Cray HPC Environments for Leading Edge Simulations

HPC Environments for
Leading Edge Simulations
1
Greg Clifford
Manufacturing Segment Manager
clifford@cray.com

Topics:
● Cray, Inc and some customer
examples
● Application scaling examples
● The Manufacturing segment is set
for a significant step forward in
performance
2

Manufacturing
Earth Sciences
Energy Life Sciences
Financial
Services
Cray Industry Solutions
Cray Inc. – 2013
3
Anything That Can Be Simulated Needs a Cray
Computation Analysis Storage/Data

Capacity Focus
(Highly Configurable Solutions)
Supercomputing Solutions to Match the Needs of the Application
Supercomputing Solutions
Cray Inc. – 2013
4
CapabilityFocus
(TightlyIntegratedSolutions)
Cray CS300 Series:
Flexible Performance
Cray XC30 Series:
Scalable Performance

Cray Specializes in Large Systems…
Over 45 PF’s
in XE6 and XK7
Systems
5
Cray Higher-Ed Roundtable, July 22, 2013

New Clothes: NERSC - Edison
10/3/13
6
Cray Higher-Ed Roundtable, July 22, 2013

Running Large Jobs…
NERSC “Now Computing” Snapshot (taken Sept. 4th 2013)
10/3/13 Cray Higher-Ed Roundtable, July 22, 2013
7

WRF Hurricane Sandy Simulation on Blue
Waters
Cray Confidential
8
●  Initial analysis of WRF output is showing some very
striking features of Hurricane Sandy. Level of detail
between a 3km WRF simulation and BW 500meter run is
apparent in these radar reflectivity results
3km WRF results Blue Waters 500meter WRF results
10/3/13

WRF Hurricane Sandy Simulation on Blue
Waters
Cray Confidential
9
10/3/13

Cavity Flow Studies using HECToR (Cray XE6)
S. Lawson, et.al. University of Liverpool
10
●  1.1 Billion grid point model
●  Scaling to 24,000 cores
●  Good agreement between
experiments and CFD
* Ref: http://www.hector.ac.uk/casestudies/ucav.php

11
CTH Shock Physics
CTH is a multi-material, large
deformation, strong shock wave, solid
mechanics code and is one of the most
heavily used computational structural
mechanics codes on DoD HPC
platforms.
“For large models, CTH will show linear scaling to over 10,000 cores.
We have not seen a limit to the scalability of the CTH application”
“A single parametric study can easily consume all of the ORNL
Jaguar resources”
CTH developer

Seismic processing Compute requirements
1212
petaFLOPS
0,1
1
10
1000
100
1995 2000 2005 2010 2015 2020
0,5
Seismic Algorithm complexity
Visco elastic FWI
Petro-elastic inversion
Elastic FWI
Visco elastic modeling
Isotropic/anisotropic FWI
Elastic modeling/RTM
Isotropic/anisotropic RTM
Isotropic/anisotropic modeling
Paraxial isotropic/anisotropic imaging
Asymptotic approximation imaging
A petaflop scale system is required to deliver the capability to
move to a new level of seismic imaging.
One petaflop

13
Compute requirements in CAE
Simulation Fidelity
Robust
Design
Design
Optimization
Design
Exploration
Multiple
runs
Departmental cluster
100 cores
Desktop
16 cores
Single run
Central Compute
Cluster
1000 cores
Supercomputing
Environment
>2000 cores
“Simulation allows engineers to know, not
guess – but only if IT can deliver dramatically
scaled up infrastructure for mega
simulations….
1000’s of cores per mega simulation”
CAE developer
13

CAE Application Workload
14
CFD

(30%)

Structures

(20%)

Impact/Crash
(40%)
Vast majority of large
simulations are MPI parallel
Basically the same codes used across all industries

CAE Workload status
●  ISV codes dominate the CAE commercial workload
●  Many large manufacturing companies have >>10,000
cores HPC systems
●  Even for large organizations very few jobs use more
than 256 MPI ranks
●  There is a huge discrepancy between the scalability in
production at large HPC centers and the commercial
CAE environment
15
Why aren’t commercial CAE
environments leveraging scaling
for better performance

