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      Is distributed computing dying, or just fading into the backdrop?

      news.movim.eu / ArsTechnica · Tuesday, 11 July, 2023 - 13:44 · 1 minute

    Image of a series of bar graphs in multiple colors.

    Enlarge / This image has a warm, nostalgic feel for many of us. (credit: SETI Institute )

    Distributed computing erupted onto the scene in 1999 with the release of SETI@home, a nifty program and screensaver (back when people still used those) that sifted through radio telescope signals for signs of alien life.

    The concept of distributed computing is simple enough: You take a very large project, slice it up into pieces, and send out individual pieces to PCs for processing. There is no inter-PC connection or communication; it’s all done through a central server. Each piece of the project is independent of the others; a distributed computing project wouldn't work if a process needed the results of a prior process to continue. SETI@home was a prime candidate for distributed computing: Each individual work unit was a unique moment in time and space as seen by a radio telescope.

    Twenty-one years later, SETI@home shut down, having found nothing. An incalculable amount of PC cycles and electricity wasted for nothing. We have no way of knowing all the reasons people quit (feel free to tell us in the comments section), but having nothing to show for it is a pretty good reason.

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      Citizen scientists help discover more than 1,000 new asteroids

      news.movim.eu / ArsTechnica · Monday, 16 May, 2022 - 17:24 · 1 minute

    This mosaic consists of 16 different data sets from the NASA/ESA Hubble Space Telescope that were studied as part of the Asteroid Hunter citizen science project. Each of these data sets was assigned a color based on the time sequence of exposures. The blue tones represent the first exposure in which the asteroid was captured, and the red tones represent the last.

    Enlarge / This mosaic consists of 16 different data sets from the NASA/ESA Hubble Space Telescope that were studied as part of the Asteroid Hunter citizen science project. Each of these data sets was assigned a color based on the time sequence of exposures. The blue tones represent the first exposure in which the asteroid was captured, and the red tones represent the last. (credit: ESA/Hubble & NASA, S. Kruk (ESA/ESTEC), Hubble Asteroid Hunter citizen science team, M. Zamani (ESA/Hubble) )

    On International Asteroid Day in 2019 , a group of research institutions launched a program that could make a deep impact on our knowledge of the diminutive bodies. Using citizen science to train a machine-learning algorithm, the Hubble Asteroid Hunter project identified more than 1,000 new asteroids; the discoveries could help scientists better understand the ring of heavenly bodies that primarily float between Mars and Jupiter.

    Asteroid Hunter is a collaborative effort between various groups, including the European Science and Technology Centre, the European Space Astronomy Centre’s Science Data Centre, the Zooniverse citizen science platform, and Google.

    Back in 2019, the researchers sent out a call for citizen scientists to collaborate on the crowd-sourced effort. Through the Zooniverse platform, 11,400 members of the public from around the world identified asteroid trails in 37,000 composite images taken by the Hubble Space Telescope between 2002 and 2021. The citizen scientists pored over the images for a year and identified more than 1,000 trails.

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