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Meeting Manufacturing’s Need for Production Supercomputing Tony DeVarco Director of Virtual Product Design Manufacturing Solutions

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Challenges Manufacturing Companies Are Facing

ImageCourtesyofANSYS

•  The need to increase engineering productivity. •  Speed up product development time. •  Reduce physical prototyping to save time and costs. •  Inefficient use of expensive ISV licenses. •  Need to maintain multiple geographically distributed engineering

facilities. •  Distributed workstations cannot interact with computer resources and

data in the corporate data centers. •  Need to replace workstations with low-cost, remote clients.

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Pre/Post Model and Mesh

Creation and Visualization

CEM Computational

Electromagnetics

CFD Computational Fluid Dynamics

CSM* Explicit

Workload Scheduling

SGI® Management Center and SGI® Performance Suite

SGI® Scale-up and Scale-out Computing Solutions

Workload Scheduling Tool

Linux OS

Nastran ANSYS® Mechanical ABAQUS/Standard

ADINA Permas

LS-DYNA PAM-CRASH

RADIOSS ABAQUS Madymo

ANSYS® FLUENT OpenFOAM®

StarCCM+ PowerFLOW

CFD++ Pam-Flow

FEKO ANSYS® HFSS

CST FMSlib

ANSA Hypermesh

Gambit Patran

Altiar Hyperworks ANSYS EKM SimManager

ABAQUS/CAE d3View

SDM Simulation Data

Management

CSM* Implicit

Nastran ANSYS® Mechanical ABAQUS/Standard

ADINA Permas

Altair RADIOSS LS-DYNA

PAM-CRASH ABAQUS Madymo

Altair AcuSolve ANSYS® FLUENT

OpenFOAM®

StarCCM+ PowerFLOW

ANSYS® HFSS Altair FEKO

CST ANSYS Maxwell 3D

Altair Hypermesh ABAQUS/CAE

ANSA Gambit Patran

Altiar Hyperworks ANSYS EKM SimManager

d3View

SGI® Vizserver®

SGI Hardware 3rd Party Software CAE Segments * CSM Is Computational Structural Mechanics

SGI Software SGI Services

SG

I Services

SGI® Solution Environment and CAE Application Segments

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SGI and ANSYS Scaling Fluent 17.2 to a New

Record of 145,152 cores

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SGI ICE XA System Used

SGI and ANSYS Scaling Fluent 17.2 to a New Record of 145,152 Cores

•  A great example using a balanced production supercomputer is illustrated in a recent setting of a new commercial CFD benchmark for the widely-used ANSYS application.

•  Specifically, ANSYS and SGI application engineers worked together to achieve a new world record, scaling ANSYS Fluent® on SGI® ICE™ XA, which is one of the world’s fastest commercial distributed-memory supercomputer platforms.

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Cores

Combustor830M--Fluent17.2

ICE-XA--E5-2697v4--2.30GHz LinearScaling

GasCombustor830McellModel,CourtesyofANSYS

In the test, SGI ran Fluent on 145,152 CPU cores, which is over 16,000 more cores than the previous record. The benefit of scaling to this level is that the total wall clock time to complete a simulation can be significantly reduced. In this case, a single simulation was completed in 13 seconds. In contrast, the same simulation run on 1,296 cores took 20 minutes.

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An industry example that highlights the advantages of scaling CFD workloads on a

SGI® UV™ System

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SGI® Origin 2000, 1996 MIPS R10K

SGI Origin 3000, 1999 MIPS R12K

SGI® Altix® 3000, 2003 Intel Itanium

SGI Altix 4700, 2006 Intel Itanium SGI UV 1000, 2010

Intel E7 SGI UV 300, 2014

Intel E7 SGI UV 2000/3000, 2012/2015

Intel E5

Seven Generations of Shared Memory Systems: 1996–2015

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The Best of DMP and SMP in One Cache-Coherent System with One OS

SGI® InfiniteStorage™

NVIDIA® K5200 or M6000

Multiple Users and Multiple Jobs

Preprocessing, Mesh Generation

and Model Decomposition

Running Solvers

Post Processing and Visualization

UV rack layout for illustration purposes only.

Consolidate Workloads into One Easy-to-Administer System

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Image courtesy London Computational Solutions

•  London Computational Solutions, headed by Mark Taylor, former Head of CFD at McLaren F1, is working with Elemental Cars, an advanced track car manufacturer.

•  The goal of this effort is to improve the cornering speed of its RP1 car by using design elements to create an aerodynamic downforce that increases the vertical force on the car’s tires creating more grip with the road.

Elemental Cars

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•  “When I was Principal Aerodynamicist for McLaren F1 Racing, and now as CEO of London Computational Solutions (LCS),” states Mark Taylor, “I relied on the SGI® UV™ shared memory platform to deliver the robustness, reliability, and efficiency to scale our CFD simulations to meet a tight manufacturing deadline and our aerodynamic performance targets.”

•  “When LCS was presented with the aerodynamic challenge to improve the cornering speeds for a new British road-legal track car called Elemental RP1, I knew I could meet their requirements of a quick turnaround because the running of our CFD software on SGI UV would perform as advertised and just work.”

Image courtesy London Computational Solutions

Elemental Cars

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Examples of a fifth order accurate simulation of a full automotive car geometry.

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Elemental Cars

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