cae applications for hpc - serc.iisc.in · cae applications for hpc stephen behling cray inc ......
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C O M P U T E | S T O R E | A N A L Y Z E
CAE Applications for HPC Stephen Behling
Cray Inc May, 2015
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C O M P U T E | S T O R E | A N A L Y Z E
Short bio
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● Education in Nuclear Engineering ● Worked at U.S. National Laboratory in Idaho on reactor
safety computer codes ● Joined Cray Research in 1986
● Vectors, micro-tasking, macro-tasking ● CAE applications
● IBM (1999 – 2008) ● CAE applications
● Now back at Cray Inc. in Performance Team ● CAE applications: PowerFLOW, PAMCrash, AcuSolve, ANSYS
Mechanical ● Many other codes: SU3, GFS, NIM, …
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C O M P U T E | S T O R E | A N A L Y Z E
CAE encompasses industries, national laboratories, and research
● Aerospace ● Commercial; military; space
● Automotive ● Commercial; sports
● Other transportation ● Trains; ocean transport
● Manufacturing
● Energy ● Fossil fuels
● Nuclear
● Hydrology; medical devices; architecture; insurance
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C O M P U T E | S T O R E | A N A L Y Z E
CAE is growing rapidly
● Trends are: ● More accurate analyses ● Bigger models
● “1 billion cells”; “100 million elements”; “19 million degrees of freedom”
● Bigger computers ● More nodes; more cores; more memory; more parallel I/O
● Much CAE work uses third-party Independent Software Vendors (ISVs) for financial reasons ● Engineers (cost the most)
● Need to get answers quickly
● Software licenses (second most costly) ● Less costly than internal code development, maintenance, and support
● Computer hardware (third most costly)
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C O M P U T E | S T O R E | A N A L Y Z E
HPC workload
Automotive
Dynamics
CFD
Structures
Other
Aerospace
Dynamics
CFD
Structures
Other
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C O M P U T E | S T O R E | A N A L Y Z E
Growth in CAE HPC usage
6
Automotive and
aerospace companies
saw a huge growth in
CAE HPC power from
2000-2015
and
CAE simulation is
growing at an increasing
rate in recent years
Ref:
Industrial High Performance Computing:
Michael Taeschner, Volkswagen AG
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C O M P U T E | S T O R E | A N A L Y Z E
Growth in CAE HPC usage
7
Automotive and
aerospace companies
saw a huge growth in
CAE HPC power from
2000-2015
and
CAE simulation is
growing at an increasing
rate in recent years
Ref:
Industrial High Performance Computing:
Michael Taeschner, Volkswagen AG
• More car models
• More runs per
model
• More accuracy
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C O M P U T E | S T O R E | A N A L Y Z E
Growth in CAE HPC usage
8
Automotive and
aerospace companies
saw a huge growth in
CAE HPC power from
2000-2015
and
CAE simulation is
growing at an increasing
rate in recent years
Ref:
Industrial High Performance Computing:
Michael Taeschner, Volkswagen AG
NEED BIGGER
COMPUTERS!
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C O M P U T E | S T O R E | A N A L Y Z E
ISV license pricing favors parallel computing
9
• Most ISVs have a pricing
system the encourages
running in parallel
• It is typically cheaper per
simulation to use more cores
• Graph shows PAM-CRASH
example with “very
conservative” estimate for
parallel performance Ref.
March 2015
7.5X performance
2.1X
license cost
PAM-CRASH performance vs. License cost
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C O M P U T E | S T O R E | A N A L Y Z E
CAE and parallel computers
● Computational Fluid Dynamics (CFD) ● Most scalable of the CAE applications
● All codes are MPI parallel
● Some have threading
● Structural Dynamics ● Moderate scaling; contact as parts buckle is difficult
● All codes are MPI parallel
● Some have threading
● Structural NVH (Noise, Vibration, Harshness) ● Low scaling; large memory or large I/O requirements
● All codes are MPI parallel and may be threaded
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C O M P U T E | S T O R E | A N A L Y Z E
CAE Workflow
1. Recognize problem to be solved ● Meet safety requirements? ● Reduce drag? ● Minimize weight/noise/cost? ● Maximize efficiency/reliability/profit/safety?
