Recent Advances in HPC for Structural Mechanics Simulations

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1 Recent Advances in HPC for Structural Mechanics Simulations 1

2 Trends in Engineering Driving Demand for HPC Increase product performance and integrity in less time Consider more design variants Find the optimal design Ensure performance across a range of conditions HPC is a key enabler to assure greater product integrity through robust design Increased product complexity! Assess larger, more detailed models Consider more complex physics From single component to system innovations HPC is a key enabler to gain higher-fidelity insight 2

3 Trends in Engineering Driving Demand for HPC Do more with existing engineering and design teams Scale-up of HPC to support more simulation workloads Centralized HPC infrastructure (or cloud) with effective remote access Managing collaboration and explosive growth of engineering data HPC is a key enabler to amplify engineering productivity Mainframes Client/Server Workstation/PCs Local Clusters Shared HPC Grid Cloud, Mobile

4 ANSYS Strategic Focus Scalable and Cost-Effective IT Evolution Scale-up of high performance computing new/emerging architectures more and bigger workloads Common integrated tools and platform for IT efficiency Efficient centralized infrastructure (or cloud) with effective remote access Collaboration hubs with secure and scalable data access Support for mobile platforms 4

5 ANSYS Strategic Focus Scalable and Cost-Effective IT Evolution Scale-up of high performance computing new/emerging architectures more and bigger workloads Common integrated tools and platform for IT efficiency Efficient centralized infrastructure (or cloud) with effective remote access Collaboration hubs with secure and scalable data access Support for mobile platforms 5

6 Scale-up of High Performance Computing A Software Development Imperative Today s multi-core / many-core hardware evolution makes HPC a software development imperative. 6 Source: AnandTech

7 Ideal scaling to 4096 cores (fluids) Hybrid parallelization (fluids) Network-aware partitioning (fluids) DDM for finite antenna arrays (HFSS 14) GPU acceleration with DMP(structures) ANSYS is committed to maintaining performance leadership. 7

8 ANSYS Mechanical 14.5 Scaling Achievement Minimum time to solution more important than scaling 25 Solution Scalability 20 Speedup Turbine model 2.1 million DOF Nonlinear static analysis 5 1 Loadstep, 7 substeps, 0 25 equilibrium iterations Linux cluster (8 cores per node)

9 ANSYS Mechanical 14.5 Scaling Achievement Windows 7 workstation: 2 Intel Xeon E (2.6 GHz, 16 cores total), 1 SSD, 128 GB RAM, NVIDIA Tesla C million DOF Linear static analysis PCG solver (DMP) Relative Speedup GPU Performance 5.2x 2.7x 2 cores 8 cores 16 cores (no GPU) (1 GPU) (4 GPUs) 9

10 ANSYS Mechanical Scaling Evolution ANSYS 11.0 ANSYS 12.0 ANSYS 12.1 ANSYS 13.0 SP2 ANSYS 14.0 ANSYS 14.5 Thermal (full model) 3 MDOF Thermomechanical Simulation (full model) 7.8 MDOF Time 4 hours 4 hours 4 hours 4 hours 1 hour 0.8 hour Cores GPU 32 Time ~5.5 days 34.3 hours 12.5 hours 9.9 hours 7.5 hours 6.4 hours Iterations Cores Interpolation of Boundary Conditions Submodel: Creep-Strain Analysis 5.5 MDOF Time 37 hours 37 hours 37 hours 0.2 hour 0.2 hour 0.2 hour Load Steps Improved algorithm Time ~5.5 days 38.5 hours 8.5 hours 6.1 hours 5.9 hours 4.2 hours 4 hours Iterations Cores GPU Total Time 2 weeks 5 days 2 days 1 day 0.5 day 0.5 day All runs with Sparse solver Hardware 12.0: dual X5460 (3.16 GHz Harpertown Intel Xeon) 64GB RAM per node Hardware : dual X5570 (2.93 GHz Nehalem Intel Xeon) 72GB RAM per node Hardware 14.5: dual E (2.9 GHz Sandy Bridge Intel Xeon) ANSYS 12.0 to 14.0 runs with DDR Infiniband interconnect ANSYS 14.0 to 14.5 creep runs with NROPT,CRPL + DDOPT,METIS 10 Results Courtesy of MicroConsult Engineering, GmbH

