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New parallel computing algorithm of molecular dynamics for extremely huge scale biological systems.

Jaewoon JungChigusa KobayashiKento KasaharaCheng TanAkiyoshi KurodaKazuo MinamiShigeru IshidukiTatsuo NishikiHikaru InoueYutaka IshikawaMichael FeigYuji Sugita
Published in: Journal of computational chemistry (2020)
In this paper, we address high performance extreme-scale molecular dynamics (MD) algorithm in the GENESIS software to perform cellular-scale molecular dynamics (MD) simulations with more than 100,000 CPU cores. It includes (1) the new algorithm of real-space nonbonded interactions maximizing the performance on ARM CPU architecture, (2) reciprocal-space nonbonded interactions minimizing communicational cost, (3) accurate temperature/pressure evaluations that allows a large time step, and (4) effective parallel file inputs/outputs (I/O) for MD simulations of extremely huge systems. The largest system that contains 1.6 billion atoms was simulated using MD with a performance of 8.30 ns/day on Fugaku supercomputer. It extends the available size and time of MD simulations to answer unresolved questions of biomacromolecules in a living cell.
Keyphrases
  • molecular dynamics
  • density functional theory
  • machine learning
  • deep learning
  • single cell
  • climate change
  • neural network
  • cell therapy
  • mesenchymal stem cells
  • high resolution
  • zika virus
  • dengue virus