ANSYS HPC Technology Leadership

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1 ANSYS HPC Technology Leadership 1 ANSYS, Inc. November 14,

2 Why ANSYS Users Need HPC Insight you can t get any other way It s all about getting better insight into product behavior quicker! HPC enables high-fidelity Include details - for reliable results Getting it right the first time Innovate with confidence HPC enables design exploration & optimization Consider multiple design ideas Optimize the design Ensure performance across range of conditions 2 ANSYS, Inc. November 14,

3 15 % spent on R&D 570 software developers Partner relationships ANSYS HPC Leadership A History of HPC Performance Parallel dynamic moving/deforming mesh Distributed memory particle tracking Integration with load management systems Support for Linux clusters, low latency interconnects 10M cell fluids simulations, 128 processors Ideal scaling to 2048 cores (fluids) Teraflop performance at 512 core (structures) Parallel I/O (fluids) Domain Decomposition introduced (HFSS 12) Parallel meshing (fluids) Support for clusters using Windows HPC Parallel dynamic mesh refinement and coarsening Dynamic load balancing st general-purpose parallel CFD with interactive client-server user environment s Vector Processing on Mainframes Ideal scaling to 3072 cores (fluids) Hybrid parallel for sustained multicore performance (fluids) Architecture-aware partitioning (fluids) GPU acceleration (structures) Optimized performance on multicore processors 1 st One Billion cell fluids simulation Distributed sparse solver Distributed PCG solver Variational Technology DANSYS released Distributed Solve (DSO) HFSS st company to solve 100M structural DOF Today s multi-core / many-core 64bit hardware large memory addressing evolution Shared memory multiprocessing (HFSS 7) makes HPC a software development imperative. ANSYS 1990 is committed to maintaining performance 1990 Shared Memory Multiprocessing for structural simulations leadership Iterative PCG Solver Introduced for large structural analysis 3 ANSYS, Inc. November 14, ANSYS, Inc. Proprietary

4 HPC Hardware Terminology Machine 1 (or Node 1) Core1 Core2 Core3 Core4 Processor 1 (or Socket 1) Core1 Core2 Core3 Core4 Processor 2 (or Socket 2) Interconnect (gige or Infiniband) Memory (RAM) Machine N (or Node N) Core1 Core2 Core3 Core4 Processor 1 (or Socket 1) Core1 Core2 Core3 Core4 Processor 2 (or Socket 2) Memory (RAM) GPU 4 ANSYS, Inc. November 14,

5 HPC A Software Development Imperative Clock Speed Leveling off Core Counts Growing Exploding (GPUs) Future performance depends on highly scalable parallel software 5 Source: ANSYS, Inc. November 14,

6 ANSYS Fluent Scaling Hardware (Intel Harpertown, DDR IB) 2010 Hardware (Intel Westmere, QDR IB) RATING IDEAL RATING IDEAL Number of Cores Systems keep improving: faster processors, more cores Ideal rating (speed) doubled in two years! ANSYS, Inc. November 14, Number of Cores Memory bandwidth per core and network latency/bw stress scalability 2008 release (12.0) re-architected MPI huge scaling improvement, for a while 2010 release (13.0) introduces hybrid parallelism and scaling continues!

7 ANSYS Fluent Scaling Extreme CFD Scaling s of cores Enabled by ongoing software innovation Hybrid parallel: fast shared memory communication (OpenMP) within a machine to speed up overall solver performance; distributed memory (MPI) between machines 7 ANSYS, Inc. November 14,

8 ANSYS Fluent Scaling 14.0 Improved HPC performance through Faster auto-partitioning for multi-core clusters Improved scalability for simulations with monitors enabled Optimized writing of cluster-to-cluster view factor data Cores: 1.1 million surface clusters R13 R million surface clusters ANSYS, Inc. November 14, Sample clusterto-cluster view factor data writing using 32-way parallel and InfiniBand Example data for scaling with R14 monitors

