Parallel implementation of the cascade mass-conserving semi-Lagrangian transport scheme

2016 ◽  
Vol 31 (1) ◽  
Author(s):  
Vladimir V. Shashkin ◽  
Mikhail A. Tolstykh
Keyword(s):  
Shared Memory ◽  
Large Time ◽  
Parallel Implementation ◽  
Distributed Shared Memory ◽  
Massively Parallel ◽  
Atmospheric Models ◽  
Efficient Treatment ◽  
Climate Simulations ◽  
The Cost ◽  
Future Growth

AbstractModern atmospheric models for climate simulations require accurate and efficient, locally mass-conservative and monotonic numerical schemes for treating the transport of atmospheric constituents. One of the ways to design such schemes is Finite-Volume Semi-Lagrangian approach (FVSL). FVSL schemes are characterised by the computational efficiency advantage due to the possibility of using large time-steps and efficient treatment of multiple transported quantities (tracers). This article presents massively parallel and multi-tracer efficient version of the recently developed 3D cascade FVSL transport scheme. Using hybrid distributed-shared memory parallelism with 1D MPI domain decomposition in latitude and OpenMP computations for longitude loops allows to use efficiently up to 1600 computational cores. We hope this number will grow with the future growth of the number of shared memory cores per computational node. Multi-tracer optimisations of the scheme (mostly, developing multi-tracer efficient monotonic filter) allow to reduce the cost of transporting additional tracer to 18–23% of running the scheme with one tracer.

A Massively Parallel Restriction-Smoothed Basis Multiscale Solver on Multi-Core and GPU Architectures

2021 ◽  
Author(s):  
Abdulrahman Manea
Keyword(s):  
Shared Memory ◽  
Parallel Implementation ◽  
Real Life ◽  
Parallel Architecture ◽  
Industrial Applications ◽  
Multiscale Methods ◽  
Basis Functions ◽  
Massively Parallel ◽  
Gpu Architectures ◽  
Gpu Implementation

Abstract Due to its simplicity, adaptability, and applicability to various grid formats, the restriction-smoothed basis multiscale method (MsRSB) (Møyne and Lie 2016) has received wide attention and has been extended to various flow problems in porous media. Unlike the standard multiscale methods, MsRSB relies on iterative smoothing to find the multiscale basis functions in an adaptive manner, giving it the ability to naturally adjust to various complex grid orientations often encountered in real-life industrial applications. In this work, we investigate the scalability of MsRSB on various state-of-the-art parallel architectures, including multi-core systems and GPUs. While MsRSB is — like most other multiscale methods — directly amenable to parallelization, the dependence on a smoother to find the basis functions creates unique control- and data-flow patterns. These patterns require careful design and implementation in parallel environments to achieve good scalability. We extend the work on parallel multiscale methods in Manea et al. (2016) and Manea and Almani (2019) to map the MsRSB special kernels to the shared-memory parallel multi-core and GPU architectures. The scalability of our optimized parallel MsRSB implementation is demonstrated using highly heterogeneous 3D problems derived from the SPE10 Benchmark (Christie and Blunt 2001). Those problems range in size from millions to tens of millions of cells. The multi-core implementation is benchmarked on a shared memory multi-core architecture consisting of two packages of Intel's Cascade Lake Xeon® Gold 6246 CPU, while the GPU implementation is benchmarked on a massively parallel architecture consisting of Nvidia Volta V100 GPUs. We compare the multi-core implementation to the GPU implementation for both the setup and solution stages. To the best of our knowledge, this is the first parallel implementation and demonstration of the versatile MsRSB method on the GPU architecture.

Massively Parallel Implementation of Steered Molecular Dynamics in Tinker-HP: Comparisons of Polarizable and Non-Polarizable Simulations of Realistic Systems

2019 ◽  
Author(s):  
Frédéric Célerse ◽  
Louis Lagardere ◽  
Étienne Derat ◽  
Jean-Philip Piquemal
Keyword(s):  
Molecular Dynamics ◽  
Parallel Implementation ◽  
Steered Molecular Dynamics ◽  
Massively Parallel

This paper is dedicated to the massively parallel implementation of Steered Molecular Dynamics in the Tinker-HP softwtare. It allows for direct comparisons of polarizable and non-polarizable simulations of realistic systems.

Massively Parallel Implementation of Steered Molecular Dynamics in Tinker-HP: Comparisons of Polarizable and Non-Polarizable Simulations of Realistic Systems

2019 ◽  
Author(s):  
Frédéric Célerse ◽  
Louis Lagardere ◽  
Étienne Derat ◽  
Jean-Philip Piquemal
Keyword(s):  
Molecular Dynamics ◽  
Parallel Implementation ◽  
Steered Molecular Dynamics ◽  
Massively Parallel

This paper is dedicated to the massively parallel implementation of Steered Molecular Dynamics in the Tinker-HP softwtare. It allows for direct comparisons of polarizable and non-polarizable simulations of realistic systems.

scholarly journals d4PDF: large-ensemble and high-resolution climate simulations for global warming risk assessment

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Masayoshi Ishii ◽  
Nobuhito Mori
Keyword(s):  
Risk Assessment ◽  
Global Warming ◽  
High Resolution ◽  
Climate Changes ◽  
Future Climate ◽  
Atmospheric Models ◽  
Large Ensemble ◽  
Past Climate ◽  
The Past ◽  
Climate Simulations

Abstract A large-ensemble climate simulation database, which is known as the database for policy decision-making for future climate changes (d4PDF), was designed for climate change risk assessments. Since the completion of the first set of climate simulations in 2015, the database has been growing continuously. It contains the results of ensemble simulations conducted over a total of thousands years respectively for past and future climates using high-resolution global (60 km horizontal mesh) and regional (20 km mesh) atmospheric models. Several sets of future climate simulations are available, in which global mean surface air temperatures are forced to be higher by 4 K, 2 K, and 1.5 K relative to preindustrial levels. Nonwarming past climate simulations are incorporated in d4PDF along with the past climate simulations. The total data volume is approximately 2 petabytes. The atmospheric models satisfactorily simulate the past climate in terms of climatology, natural variations, and extreme events such as heavy precipitation and tropical cyclones. In addition, data users can obtain statistically significant changes in mean states or weather and climate extremes of interest between the past and future climates via a simple arithmetic computation without any statistical assumptions. The database is helpful in understanding future changes in climate states and in attributing past climate events to global warming. Impact assessment studies for climate changes have concurrently been performed in various research areas such as natural hazard, hydrology, civil engineering, agriculture, health, and insurance. The database has now become essential for promoting climate and risk assessment studies and for devising climate adaptation policies. Moreover, it has helped in establishing an interdisciplinary research community on global warming across Japan.

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