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Benchmarking with a cross-platform open-source flow solver, PyFR
Submission navigation links for Knowledge Base Resources
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Submission information
Submission Number:
143
Submission ID:
3746
Submission UUID:
61c055a7-0870-4dc2-a2f5-33df225d3d14
Submission URI:
/form/resource
Created:
Tue, 05/30/2023 - 13:32
Completed:
Tue, 05/30/2023 - 13:32
Changed:
Fri, 03/14/2025 - 11:43
Remote IP address:
165.91.195.239
Submitted by:
Sambit Mishra
Language:
English
Is draft:
No
Webform:
Knowledge Base Resources
Approved
Yes
Title
Benchmarking with a cross-platform open-source flow solver, PyFR
Category
Tool
Tags
finite-element-analysis
,
benchmarking
,
parallelization
,
github
,
fluid-dynamics
,
openmpi
,
c++
,
cuda
,
mpi
Skill Level
Intermediate
Description
What is PyFR and how does it solve fluid flow problems?
PyFR is an open-source Computational Fluid Dynamics (CFD) solver that is based on Python and employs the high-order Flux Reconstruction technique. It effectively solves fluid flow problems by utilizing streaming architectures, making it suitable for complex fluid dynamics simulations.
How does PyFR achieve scalability on clusters with CPUs and GPUs?
PyFR achieves scalability by leveraging distributed memory parallelism through the Message Passing Interface (MPI). It implements persistent, non-blocking MPI requests using point-to-point (P2P) communication and organizes kernel calls to enable local computations while exchanging ghost states. This design approach allows PyFR to efficiently operate on clusters with heterogeneous architectures, combining CPUs and GPUs.
Why is PyFR valuable for benchmarking clusters?
PyFR's exceptional performance has been recognized by its selection as a finalist in the ACM Gordon Bell Prize for High-Performance Computing. It demonstrates strong-scaling capabilities by effectively utilizing low-latency inter-GPU communication and achieving strong-scaling on unstructured grids. PyFR has been successfully benchmarked with up to 18,000 NVIDIA K20X GPUs on Titan, showcasing its efficiency in handling large-scale simulations.
Link to Resource
PyFR documentation
PyFR source code from Github
Discourse channel for discussions and help
Domain
ACCESS CSSN
,
Campus Champions
,
CAREERS
,
CCMNet
,
Great Plains
,
Kentucky
,
Northeast