9 ANSYS Fluent Scaling 14.0 sedan_4m truck_14m Rating Rating NCores NCores truck_111m Rating HPC configuration 2-socket Intel Westmere hex-core 2.93 GHz 2 X 6= 12 cores per node QDR InfiniBand NCores 9 ANSYS, Inc. November 14,

10 ANSYS Fluent Scaling sedan_4m 2500 truck_poly_14m Rating Rating NCores NCores 350 truck_111m Architecture aware partitioning to minimize inter-machine communications Rating Hierarchy based hybrid AMG at coarsest levels 4-socket AMD Magny-Cour 2.3GHz 4 X 12 = 48 cores per node QDR InfiniBand NCores 10 ANSYS, Inc. November 14,

11 ANSYS CFD Scaling 14.0 Network-aware partitioning Original partitions are remapped to the cluster considering the network topology and latencies Minimizes inter-machine traffic reducing load on network switches Improves performance, particularly on slow interconnects and/or large clusters Partition Graph 3 machines, 8 cores each Colors indicate machines Original mapping New mapping 11 ANSYS, Inc. November 14,

12 12 ANSYS Fluent File I/O Performance 13.0 Case file IO Both read and write significantly faster in R13 A combination of serial-io optimizations as well as parallel-io techniques, where available Parallel-IO (.pdat) Significant speedup of parallel IO, particularly for cases with large number of zones Support for Lustre, EMC/MPFS, AIX/GPFS file systems added Data file IO (.dat) Performance in R12 was highly optimized. Further incremental improvements done in R13 ANSYS, Inc. November 14, 91.2 Parallel Data write truck_14m, case read R13 vs. R12 BMW -68% FL5L2 4M -63% Circuit -97% Truck 14M -64%

13 ANSYS Mechanical Scaling Sparse Solver (Parallel Re-Ordering) Focus on bottlenecks in Solution Rating Solution Rating R12.1 R13.0 Number of cores PCG Solver (Pre-Conditioner Scaling) R12.1 R13.0 the distributed memory solvers (DANSYS) sparse direct solver Parallelized equation ordering 40% faster w/ updated Intel MKL Preconditioned Conjugate Gradient (PCG) iterative solver Parallelized preconditioning step ANSYS, Inc. November 14, Number of cores

14 What about GPU Computing? CPUs and GPUs work in a collaborative fashion CPU GPU PCI Express channel Multi-core processors Typically 4-6 cores Powerful, general purpose Many-core processors Typically hundreds of cores Great for highly parallel code, within memory constraints 14 ANSYS, Inc. November 14,

15 ANSYS Mechanical SMP GPU 13.0 Solver Kernel Speedups Overall Speedups From NAFEMS World Congress May Boston, MA, USA Accelerate FEA Simulations with a GPU -by Jeff Beisheim, ANSYS 15 ANSYS, Inc. November 14, Tesla C2050 and Intel Xeon 5560

16 Distributed ANSYS Supports MDOF, Nonlinear Structural Analysis using the Distributed Sparse Solver GPU Acceleration can now be used with Distributed ANSYS to combine the advantage of GPU technology and the power of distributed ANSYS 16 ANSYS, Inc. November 14,

17 Distributed ANSYS Supports Distributed ANSYS 14.0 Total Simulation Speedups (ANSYS 13.0 benchmark problems) 4 CPU cores CPU cores + 1 GPU V13cg-1 (JCG, 1100k) V13sp-1 (sparse, 430k) V13sp-2 (sparse, 500k) V13sp-3 (sparse, 2400k) V13sp-4 (sparse, 1000k) V13sp-5 (sparse, 2100k) Windows workstation : Two Intel Xeon 5560 processors (2.8 GHz, 8 cores total), 32 GB RAM, NVIDIA Tesla C2070, Windows 7, TCC driver mode 17 ANSYS, Inc. November 14,

18 ANSYS Mechanical Multi-Node GPU Solder Joint Benchmark (4 MDOF, Creep Strain Analysis) Linux cluster : Each node contains 12 Intel Xeon 5600-series cores, 96 GB RAM, NVIDIA Tesla M2070, InfiniBand Solder balls Mold PCB Total Speedup R14 Distributed ANSYS w/wo GPU Without GPU With GPU 1.7x 1.9x 3.4x 3.2x 4.4x 16 cores 32 cores 64 cores 18 ANSYS, Inc. November 14, Results Courtesy of MicroConsult Engineering, GmbH

