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Cross-platform programming model for many-core lattice Boltzmann simulations.

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A new C++17 Parallel Algorithms strategy enables high-performance lattice Boltzmann (LB) simulations on CPUs and GPUs without specialized code. This hardware-agnostic approach achieves state-of-the-art results for fluid dynamics problems.

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Area of Science:

  • Computational fluid dynamics
  • High-performance computing
  • Parallel algorithms

Background:

  • Lattice Boltzmann (LB) simulations are crucial for fluid dynamics.
  • Hardware-specific implementations often limit code portability and performance.
  • Developing efficient, hardware-agnostic simulation strategies is a key challenge.

Purpose of the Study:

  • To introduce a novel, hardware-agnostic implementation strategy for LB simulations.
  • To demonstrate high performance on both homogeneous and heterogeneous many-core platforms (CPUs and GPUs).
  • To validate the approach using various LB schemes and collision models.

Main Methods:

  • Utilizing C++17 Parallel Algorithms exclusively, avoiding language extensions or vendor-specific code.
  • Implementing a single codebase that compiles and runs efficiently on diverse hardware.
  • Testing with six common implementation schemes and nine LB collision models.

Main Results:

  • Achieved massive performance gains on both many-core CPUs and GPUs.
  • Demonstrated state-of-the-art performance for a non-trivial fluid dynamics problem with a single code.
  • Showcased the versatility and good performance across different LB collision models and implementation schemes.

Conclusions:

  • A concise, generic LB implementation using C++17 Parallel Algorithms can match hardware-specific performance.
  • Modern many-core CPUs show significant performance gains, narrowing the gap with GPUs.
  • The open-source project stlbm provides a reusable, high-performance solution for the scientific community.