2. Represent system via a CAD model ● Multiple use: both for manufacturing and for various analyses
3. Translate CAD description into computational mesh ● Each discipline needs its own mesh
4. Decompose mesh into computational domains ● First pick number of computational nodes/cores and then run decomposition tool
5. Solve ● Main computational task in CAE
6. Analyze ● Graphics; statistics
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C O M P U T E | S T O R E | A N A L Y Z E
CAE Workflow
1. Recognize problem to be solved ● Meet safety requirements? ● Reduce drag? ● Minimize weight/noise/cost? ● Maximize efficiency/reliability/profit/safety?
2. Represent system via a CAD model ● Multiple use: both for manufacturing and for various analyses
3. Translate CAD description into computational mesh ● Each discipline needs its own mesh
4. Decompose mesh into computational domains ● First pick number of computational nodes/cores and then run decomposition tool
5. Solve ● Main computational task in CAE
6. Analyze ● Graphics; statistics
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C O M P U T E | S T O R E | A N A L Y Z E
CAE Workflow
1. Recognize problem to be solved ● Meet safety requirements? ● Reduce drag? ● Minimize weight/noise/cost? ● Maximize efficiency/reliability/profit/safety?
2. Represent system via a CAD model ● Multiple use: both for manufacturing and for various analyses
3. Translate CAD description into computational mesh ● Each discipline needs its own mesh
4. Decompose mesh into computational domains ● First pick number of computational nodes/cores and then run decomposition tool
5. Solve ● Main computational task in CAE
6. Analyze ● Graphics; statistics
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C O M P U T E | S T O R E | A N A L Y Z E
CAE Workflow requirements
● CAD ● Days to weeks
● Translate CAD to mesh ● Hours to day ● Usually single processor
● Domain decomposition ● Minutes to hours; can be single workstation ● May use parallel processing and may be part of solve step ● Examples: Metis (serial), pMetis (parallel)
● Solve ● Hours to days to weeks to … unsolvable ● The most benefit for engineers is to have one or more results per day ● Need a supercomputer for this
● Analyze ● Days or more ● Need powerful graphics
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C O M P U T E | S T O R E | A N A L Y Z E
CAE simulation characteristics for solve step
• Computational Fluid Dynamics (CFD)
• Often highly scalable (16000+ cores)
• I/O requirements low to moderate for typical analyses; big data for LES
• Seldom use math libraries; HDF5
• Typical runs 100 -1000 cores
• Dynamics: Impact Simulation; Crash/Safety Simulation
• Can be moderately scalable (2000+ cores)
• Low I/O requirements
• Seldom use math libraries; HDF5
• Typical runs: 20 – 200 cores
• Structures and NVH
• Low Scaling (200+) cores
• Large memory; good I/O; often have GPU option
• BLAS2, BLAS3
• Typical runs: 1 to 10% of the HPC environment
• Other/Multi-Physics
• Fluid-Structure interaction
• Ships and waves; Blood flow; Oil pipe riser (sub-sea well to shore)
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C O M P U T E | S T O R E | A N A L Y Z E
Scaling is affected by load imbalance and network communication
0
4000
8000
12000
16000
0 4000 8000 12000 16000
Sp
ee
d u
p
Number of cores
Excellent
Good
Not so good
Ideal speedup
It can be a lot of
work to move
from “good” to
“excellent”
scaling.
