Editorial: Neuroscience, computing, performance, and benchmarks: Why it matters to neuroscience how fast we can compute

Frontiers in Neuroinformatics, vol. 17, pp. 1157418

Abstract

At the turn of the millennium the computational neuroscience community realized that neuroscience was in a software crisis: software development was no longer progressing as expected and reproducibility declined. The International Neuroinformatics Coordinating Facility (INCF) was inaugurated in 2007 as an initiative to improve this situation. The INCF has since pursued its mission to help the development of standards and best practices. In a community paper published this very same year, Brette et al. tried to assess the state of the field and to establish a scientific approach to simulation technology, addressing foundational topics, such as which simulation schemes are best suited for the types of models we see in neuroscience. In 2015, a Frontiers Research Topic “Python in neuroscience” by Muller et al. triggered and documented a revolution in the neuroscience community, namely in the usage of the scripting language Python as a common language for interfacing with simulation codes and connecting between applications. The review by Einevoll et al. documented that simulation tools have since further matured and become reliable research instruments used by many scientific groups for their respective questions. Open source and community standard simulators today allow research groups to focus on their scientific questions and leave the details of the computational work to the community of simulator developers. A parallel development has occurred, which has been barely visible in neuroscientific circles beyond the community of simulator developers: Supercomputers used for large and complex scientific calculations have increased their performance from ~10 TeraFLOPS (1013 floating point operations per second) in the early 2000s to above 1 ExaFLOPS (1018 floating point operations per second) in the year 2022. This represents a 100,000-fold increase in our computational capabilities, or almost 17 doublings of computational capability in 22 years. Moore's law (the observation that it is economically viable to double the number of transistors in an integrated circuit every other 18–24 months) explains a part of this; our ability and willingness to build and operate physically larger computers, explains another part. It should be clear, however, that such a technological advancement requires software adaptations and under the hood, simulators had to reinvent themselves and change substantially to embrace this technological opportunity. It actually is quite remarkable that—apart from the change in semantics for the parallelization—this has mostly happened without the users knowing. The current Research Topic was motivated by the wish to assemble an update on the state of neuroscientific software (mostly simulators) in 2022, to assess whether we can see more clearly which scientific questions can (or cannot) be asked due to our increased capability of simulation, and also to anticipate whether and for how long we can expect this increase of computational capabilities to continue.

Authors 6

1. James B. Aimone

   Sandia National Laboratories

   Affiliation as printed

   Neural Exploration and Research Laboratory, Center for Computing Research, Sandia National Laboratories, Albuquerque, NM, United States

   Neural Exploration and Research Laboratory, Center for Computing Research, Sandia National Laboratories, United States

2. Omar Awile

   École Polytechnique Fédérale de Lausanne

   Affiliation as printed

   Blue Brain Project, École Polytechnique Fédérale de Lausanne, Geneva, Switzerland

   Blue Brain Project, École Polytechnique Fédérale de Lausanne, Switzerland

3. Markus Diesmann Aachen Department of Psychiatry, Psychotherapy and Psychosomatics Department of Physics School of Medicine Faculty 1

   RWTH Aachen University · Forschungszentrum Jülich · Jülich Aachen Research Alliance

   Affiliation as printed

   Department of Physics, Faculty 1, RWTH Aachen University, Aachen, Germany

   Department of Psychiatry, Psychotherapy and Psychosomatics, School of Medicine, RWTH Aachen University, Aachen, Germany

   Institute of Neuroscience and Medicine and Institute for Advanced Simulation and JARA-Institute Brain Structure-Function Relationships, Jülich Research Centre, Jülich, Germany

   Department of Physics, Faculty 1, RWTH Aachen University, Germany

   Department of Psychiatry, Psychotherapy and Psychosomatics, School of Medicine, RWTH Aachen University, Germany

   Institute of Neuroscience and Medicine and Institute for Advanced Simulation and JARA-Institute Brain Structure-Function Relationships, Jülich Research Centre, Germany

4. James C. Knight

   University of Sussex

   Affiliation as printed

   School of Engineering and Informatics, University of Sussex, Brighton, United Kingdom

   School of Engineering and Informatics, University of Sussex, United Kingdom

5. Thomas Nowotny

   University of Sussex

   Affiliation as printed

   School of Engineering and Informatics, University of Sussex, Brighton, United Kingdom

   School of Engineering and Informatics, University of Sussex, United Kingdom

6. Felix Schürmann corresponding

   École Polytechnique Fédérale de Lausanne

   Affiliation as printed

   Blue Brain Project, École Polytechnique Fédérale de Lausanne, Geneva, Switzerland

   Blue Brain Project, École Polytechnique Fédérale de Lausanne, Switzerland