Search engine for discovering works of Art, research articles, and books related to Art and Culture
ShareThis
Javascript must be enabled to continue!

Coupled earth system modeling on heterogeneous HPC architectures with ParFlow in the Terrestrial Systems Modeling Platform

View through CrossRef
<p>Rapidly changing heterogeneous supercomputer architectures pose a great challenge to many scientific communities trying to leverage the latest technology in high-performance computing. Implementations that simultaneously result in a good performance and developer productivity while keeping the codebase adaptable and well maintainable in the long-term are of high importance. ParFlow, a widely used hydrologic model, achieves these attributes by hiding the architecture-dependent code in preprocessor macros (ParFlow embedded Domain Specific Language, eDSL) and leveraging NVIDIA's Unified Memory technology for memory management. The implementation results in very good weak scaling with up to 26x speedup when using four NVIDIA A100 GPUs per node compared to using the available 48 CPU cores. Good weak scaling is observed using hundreds of nodes on the new JUWELS Booster system at the Jülich Supercomputing Centre, Germany. Furthermore, it is possible to couple ParFlow with other earth system compartment models such as land surface and atmospheric models using the OASIS-MCT coupler library, which handles the data exchange between the different models. The ParFlow GPU implementation is fully compatible with the coupled implementation with little changes to the source code. Moreover, coupled simulations offer interesting load-balancing opportunities for optimal usage of the existing resources. For example, running ParFlow on GPU nodes, and another application component on CPU-only nodes, or efficiently distributing the CPU and GPU resources of a single node between the different application components may result in the best usage of heterogeneous architectures.</p>
Title: Coupled earth system modeling on heterogeneous HPC architectures with ParFlow in the Terrestrial Systems Modeling Platform
Description:
<p>Rapidly changing heterogeneous supercomputer architectures pose a great challenge to many scientific communities trying to leverage the latest technology in high-performance computing.
Implementations that simultaneously result in a good performance and developer productivity while keeping the codebase adaptable and well maintainable in the long-term are of high importance.
ParFlow, a widely used hydrologic model, achieves these attributes by hiding the architecture-dependent code in preprocessor macros (ParFlow embedded Domain Specific Language, eDSL) and leveraging NVIDIA's Unified Memory technology for memory management.
The implementation results in very good weak scaling with up to 26x speedup when using four NVIDIA A100 GPUs per node compared to using the available 48 CPU cores.
Good weak scaling is observed using hundreds of nodes on the new JUWELS Booster system at the Jülich Supercomputing Centre, Germany.
Furthermore, it is possible to couple ParFlow with other earth system compartment models such as land surface and atmospheric models using the OASIS-MCT coupler library, which handles the data exchange between the different models.
The ParFlow GPU implementation is fully compatible with the coupled implementation with little changes to the source code.
Moreover, coupled simulations offer interesting load-balancing opportunities for optimal usage of the existing resources.
For example, running ParFlow on GPU nodes, and another application component on CPU-only nodes, or efficiently distributing the CPU and GPU resources of a single node between the different application components may result in the best usage of heterogeneous architectures.
</p>.

Related Results

Theia can arrive late and be oxidized, but not if it is large compared to proto-Earth
Theia can arrive late and be oxidized, but not if it is large compared to proto-Earth
The Moon-forming impact was the most significant event during the accretion of Earth substantially establishing the physical and chemical states of the Earth-Moon system. In the ca...
Democratising HPC Training: co-creating an Industrial HPC Nano Online Course
Democratising HPC Training: co-creating an Industrial HPC Nano Online Course
Abstract Purpose: Disruptive technologies (AI, IoT, etc) unlock new frontiers of data-centric innovation. This increases the computational needs, pushing more and more comp...
Mapping the groundwater depth in Africa at high resolution (1 km²) based on the Parflow model and machine learning
Mapping the groundwater depth in Africa at high resolution (1 km²) based on the Parflow model and machine learning
Groundwater depth is the result of a balance between climatic conditions (rainfall, temperature, radiation, etc.), topography (slope and proximity of a river), land use, soil and s...
The ICON-ParFlow coupling: Integrating a continental-scale hydrological model into an Earth system model
The ICON-ParFlow coupling: Integrating a continental-scale hydrological model into an Earth system model
3D prognostic groundwater flow on a global scale is currently lacking in Earth system models. In order to prepare Earth system models for kilometer-scale simulations with integrate...
Accelerated hydrologic modeling: ParFlow GPU implementation
Accelerated hydrologic modeling: ParFlow GPU implementation
<p>  ParFlow is known as a numerical model that simulates the hydrologic cycle from the bedrock to the top of the plant canopy. The original codebase pro...
LLM as HPC Expert: Extending RAG Architecture for HPC Data
LLM as HPC Expert: Extending RAG Architecture for HPC Data
High-Performance Computing (HPC) is crucial for performing advanced computational tasks, yet their complexity often challenges users, particularly those unfamiliar with HPC-specifi...
HPC Cloud Architecture to Reduce HPC Workflow Complexity in Containerized Environments
HPC Cloud Architecture to Reduce HPC Workflow Complexity in Containerized Environments
The complexity of high-performance computing (HPC) workflows is an important issue in the provision of HPC cloud services in most national supercomputing centers. This complexity p...
A paradigm shift of HPC for geosciences: a novel HPC service model for geosciences applications
A paradigm shift of HPC for geosciences: a novel HPC service model for geosciences applications
(English) The Oil and Gas (O&G) industry ranks prominently among the leading commercial users of powerful supercomputers worldwide, as indicated by global High-Performance Comp...

Back to Top