19 ANSYS Mechanical Multi-Node GPU Solder Joint Benchmark (4 MDOF, Creep Strain Analysis) Linux cluster : Each node contains 12 Intel Xeon 5600-series cores, 96 GB RAM, NVIDIA Tesla M2070, InfiniBand Solder balls 1 8 cores 1 8 cores, 1 GPU 2 4 cores, 2 GPU 8 1 core, 8 GPU 19 ANSYS, Inc. November 14, Mold PCB Results Courtesy of MicroConsult Engineering, GmbH

20 GPU Acceleration for CFD Radiation View Factor Calculation (ANSYS Fluent 14 - beta) First capability for specialty physics view factors, ray tracing, reaction rates, etc. R&D focus on linear solvers, smoothers but potential limited by Amdahl s Law 20 ANSYS, Inc. November 14,

21 Case Study HPC for High Fidelity CFD 8M to 12M element turbocharger models (ANSYS CFX) Previous practice (8 nodes HPC) Full stage compressor runs hours Turbine simulations up to 72 hours Current practice (160 nodes) 32 nodes per simulation Full stage compressor 4 hours Turbine simulations 5-6 hours Simultaneous consideration of 5 ideas Ability to address design uncertainty clearance tolerance ANSYS HPC technology is enabling Cummins to use larger models with greater geometric details and more-realistic treatment of physical phenomena ANSYS, Inc. November 14,

22 Case Study HPC for High Fidelity CFD EURO/CFD Model sizes up to 200M cells (ANSYS FLUENT) cluster of 700 cores cores per simulation 25 Millions (4 Days) 50 Millions (2 Days) 3 Millions of Cells (6 Days) 10 Millions (5 Days) Compressibility Conduction/Convection Supersonic Multiphase Radiation Increase of : Transient Optimisation / DOE Dynamic Mesh Requirement for Accuracy Complexity of models LES Combustion Aeroacoustic Fluid Structure Interaction 22 ANSYS, Inc. November 14,

23 Microconsult GmbH Case Study HPC for High Fidelity Mechanical Solder joint failure analysis Thermal stress 7.8 MDOF Creep strain 5.5 MDOF Simulation time reduced from 2 weeks to 1 day From 8 26 cores (past) to 128 cores (present) HPC is an important competitive advantage for companies looking to optimize the performance of their products and reduce time to market. 23 ANSYS, Inc. November 14,

24 Case Study HPC for Desktop Productivity Cognity Limited steerable conductors for oil recovery ANSYS Mechanical simulations to determine load carrying capacity 750K elements, many contacts 12 core workstations / 24 GB RAM 6X speedup / results in 1 hour or less 5-10 design iterations per day Parallel processing makes it possible to evaluate five to 10 design iterations per day, enabling Cognity to rapidly improve their design ANSYS, Inc. November 14,

25 Case Study Desktop Productivity Cautionary Tale NVIDIA - Case study on the value of HW refresh and SW best-practice Deflection and bending of 3D glasses ANSYS Mechanical 1M DOF models Optimization of: Solver selection (direct vs iterative) Machine memory (in core execution) Multicore (8-way) parallel with GPU acceleration Before/After: 77x speedup from 60 hours per simulation to 47 minutes. Most importantly: HPC tuning added scope for design exploration and optimization. 25 ANSYS, Inc. November 14,

26 Take Home Points / Discussion ANSYS HPC performance enables scaling for high-fidelity What could you learn from a 10M (or 100M) cell / DOF model? What could you learn if you had time to consider 10 x more design ideas? Scaling applies to all physics, all hardware (desktop and cluster) ANSYS continually invests in software development for HPC Maximized value from your HPC investment This creates differentiated competitive advantage for ANSYS users Comments / Questions / Discussion 26 ANSYS, Inc. November 14,

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