11 ANSYS Mechanical 15.0 Faster Performance at Higher Core Counts by an enhanced domain decomposition method 6 Improved Scaling at 8 cores 8-node Linux cluster (with 8 cores and 48 GB of RAM per node, InfiniBand DDR) Speedup over R x 1.7x 2.7x 2.4x 0 Engine (9 MDOF) Stent (520 KDOF) Clutch (160 KDOF) Bracket (45 KDOF) 11

12 ANSYS Mechanical 15.0 Faster Performance at Higher Core Counts by an enhanced domain decomposition method 6 Improved Scaling at 16 cores 8-node Linux cluster (with 8 cores and 48 GB of RAM per node, InfiniBand DDR) Speedup over R x 1.8x 3.8x 4.0x 0 Engine (9 MDOF) Stent (520 KDOF) Clutch (160 KDOF) Bracket (45 KDOF) 12

13 ANSYS Mechanical 15.0 Faster Performance at Higher Core Counts by an enhanced domain decomposition method Speedup over R x Improved Scaling at 32 cores 2.2x 3.9x 8-node Linux cluster (with 8 cores and 48 GB of RAM per node, InfiniBand DDR) 5.0x 0 Engine (9 MDOF) Stent (520 KDOF) Clutch (160 KDOF) Bracket (45 KDOF) 13

14 GPU Achievements ANSYS Mechanical 14.5 Supporting Multi-GPUs Multiple GPUs per machine are now supported (R14.5) Supports single workstation with multiple GPUs Supports cluster with each compute node having multiple GPUs Both shared and distributed memory parallel modes are supported 14

15 GPU Achievements ANSYS Mechanical 14.5 Supporting Multi-GPUs ANSYS Mechanical Number of Jobs Per Day Results for Distributed ANSYS 14.5 and Intel Xeon 8-Core CPUs Higher is Better Xeon E5-2687W 8 Cores + Tesla C x Speedup with 2 GPUs 19 Xeon E5-2687W 8 Cores + 2 x Tesla C2075 V14sp-5 Model Turbine geometry 2,100 K DOF SOLID187 FEs Static, nonlinear One iteration ANSYS Mechanical14.5 Direct sparse solver Results from HP Z820; 2 x Xeons (16 Cores, use of only 8) 128GB memory, Win7; 2 x Tesla C

16 GPU Achievements ANSYS Mechanical 14.5 Speed-up for PCG Solvers With 14.5, more structural mechanics simulations can be accelerated by using GPUs In 14.5, a hybrid solution is also employed for PCG solvers, where portion not fit in GPU memory is solved by CPU In 13.0/14.0 no additional speedup from GPU obtained due to matrix not fitting in GPU memory 16 Results (baseline is 1 core w/o GPU): Cores GPU Speedup R14.0 R no yes yes Modal analysis of a probe Windows workstation: Two Intel Xeon 5530 processors (2.4 GHz, 8 cores total), 48 GB RAM, NVIDIA Quadro 6000

17 GPU Achievements ANSYS Mechanical 15.0 Supporting Newest GPUs Performance on newest NVIDIA GPUs (Kepler) R15 can be up to 30% faster than previous version Speedup Improved Scaling with GPUs R145 (8 cores) R145 (8 cores + 1 GPU) R15 (8 cores + 1 GPU) x 1.3x 1.50 Linux server (32 Intel Xeon E GHz, 1 Tesla K20Xm, 512 GB RAM) Turbine benchmark BGA benchmark

