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A New Unstructured Grid Based Framework For Large Scale Computing of Fluid Flows V. K. Suman & V. Y. Mudkavi Computational & Theoretical Fluid Dynamics Division, CSIR-NAL
Motivation
Achievements
Develop code base to
• Employed meshes as large as 427 million elements • Employed 17,280 cores (99.26 % of full capacity) of CSIR-4PI’s 360 TF Anantha supercomputer
• Tackle complex problems pertaining to aerospace industry (high AoA aerodynamics, stall, CAA) accurately and efficiently
• Significant speed-up of Partitioning & sub-domain assembly
• Enable research on prototypical problems to gain insight
• Tremendous speed-up & super-linear scaling of a simple solver
Results E:/Work-K/CFD/ICEM/NCA/NCA_69/WBDE
Z
X
Y
ICEM CFD 14.0; NCAD@Vishal-PC
Fig. 1: Top left: Civil aircraft design & development; Top right: Turbulence Studies (Credit: Album of Fluid Motion); Bottom left: Landing Gear Noise Studies (Credit: Onera Lab); Bottom right: High AoA aerodynamics (Credit: Russ Tedrake, MIT Computer Science and Artificial Intelligence Laboratory)
Responsibilities Task Solve real problems
Responsibilities/Difficulties
Handle complex geometries ⇒ Unstructured grids/Chimera Methodology 9 O(Re 4 ) points required 6 Develop accurate computational methodologies for DNS ⇒ Massively parallel computing & high scalability O(10 processors) 6 15 Typical analysis of transport aircraft configuration (Re ∼ 20 × 10 ) requires quadrillion (10 ) points Transitional, Turbulent flows LES Grid sizes of billion, trillion elements ⇒ Highly scalable I/O for managing data.
Common Framework- Purpose & Scope
Figure 2: Schematic of a transport aircraft configuration. Partitions created for full Parallel aircraft mesh configuration ( 96Elapsed millionTimes hex elements) Elapsed Times for 96 million mesh example: Algorithm with serial for 96 million mesh example: Parallel Algorithm with Parallel I/O I/O using HDF5 API 180 cores 240 cores 300 cores I/O 1465.0338 1534.025 1393.8819 Partitioning 4.68135 3.92714 4.00486 Local Mesh Assembly 122.0348 62.5623 41.7881
No. of Vertices No. of Faces No. of Cells Cell Type
RANS
FVM
Transition
170,857 1,808,793 884,142 Tetrahedron
Elapsed Time Per Iteration for Simulation of Flow Past 3D Missile.
Transition
Turbulence
Turbulence
Common
DNS
UDNS
Framework
Instabilities
Instabilities
DG
FD
Receptivity
Receptivity
LES
FSI
Transition
CAA
No. of Nodes(cores) Elapsed Time (s) Speedup (Obtained/Ideal) 2(32) 0.12532 10(160) 0.02443 5.129/5 20(320) 0.01171 10.702/10 50(800) 0.00427 29.349/25 100(1600) 0.00225 59.698/50
Turbulence
Future Developments Common Framework- Features
• Support for meshless solver development • Robust RANS solver for design & analysis
• Developed for writing CFD codes for generic unstructured grids
• High fidelity solvers (DNS/LES)
• Designed using OOP concepts & written in C++ • Highly scalable algorithms for massively parallel computing • Hierarchical neighbor construction for high-order FV
References
Common Framework Parallel Computing Environment
MPI
OpenMP
• G. Karypis and V. Kumar, A fast and highly quality multilevel scheme for partitioning irregular graphs, SIAM J. Sci. Comp. 20, 359 (1999).
+
MPI+OpenMP
Parallel I/O (HDF5 API)
• The HDF Group, Hierarchical data format version 5 (2000–2010). • V.K. Suman. An Improved Parallel Domain Decomposition Methodology Based on Parallel I/O for Unstructured Grid Based Petascale CFD Computations, Project Document, NAL-PD/CTFD/2013/1009, 2013.
