\/td>\n	12<\/span><\/td>\n	13.6<\/span><\/td>\n	19.0<\/span><\/td>\n	5.2<\/span><\/td>\n<\/tr>\n
EUROPA<\/b><\/td>\n	1.850.934<\/span><\/td>\n	610.6<\/span><\/td>\n	\u00a0<\/span><\/td>\n	\u00a0<\/span><\/td>\n	\u00a0<\/span><\/td>\n<\/tr>\n
<\/td>\n	<\/td>\n	<\/td>\n	<\/td>\n	<\/td>\n	<\/td>\n<\/tr>\n
OTHER<\/b><\/td>\n	\u00a0<\/span><\/td>\n	\u00a0<\/span><\/td>\n	\u00a0<\/span><\/td>\n	\u00a0<\/span><\/td>\n	\u00a0<\/span><\/td>\n<\/tr>\n
Australia<\/b><\/td>\n	60.177<\/span><\/td>\n	26<\/span><\/td>\n	\u00a0<\/span><\/td>\n	\u00a0<\/span><\/td>\n	40.1<\/span><\/td>\n<\/tr>\n
Morocco<\/b><\/td>\n	5.014<\/span><\/td>\n	39<\/span><\/td>\n	\u00a0<\/span><\/td>\n	\u00a0<\/span><\/td>\n	50.1<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n Table 1. HPC availability per researcher and relative to GDP in the TOP500 countries (includes HPC in industry).<\/strong><\/p>\n The local reality is far from this data. Table 2 shows data from Argentina, Brazil, Chile and Mexico. In Chile, the availability of computing power is 2-3 times less per researcher than in countries with less computing power in the OECD and up to 100 times less than a researcher in the US.<\/strong> In Chile, our investment measured in TFlops per million US$ of GDP is 166 times less than in the US; with respect to European countries that invest less in HPC it is 9 times less, and with respect to the European average (including Finland) it is 80 times less, i.e. the difference is considerable. It is clear that we need to close this gap. An investment go about 5 million dollars in HPC infrastructure in the next 5 years would close this gap by a factor of almost 20 times our computational capacity. However, returning to the example of Spain, the supercomputer it will have this year will offer 23 times more computing power than at present and, therefore, we will only maintain our relative distance. If we do not invest, the dap will increase by at least 23 times and will end up being huge. Therefore, we do not only need a one-time investment, but we need to ensure a regular investment. Some neighbouring countries are already investing significantly in supercomputing. This is the case in Argentina, where they are investing 7 million dollars (2 million for the datacenter and 5 million to buy a new supercomputer), which will increase their current capacities by almost 40 times(5).<\/p>\n\n\n\n\n\n\n\n Country<\/b><\/td>\n Rpeak\u00a0<\/b><\/p>\n (TFlops)<\/b><\/td>\n Population (millions)<\/b><\/td>\n Res\/1000<\/b><\/td>\n GFlops\/Res<\/b><\/td>\n Tflops\/M US$<\/b><\/td>\n<\/tr>\n Brazil*<\/b><\/td>\n 3.000<\/span><\/td>\n 216<\/span><\/td>\n 1.1\u00a0<\/span><\/td>\n 12.6<\/span><\/td>\n 1.8<\/span><\/td>\n<\/tr>\n Mexico<\/b><\/td>\n 2.200<\/span><\/td>\n 130<\/span><\/td>\n 1.2<\/span><\/td>\n 14.1<\/span><\/td>\n 1.8<\/span><\/td>\n<\/tr>\n Argentina<\/b><\/td>\n 400<\/span><\/td>\n 45<\/span><\/td>\n 1.2<\/span><\/td>\n 7.4\u00a0<\/span><\/td>\n 0.8<\/span><\/td>\n<\/tr>\n Chile<\/b><\/td>\n 250<\/span><\/td>\n 20<\/span><\/td>\n 1.3<\/span><\/td>\n 9.6<\/span><\/td>\n 0.8<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n Table 2. HPC availability per researcher and relative to GDP in the region\u00a0(*only HPC capacity in academia is considered in this table).<\/strong><\/p>\n For the above reasons, we are working to convince the Chilean authorities that we must have greater funding<\/strong> and, more crucially, permanent state funding in HPC.\u00a0<\/strong>In relation to this, on July 6 we signed a collaboration agreement between 44 institutions with the support of the Ministry of Science to work on the creation of the National Supercomputing Laboratory(6). The agreement recognised that supercomputers are a critical infrastructure for Chile’s development, that it is necessary to centralise the requirements\/resources at the national level, obtain permanent funding from the State and create a new institutional framework to provide governance. In an unprecedented inter-institutional collaboration in Chile, the competition for HPC resources at the national level is eliminated ad the possibility of direct funding from the State is opened up without generating controversy.<\/p>\n Undoubtedly, supercomputing is a fundamental pillar for the development of any country<\/strong>, where increasing investment provides a strategic advantage, and in Latin America we should not be left behind.<\/strong><\/p>\n By NLHPC<\/a><\/p>\n  <\/p>\n References<\/strong><\/em><\/p>\n (1) Hyperion Research HPC Investments Bring High Returns<\/span><\/a><\/p>\n (2) EESI-2 Special Study To Measure And Model How Investments In HPC Can Create Financial ROI And Scientific Innovation In Europe\u00a0<\/span><\/a><\/p>\n (3) https:\/\/top500.org\/\u00a0<\/a><\/p>\n (4) https:\/\/www.lavanguardia.com\/ciencia\/20230129\/8713515\/llega-superordenador-marenostrum-5-bsc-barcelona.html<\/a><\/p>\n (5) https:\/\/www.hpcwire.com\/2022\/12\/15\/argentina-announces-new-supercomputer-for-national-science\/<\/a><\/p>\n (6) https:\/\/uchile.cl\/noticias\/187955\/44-instituciones-crearan-el-laboratorio-nacional-de-supercomputacion<\/a><\/p>\n  <\/p>\n","protected":false},"excerpt":{"rendered":" High-Performance Computing (HPC) has proven to be a strong driver for science and technology development, and is increasingly considered indispensable for most scientific disciplines. HPC is making a difference in key topics of great interest such as climate change, personalised medicine, engineering, astronomy, education, economics, industry and public policy, becoming a pillar for the development […]<\/p>\n","protected":false},"author":2,"featured_media":2740,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[2],"tags":[48,266,180,209],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/risc2-project.eu\/index.php?rest_route=\/wp\/v2\/posts\/2739"}],"collection":[{"href":"https:\/\/risc2-project.eu\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/risc2-project.eu\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/risc2-project.eu\/index.php?rest_route=\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/risc2-project.eu\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=2739"}],"version-history":[{"count":3,"href":"https:\/\/risc2-project.eu\/index.php?rest_route=\/wp\/v2\/posts\/2739\/revisions"}],"predecessor-version":[{"id":2760,"href":"https:\/\/risc2-project.eu\/index.php?rest_route=\/wp\/v2\/posts\/2739\/revisions\/2760"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/risc2-project.eu\/index.php?rest_route=\/wp\/v2\/media\/2740"}],"wp:attachment":[{"href":"https:\/\/risc2-project.eu\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=2739"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/risc2-project.eu\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=2739"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/risc2-project.eu\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=2739"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}