18 GPU Achievements ANSYS Mechanical 15.0 Supporting Xeon Phi Significant speedups can be achieved with Xeon Phi card Shared Memory Sparse Solver on Linux Speedup x 4.3x 3.3x Xeon Phi Acceleration (SMP) CPU cores only CPU cores + Xeon Phi 6.8x 6.0x 1 core 2 cores 4 cores 8 cores 16 cores V14sp-5 Model Turbine geometry 2.1 million DOF SOLID187 elements Static, nonlinear analysis One iteration Sparse direct solver Linux workstation (16 Intel Xeon E GHz, A Xeon Phi, 64 GB RAM)

19 HPC Licensing Scalable licensing ANSYS HPC (per-process) ANSYS HPC Pack Virtually Unlimited parallel on single job Best solution for extreme scaling needs Parallel enabled increases quickly as packs added ANSYS HPC Workgroup Volume access to HPC for many users running everyday HPC jobs 128 to 2048 parallel shared across any number of simulations (note: new HPC Workgroup 32 & 64) ANSYS HPC Enterprise Similar to HPC Workgroup but deploy and use anywhere in the world Parallel Enabled (Cores) Single HPC solution for FEA/CFD/FSI and any level of fidelity Packs per Simulation

20 New Parametric Modeling and Licensing at 14.5 ANSYS HPC Parametric Pack Explore Your Parametric Designs Faster, More Cost Effectively 20

21 Example: Static Analysis of Semi-submersible New Parametric Modeling and Licensing at 14.5 Problem Static Analysis of semi-submersible using beam & shell elements, subjected to hydrostatic pressure and gravity loading Design objective: minimize both total mass and equivalent stress Input parameters: pontoon thickness, base column thickness (16 design points) Detail: 232,583 nodes, 230,770 elements Base Column Hardware: Dell workstation with dual Intel Xeon E (2.90 GHz, 16 cores), 256 GB memory, all jobs running 2 cores Licensing Solution 1 ANSYS Mechanical 2 ANSYS HPC Parametric Packs Result/Benefit ~6x speedup over sequential execution Easier and fully automated workflow Pontoon 21 Acknowledgment: Paul Schofield and Jiaping Zhang, ANSYS Houston

22 ANSYS 15.0 License Scheme for GPUs - One HPC Task Required to Unlock one GPU! Licensing Examples: 1 x ANSYS HPC Pack Total 8 HPC Tasks (4 GPUs Max) Example of Valid Configurations: 6 CPU Cores + 2 GPUs 4 CPU Cores + 4 GPUs 2 x ANSYS HPC Pack Total 32 HPC Tasks (16 GPUs Max)..... (Applies to all schemes: HPC, HPC Pack, HPC Workgroup, HPC Enterprise, etc.) 24 CPU Cores + 8 GPUs (Total Use of 2 Compute Nodes) 22

23 ANSYS Strategic Focus Scalable and Cost-Effective IT Evolution Scale-up of high performance computing new/emerging architectures more and bigger workloads Common integrated tools and platform for IT efficiency Efficient centralized infrastructure (or cloud) with effective remote access Collaboration hubs with secure and scalable data access Support for mobile platforms 23

24 IT Efficiency Common Integrated Tools & Platform 24

25 Flexible Deployment ANSYS Architecture for HPC ANSYS Workbench User Environment/Graphics Job Submission Multi-core / Multi-node Compute Cluster Workstation-Based or Thin Clients Graphics Servers File Servers 25 High-Performance Computing ANSYS Remote Solve Manager: Workbench-based job submission with full portfolio support for Platform LSF, PBS Pro, and Microsoft Job Scheduler Bundled third-party Message-Passing software with optimized performance (Intel MPI, Platform MPI) on gige, 10gigE, or InfiniBand cluster fabric.