16
Often the full power available is
not being leveraged

10/3/13
17
Innovations in the field of Combustion

c. 2003,
high density,
fast interconnect
Crash & CFD
c. 1983, Cray X-MP, Convex
MSC/NASTRAN
c. 1988, Cray Y-MP, SGI
Crash
18
c.1978
Cray-1, Vector processing
Serial
c. 2007, Extreme scalability
Proprietary interconnect
1000’s cores
Requires “end-to-end parallel”
c. 1983
Cray X-MP, SMP
2-4 cores
c. 1998,
MPI Parallel
“Linux cluster”,
low density, slow interconnect
~100 MPI ranks
c. 2013
Cray XE6
driving apps:
CFD, CEM, ???
Propagation of HPC to commercial CAE
Early adoption Common in Industry

Obstacles to extreme scalability using ISV CAE codes
19
1.  Most CAE environments are configured for capacity computing
—  Difficult to schedule 1000‘s of cores for one simulation
—  Simulation size and complexity driven by available compute resource
—  This will change as compute environments evolve
2.  Application license fees are an issue
—  Application cost can be 2-5 times the hardware costs
—  ISVs are encouraging scalable computing and are adjusting their
licensing models
3.  Applications must deliver “end-to-end” scalability
—  “Amdahl’s Law” requires vast majority of the code to be parallel
—  This includes all of the features in a general purpose ISV code
—  This is an active area of development for CAE ISVs

Copyright © 2013 Altair Engineering, Inc. Proprietary and Confidential. All rights reserved.
Collaboration with Cray
•  Fine-tuned AcuSolve for maximum efficiency on Cray hardware
•  Using Cray MPI libraries
•  Efficient core placement
•  AcuSolve package built specifically for Cray’s Extreme Scalability
Mode(ESM) -- and for the first time shipped in V12.0
•  Extensively tested the code for various Cray systems (XE6, XC30)
20

Version 12.0: More Scalable
•  Optimized domain decomposition for hybrid mpi/openmp
•  Added MPI performance optimizer
•  Nearly perfect scalability seen down to ~4k nodes/subdomain
Parallel performance
on a Linux Cluster with
IB interconnect
21

Version 12.0: Larger Problems
•  In V12.0 the capacity of AcuSolve is increased to efficiently solve
problem sizes exceeding 1 billion elements
•  Example: transient, DDES simulation of F1 drafting on ~1 billion
elements
22

Case studies are real-life engineering problems
All tests are performed in-house by Cray
•  Case Study #1: Aerodynamics of a car model (ASMO)
referred as 70M
•  70 million elements
•  Transient incompressible flow (implicit solve)
Case Studies
23

•  Case Study #2: Cabin comforter model referred as
140M
•  140 million elements
•  Steady incompressible flow + heat transfer (implicit solve) + radiation
Case Studies
24

Performance Results (combined)
140M Cray XC30 (SandyBridge + Aries)
70M Cray XC30 (SandyBridge + Aries)
70M Cray XE6 (AMD + Gemini)
70M Linux cluster (SandyBridge + IB)
Ideal
small core
count 25

Webinar Conclusions
•  Cray’s XC30 demonstrated the best performance in terms of both
scalability and throughput
•  Parallel performance of XE6 and XC30 interconnect was superior
to IB
•  For small number of cores (approximately less than 750),
AcuSolve parallel performance is satisfactory across multiple
platforms
•  Throughput is mostly affected by core type (e.g. SandyBridge v.s.
Westmere)
26

Summary of Cray Value
1. Extreme fidelity simulations require HPC
performance and extreme scalability is the only
option to achieve this performance
2. Cray systems are designed for large production HPC
environments, whether it is a single simulation
using 10,000 cores or 100 simulations each using
100 cores.
3. The technology is in place for CAE environments to
leverage >>1000s of cores per simulation and we are
over due to see extreme scaling leveraged in
commercial environments

Questions?
28

Cray HPC Environments for Leading Edge Simulations

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