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Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

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Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
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Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package
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Scalable Molecular Dynamics with NAMD on the Summit System.

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NAnoscale Molecular Dynamics (NAMD) software was optimized for high-performance computing on advanced supercomputers. These NAMD optimizations enable faster simulations of large biomolecular systems, advancing scientific discovery.

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Area of Science:

  • Computational Biology
  • Biophysics
  • High-Performance Computing

Background:

  • Molecular dynamics simulations are crucial for understanding complex biological systems.
  • Large-scale simulations demand significant computational resources.
  • NAnoscale Molecular Dynamics (NAMD) is a key application for these simulations.

Purpose of the Study:

  • To enhance NAMD performance on IBM's POWER9 and NVIDIA Volta V100 GPU-based supercomputers (Summit and Sierra).
  • To enable efficient, large-scale biomolecular simulations.
  • To present algorithm improvements and performance optimizations.

Main Methods:

  • Algorithm improvements and performance optimizations for NAMD.
  • Data layout changes for GPU acceleration and CPU vectorization.
  • Optimized FFT calculations, load balancing, and GPU offload efficiency.
  • Integration of PAMI support in Charm++ and stochastic velocity rescaling thermostat.

Main Results:

  • Achieved high performance of NAMD on Summit and Sierra supercomputers.
  • Demonstrated significant improvements in GPU acceleration and CPU vectorization.
  • Presented performance scaling results on early IBM Newell systems.

Conclusions:

  • Optimized NAMD effectively leverages heterogeneous processors for demanding simulations.
  • These advancements facilitate breakthroughs in understanding large biomolecular complexes.
  • The study showcases the power of supercomputing for molecular dynamics research.