26 ANSYS Strategic Focus Scalable and Cost-Effective IT Evolution Scale-up of high performance computing new/emerging architectures more and bigger workloads Common integrated tools and platform for IT efficiency Efficient centralized infrastructure (or cloud) with effective remote access Collaboration hubs with secure and scalable data access Support for mobile platforms 26

27 Effective Global Collaboration on Consolidated Infrastructure Optimizing Remote Simulation Workflow Engineering IT is Evolving to Centralized HPC Resources, with Users Remote Customer Initiatives Datacenter Consolidation Private / Public Cloud Globally Connected R&D IP Protection & Leverage Virtual Desktop Enabling Simulation Practices Data Management Data remains in the datacenter Eliminate file transfer bottlenecks Data centralization for collaboration Mobility and Remote Access Beyond batch processing! Centralized Flexible Licensing Compute Centers HPC Users 27

28 Current Trends / ANSYS Strategy Spectrum of Private, Hosted and Public Cloud Software & User Environment: Seamless usability and remote access Hardware: Private cloud or hosted HPC (w/ data security ) later Business: Evolution / Add flexibility of usage to traditional license model 28 Graphic courtesy of IBM

29 Users (Remote/Mobile) ANSYS High-Performance Computing Roadmap for Remote/Mobile Access Browser access Remote Display ANSYS Portal Web/Mobile UI Coming soon Batch jobs Interactive jobs Enterprise datacenter or cloud Compute cluster Work in Progress data Graphics server Data Management Simulation Job Management Mobility & Remote Access Data/Process Management Search & Retrieval Light Weight Visualization Security & Access Controls Dashboard to manage Open - Interface to Schedulers & Resource Managers Job Management Job Controls Remote Execution Interactive remote Visualization Mobile monitoring - Detach/Attach 29 R15.0

30 ANSYS Cloud Partner-Enabled Solutions Customer Facility Enable customers to Outsource HPC Burst or steady-state extension of in-house capacity Leverage partnerships with HPC Cloud Partners HPC hosting experts; data security; choice 30 On-Premise license On-Premise Data Combined usage (on premise + cloud) Browser access Cloud Portal Secure account access; data management; job management WIP Data Batch jobs Interactive jobs Thin client access Compute cluster Graphics servers Partner built, partner owned and operated. Cloud License SW sold and supported by ANSYS Traditional Lease/Perpetual or (Coming) Usage Based

31 ANSYS Cloud Customer Experience Gompute Remote simulation on the cloud Secure VPN Connection Portal Tools / Data Storage 31 HPC Job Submission Remote Display

32 ANSYS Cloud Customer Experience Gompute Set up an ANSYS Cloud account / Evaluate Accept HW terms and conditions Run sample ANSYS workloads 32

33 ANSYS Cloud Customer Experience CADFEM Germany Start Real VNC Viewer on your machine and Login with your Hostname In Win7 environment start your ANSYS Secure VPN Connection Remote Display HPC Job Submission 33

34 ANSYS Cloud ANSYS is Building out a Network of Partners Current Partner Listing Partial list. Partners will continue to be added in time. Pending / target partner. 34

35 Wrap Up / Conclusions 35

36 HPC & Cloud ANSYS Strategy Enterprise Requirements / Practices Enterprise SW Portfolio Management Mobility & remote access Global Collaboration, Monitoring & Control Work in Progress Data Management Job Scheduling & Resource Management HPC Scale Up & HW Optimization ANSYS Collaboration Platform Performance at 1000 s of cores Integrated job and data mgmt Mobile / web access Optimized remote graphics Open support for IT tools ANSYS Cloud Partners Hosting service experts True HPC cloud Full remote simulation experience Flexible business evolution Desktop Private Cloud / Enterprise HPC Hosted HPC Cloud Public Cloud 36 Infrastructure / Cloud Spectrum

37 Thank You! Connect with Me Connect with ANSYS, Inc. LinkedIn ANSYSInc Facebook ANSYSInc Follow our Blog ansys-blog.com 37

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