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             BSC’s Girona on MareNostrum’s Evolution and Delivering World-Class Compute from Barcelona


































        MareNostrum 5 supercomputer (Source: BSC-CNS)


        the major objective is to support science and   For example, it will run simulations for new   The second challenge is that the systems
        innovation in Spain and the rest of Europe.   aircraft designs.         are more complex today, requiring more
        Many of the users do applied research in   We’re seeing increasing demand in several   specialized components. Supercomputers
        collaboration with industrial players to   other domains. This includes energy in   are water-cooled, which means they need
        develop new methods and algorithms to make   general and nuclear fusion in particular.   hoses and pipes that withstand high tem-
        advances in science and technology.  For example, for wind farms, you have to   peratures and need to be certified. And the
          We’ve supported many applications that   model the behavior of the wind, which is very   components are very dense, which makes it
        achieve breakthroughs in science and tech-  complex; and for nuclear fusion, you have   difficult to build the bigger system and to
        nology. For example, we dedicated parts of   to analyze the behavior of plasma inside   remove and replace parts.
        the system to help develop vaccines for the   the reactor. The demand also includes large   Today’s supercomputers are unique. The
        coronavirus and to solve distribution prob-  language models and physical and chemical   cost of the systems is very high, and the
        lems to get the vaccines to people. Another   simulations and modelization at the highest   supplies are very scarce. MareNostrum 1
        example is the work the ESA [European Space   level. For example, personalized medicine   was based on the PowerPC 970, which was
        Agency] has been doing to build a 3D map of   requires more complex analysis to adapt   the processor used for Apple Macintosh
        the universe.                       treatment to a specific patient. To really ana-  at the time. It was very easy to buy those
          By increasing the computing power, system   lyze the behavior of an individual patient’s   general-purpose processors.
        memory and number of cores,         heart or to design drugs that are tailored for   Today, we’re using Intel Sapphire Rapids
        MareNostrum 5 will help solve more and   specific patients, exascale systems will be   with 56 cores, which, because it isn’t sold
        more complex problems. For example, climate   required.                 to the general market, is in limited supply—
        change simulations will be able to have                                 and the same is true for the Hopper 100.
        higher resolution, moving from representing   EE TIMES EUROPE: What are some of the   We have a total of 4,480 H100s, which is a
        phenomena on spatial scales of hundreds of   obstacles slowing down the evolution of   big part of what’s available on the market.
        kilometers to include processes occurring on   supercomputers?          When one is damaged and you need a new
        scales of a few kilometers, making predictions   Girona: Today, it’s really hard to get a   one, it might not be easy to get a replace-
        much more accurate and reliable.    supercomputer up to the state of production   ment quickly.
          It will also be possible to tackle much more   on time. From my experience with systems in   Cables are also a challenge. The number
        complex problems of artificial intelligence   the past, we set a date and managed to have   of cables and the different lengths make it
        and big data analysis. For example, it will be   the system in operation on that date. That is   very challenging to keep what you need in
        possible to generate massive language models   nearly impossible now.   stock. You have to find a reliable supplier to
        by training much larger neural networks with   The first challenge is that materials and   get the parts you need.
        hundreds of billions of parameters, using   capacities are lacking. Supply chains still   Another obstacle that slows things down is
        infinitely larger datasets than today.  haven’t recovered since the pandemic, and   the software that’s used on supercomputers.
          MareNostrum 5 specifically targets    different events around the world continue   We have been too focused on maintaining
        European medical research, which includes   to produce cascading effects. We saw this   legacy code, when instead we should be
        the design of new drugs, the development of   recently with the Suez Canal crisis and with   rethinking the ways we solve problems. If
        vaccines and the simulation of virus propa-  the earthquake in Taiwan in early April, when   you could change some of the algorithms to
        gation. We also expect it to be an essential   TSMC and other manufacturers temporarily   take advantage of the newer architectures,
        tool for materials science and engineering.   stopped production of semiconductors.  you could create new opportunities. ■


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