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C O M P U T E | S T O R E | A N A L Y Z E
Elapsed time (on log-log plot) is another way to look at scaling
1
4
16
64
256
1024
32 256 2048 16384
Ela
ps
ed
tim
e
Number of cores
Actual
Ideal
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C O M P U T E | S T O R E | A N A L Y Z E
CFD ISV examples: all are unstructured grids
● OpenFOAM by OpenCFD Ltd at ESI Group ● Open source under GNU General Public License ● Finite volume discretization for typical CFD; MPI parallelization
● ANSYS Fluent by ANSYS Inc. ● Finite volume discretization; MPI parallelization
● STAR-CCM+ by CD-adapco Inc. ● Finite volume discretization; MPI parallelization
● AcuSolve by Altair ● Finite element; hybrid MPI and OpenMP parallelization
● PowerFLOW by Exa Corporation ● Lattice Boltzmann; MPI parallelization with some threading
● HiFUN by Sandl ● MPI parallelization
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C O M P U T E | S T O R E | A N A L Y Z E
EXA/PowerFLOW scaling on the Cray XC40
19
1
2
4
8
16
32
64
128
256
512
1024
32 256 2048 16384
Elap
sed
tim
e 51
2 ti
me
ste
ps
(s.)
Number of SP tasks (cores)
PowerFLOW version 5.1a on Cray XC40
2.3 GHz 16-core Intel ® Haswell processors
PowerFLOW CFD
simulation scaling to
over 16,000 cores
Lattice Boltzmann code
88 million voxels
“large-performance-test”
PowerFLOW scaling
Ideal scaling
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C O M P U T E | S T O R E | A N A L Y Z E
Cray and ANSYS/Fluent work together to add value On-going development effort to improve HPC scaling in Fluent
• Segregated implicit solver
• Scalable at ~10K cells per core! 0
500
1000
1500
2000
2500
3000
3500
4000
0 2048 4096 6144 8192 10240 12288
Pe
rfo
rma
nc
e R
ati
ng
Number of Cores Rating is jobs per day. A higher rating means faster performance.
Truck_111M Turbulent Flow
0
100
200
300
400
500
600
700
800
900
1000
0 2048 4096 6144 8192 10240 12288 14336
Number of Cores
DLR_96M LES Combustion
R15.0
Ideal
• Pressure based coupled solver
• Scalable at ~10K cells per core!
Release15
Release14
Release13
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C O M P U T E | S T O R E | A N A L Y Z E
1 billion element AcuSolve Formula 1 external flow simulation
● Date = Fri Nov 8 15:49:22 2013
● Problem = F1
● Title = AcuSolve Problem
● Platform = Linux 3.0.80-
0.5.1_1.0501.7664-cray_ari_c x86_64
● Machine = linux64
● No. of threads = 24
● No. of nodes = 169984316
● No. of elements = 1007704126
0
1000
2000
3000
0 1000 2000 3000
Number of cores
Speed up
Linear
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C O M P U T E | S T O R E | A N A L Y Z E
Human Respiratory System Transient incompressible turbulent flow 360M elements, scaled to 25,000 cores
Kiln Furnace Transient incompressible turbulent flow Coupled with energy and combustion 4.22 billion elements, scaled to 100,000 cores
Human Heart Non-linear solid mechanics Coupled with electrical propagation 3.4 billion elements, scaled to 100,000 cores
CFD Results from NCSA “Blue Waters” system ALYA CFD code: 3 Real-World Cases
Ref: “Growth of HPC Industrial Partnership”, Merle Giles NCSA, Oct. 2014
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C O M P U T E | S T O R E | A N A L Y Z E
Impact/Crash Simulation Dynamic Structural Analysis
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Examples:
• LS-DYNA by LSTC
• RADIOSS by Altair
• PAMCrash by ESI Group
• Abaqus explicit by Dassault Systèmes
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C O M P U T E | S T O R E | A N A L Y Z E
2014 IDC award for scaling LS-DYNA
24
Rolls-Royce, Procter and Gamble, National Center for Supercomputing
Applications, Cray Inc., Livermore Software Technology Corporation (U.S.).
