CPU-only Version Research Articles

FluTAS: A GPU-accelerated finite difference code for multiphase flows

We present the Fluid Transport Accelerated Solver, FluTAS, a scalable GPU code for multiphase flows with thermal effects. The code solves the incompressible Navier-Stokes equation for two-fluid systems, with a direct FFT-based Poisson solver for the pressure equation. The interface between the two fluids is represented with the Volume of Fluid (VoF) method, which is mass conserving and well suited for complex flows thanks to its capacity of handling topological changes. The energy equation is explicitly solved and coupled with the momentum equation through the Boussinesq approximation. The code is conceived in a modular fashion so that different numerical methods can be used independently, the existing routines can be modified, and new ones can be included in a straightforward and sustainable manner. FluTAS is written in modern Fortran and parallelized using hybrid MPI/OpenMP in the CPU-only version and accelerated with OpenACC directives in the GPU implementation. We present different benchmarks to validate the code, and two large-scale simulations of fundamental interest in turbulent multiphase flows: isothermal emulsions in HIT and two-layer Rayleigh-Bénard convection. FluTAS is distributed through a MIT license and arises from a collaborative effort of several scientists, aiming to become a flexible tool to study complex multiphase flows. Program summaryProgram Title: : Fluid Transport Accelerated Solver, FluTAS.CPC Library link to program files:https://doi.org/10.17632/tp6k8wky8m.1Developer's repository link:https://github.com/Multiphysics-Flow-Solvers/FluTAS.git.Licensing provisions: MIT License.Programming language: Fortran 90, parallelized using MPI and slab/pencil decomposition, GPU accelerated using OpenACC directives.External libraries/routines: FFTW, cuFFT.Nature of problem: FluTAS is a GPU-accelerated numerical code tailored to perform interface resolved simulations of incompressible multiphase flows, optionally with heat transfer. The code combines a standard pressure correction algorithm with an algebraic volume of fluid method, MTHINC [1].Solution method: the code employs a second-order-finite difference discretization and solves the two-fluid Navier-Stokes equation using a projection method. It can be run both on CPU-architectures and GPU-architectures.

Performance Analysis of CP2K Code for Ab Initio Molecular Dynamics on CPUs and GPUs.

Using a realistic molecular catalyst system, we conduct scaling studies of ab initio molecular dynamics simulations using the popular CP2K code on both Intel Xeon CPU and NVIDIA V100 GPU architectures. Additional performance improvements were gained by finding more optimal process placement and affinity settings. Statistical methods were employed to understand performance changes in spite of the variability in runtime for each molecular dynamics timestep. Ideal conditions for CPU runs were found when running at least four MPI ranks per node, bound evenly across each socket. This study also showed that fully utilizing processing cores, with one OpenMP thread per core, performed better than when reserving cores for the system. The CPU-only simulations scaled at 70% or more of the ideal scaling up to 10 compute nodes, after which the returns began to diminish more quickly. Simulations on a single 40-core node with two NVIDIA V100 GPUs for acceleration achieved over 3.7× speedup compared to the fastest single 36-core node CPU-only version. These same GPU runs showed a 13% speedup over the fastest time achieved across five CPU-only nodes.

Palabos-npFEM: Software for the Simulation of Cellular Blood Flow (Digital Blood)

Palabos-npFEM is a computational framework for the simulation of blood flow with fully resolved constituents. The software resolves the trajectories and deformed state of blood cells, such as red blood cells and platelets, and the complex interaction between them. The tool combines the lattice Boltzmann solver Palabos for the simulation of blood plasma (fluid phase), a finite element method (FEM) solver for the resolution of blood cells (solid phase), and an immersed boundary method (IBM) for the coupling of the two phases. Palabos-npFEM provides, on top of a CPU-only version, the option to simulate the deformable bodies on GPUs, thus the code is tailored for the fastest supercomputers. The software is integrated in the Palabos core library, and is available on the Git repository https://gitlab.com/unigespc/palabos. It offers the possibility to simulate various setups, e.g. several geometries and blood parameters, and due to its modular design, it allows external solvers to readily replace the provided ones.

Petascale scramjet combustion simulation on the Tianhe-2 heterogeneous supercomputer

Abstract Combustion simulation is complex and computationally expensive as it involves integration of fundamental chemical kinetics and multidimensional Computational Fluid Dynamics (CFD) models. This paper presents our efforts porting a real-world supersonic combustion simulation application to the heterogeneous architecture consists of multi-core CPUs and Intel Many Integrated Core (MIC) coprocessors. Scalable OpenMP parallelization is added to make use of the large number of cores on CPUs and MIC coprocessors. Single thread performance optimizations are addressed to improve the computational efficiency. CPU and MIC collaborative algorithm, along with a series of techniques to improve the data transfer efficiency and load balance, are applied. Performance evaluation is performed on the Tianhe-2 supercomputer. The results show that on a single node, the optimized CPU-only version is 8.33 times faster than the baseline version, and the CPU + MIC heterogeneous version is again 3.07 times faster than the optimized CPU-only version. The resulting codes effectively scale to 5120 nodes (998,400 cores) on a mesh with 27.46 Giga cells. Given that the total number of floating-point operations is reduced by about 10 times after our optimizations, the heterogeneous version still achieves a sustained double precision floating-point performance of 0.46 Pflops on 5120 nodes. This demonstrates Petascale heterogeneous computing capabilities for real-world supersonic combustion problems.

Development of a hybrid parallel MCV-based high-order global shallow-water model

Utilization of high-order spatial discretizations is an important trend in developing global atmospheric models. As a competitive choice, the multi-moment constrained volume (MCV) method can achieve high accuracy while maintaining similar parallel scalability to classical finite volume methods. In this work, we introduce the development of a hybrid parallel MCV-based global shallow-water model on the cubed-sphere grid. Based on a sequential code, we perform parallelization on both the process and the thread levels. To enable process-level parallelism, we first decompose the six patches of the cubed-sphere in a same 2-D partition and then employ a conflict-free pipe-flow communication scheme for overlapping the halo exchange with computations. To further exploit the heterogeneous computing capacity of an Intel Xeon Phi accelerated supercomputer, we propose a guided panel-based inner---outer partition to distribute workload among the CPUs and the coprocessors. In addition to the above, thread-level parallelism along with various optimizations is done on both the multi-core CPU and the many-core accelerator. Numerical experiments are carried out to validate the correctness of the optimized parallel code and examine its parallel performance. Test results show that both the CPU-only and the hybrid codes scale well to hundreds of processes in terms of both the strong and weak scaling. In particular, the hybrid code can achieve a speedup of $$2.56\times $$2.56× as compared to the CPU-only version. In the largest run on a $$9216\,\times \,9216\,\times \,6$$9216×9216×6 mesh (1.5 billion unknowns), the hybrid code sustains an aggregative performance of 26.5 Tflops with 486 processes (33,534 cores).