Journal Article FZJ-2024-05083

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Impact of quantum and neuromorphic computing on biomolecular simulations: Current status and perspectives

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2024
Elsevier Amsterdam [u.a.]

Current opinion in structural biology 87, 102817 () [10.1016/j.sbi.2024.102817]

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Abstract: New high-performance computing architectures are becoming operative, in addition to exascale computers. Quantum computers (QC) solve optimization problems with unprecedented efficiency and speed, while neuromorphic hardware (NMH) simulates neural network dynamics. Albeit, at the moment, both find no practical use in all atom biomolecular simulations, QC might be exploited in the not-too-far future to simulate systems for which electronic degrees of freedom play a key and intricate role for biological function, whereas NMH might accelerate molecular dynamics simulations with low energy consumption. Machine learning and artificial intelligence algorithms running on NMH and QC could assist in the analysis of data and speed up research. If these implementations are successful, modular supercomputing could further dramatically enhance the overall computing capacity by combining highly optimized software tools into workflows, linking these architectures to exascale computers.

Classification:

Contributing Institute(s):
  1. Computational Biomedicine (INM-9)
  2. Jülich Supercomputing Center (JSC)
Research Program(s):
  1. 5241 - Molecular Information Processing in Cellular Systems (POF4-524) (POF4-524)
  2. 5111 - Domain-Specific Simulation & Data Life Cycle Labs (SDLs) and Research Groups (POF4-511) (POF4-511)
  3. JL SMHB - Joint Lab Supercomputing and Modeling for the Human Brain (JL SMHB-2021-2027) (JL SMHB-2021-2027)
  4. SLNS - SimLab Neuroscience (Helmholtz-SLNS) (Helmholtz-SLNS)
  5. DFG project 491111487 - Open-Access-Publikationskosten / 2022 - 2024 / Forschungszentrum Jülich (OAPKFZJ) (491111487) (491111487)

Appears in the scientific report 2024
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 Record created 2024-07-30, last modified 2025-02-03


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