Researchers from NCSA, Rolls Royce, Proctor and Gamble, Cray Inc, and
Livermore Software Technology Corporation were able to scale the commercial
explicit finite element code, LS-DYNA, to 15,000 cores…
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C O M P U T E | S T O R E | A N A L Y Z E
Ford: 100M Element Model of “B pillar”
● Three papers at the 2014 LS-DYNA conference using 100M element model ● “LS-DYNA performance in Side Impact Simulations
with 100M element Models” El Fadl, B., Ford Motor Company ● 2048 cores: 2.5 days
● 1024 cores: 4.5 days
● “Meso-Scale FEA Modeling to Simulate Crack Initiation and Propagation in Boron Steel” Chen, Y., Ford Motor Company
● “Fracture Prediction and Correlation of ALSi Host Stamped Steels with Difference Models in LS-DYNA” by Zhu, H.
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C O M P U T E | S T O R E | A N A L Y Z E
Example using RADIOSS
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8072.29
4509.92
2686.82
1747.8
1242.66
844.09
628.5 458.23
356.68 349.56
100
1000
10000
1 2 4 8 16 32 64 128 256 512
[16 mpi, 2omp]
[16 mpi, 4omp]
[32 mpi, 4omp]
[32 mpi, 8omp]
[64 mpi, 8omp]
[512 mpi,2 omp]
[512 mpi,4 omp
[512 mpi,8 omp]
[512mpi,16omp]
[512mpi,32omp]
EL
AP
SE
D T
IME
Results for Taurus A05 Refined 10 million elements RADIOSS 13.0
Crystal XC40; Haswell-32 cores - 2.3 GHz
16000 cores
Number of nodes
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C O M P U T E | S T O R E | A N A L Y Z E
Noise, Vibration & Harshness (NVH) Implicit Structural Analysis
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Image courtesy of MSC Software
Examples:
• MSC-Nastran by MSC Software
• Abaqus Implicit by Dassault Systèmes
• ANSYS Mechanical by Ansys Inc.
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C O M P U T E | S T O R E | A N A L Y Z E
MSC Nastran NVH performance on Cray CS400
28
Large Structure Nodes ● Two Xeon E5-2667-v3 (Haswell, 8 core, 3.2 GHz)
● 758 GB RAM – Twenty four (24) 32GB DIMMs
● 4 x 1.6TB PCIe SSDs (Striped)
Implicit, structural eigenvalue solutions require a balance of
processor speed, memory and IO performance
Recent MSC Nastran benchmarks posted: http://web.mscsoftware.com/support/prod_support/nastran/performance/msc20140.cfm
• Largest NVH model size increased to 19 million DOF
• This NVH model is 5X the version largest version 2013 example
• Cray CS400 “NVH configuration” 1.6X faster than best version 2013 results
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C O M P U T E | S T O R E | A N A L Y Z E
Summary
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C O M P U T E | S T O R E | A N A L Y Z E
Scalability of select ISV applications in CLE
ISV Application Primary segment Demonstrated
scalability *
ANSYS Fluent Commercial CFD >36,000 cores
LS-DYNA Impact/crash analysis >15,000 cores
CFD++ Aerospace CFD >10,000 cores
STAR-CCM+ Commercial CFD >100,000 cores
PowerFLOW External CFD >16,000 cores
AcuSolve Commercial CFD > 6,000 cores
Abaqus/standard Structural analysis >300 cores
30
* Demonstrated scalability typically limited by the simulation model available
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C O M P U T E | S T O R E | A N A L Y Z E
CAE is growing rapidly
● Trends are: ● More accurate analyses
● Bigger models ● “1 billion cells”; “100 million elements”; “19 million degrees of freedom”
● Bigger computers ● More nodes; more cores; more memory; more parallel I/O
● Cray Inc is proud to be a key vendor in this discipline
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