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Accelerating Computational Science and Engineering with Leadership Computing Accelerating computational science and engineering with leadership computing Jack C. Wells Director of Science Oak Ridge Leadership Computing Facility NVIDIA Theatre @ SC13 Office of Science Big Problems Require Big Solutions Climate Change Energy Healthcare Competitiveness 2 What is the Leadership Computing Facility (LCF)? • Collaborative DOE Office of Science • Highly competitive user allocation program at ORNL and ANL programs (INCITE, ALCC). • Mission: Provide the computational • Projects receive 10x to 100x more and data resources required to solve resource than at other generally the most challenging problems. available centers. • 2-centers/2-architectures to address • LCF centers partner with users to diverse and growing computational enable science & engineering needs of the scientific community breakthroughs (Liaisons, Catalysts). 3 #2 Titan System (Cray XK7) 27.1 PF 24.5 PF 2.6 PF Peak Performance 18,688 compute nodes GPU CPU LINPACK Performance 17.59 PF Power 8.2 MW System Memory 710 TB total memory Gemini High Speed Interconnect 3D Torus Interconnect Storage Luster Filesystem 32 PB High-Performance Archive 29 PB Storage System (HPSS) I/O Nodes 512 Service and I/O nodes 4 High-impact science at OLCF: Four of Six SC13 Gordon Bell Finalists Used Titan Peter Staar Massimo Bernaschi Michael Bussmann Salman Habib ETH Zurich ICNR-IAC Rome HZDR - Dresden Argonne High-Temperature Biofluidic Superconduc4vity Systems Plasma Physics Cosmology Taking a Quantum 20 Petaflops Radiave Signatures HACC: Extreme Leap in Time to Simulaon of of the Relavisc Scaling and Soluon for Protein Kelvin-Helmholtz Performance Simulaons of High-TC Suspensions in Instability Across Diverse Superconductors Crowding Architectures Condions Titan Titan Titan Sequoia (15.4 PF) (20 PF) (7.2 PF) (13.9 PF), Titan 5 Science challenges for LCF in next decade Combustion Science Climate Change Science Increase efficiency by Understand the dynamic 25%-50% and lower ecological and chemical emissions from internal evolution of the climate combustion engines using system with uncertainty advanced fuels and low- quantification of impacts. temperature combustion. Fusion Energy Biomass to Biofuels Develop predictive Enhance the understanding understanding of plasma and production of biofuels for properties, dynamics, and transportation and other bio- interactions with products from biomass. surrounding materials. Optimized Accelerator Designs Solar Energy Optimize designs as the next Improve photovoltaic generations of accelerators . efficiency and lower Detailed models are needed to cost for organic and provide efficient designs of new inorganic materials. light sources. 6 Solar energy Key science challenges: Improve photovoltaic efficiency and lower cost for organic and inorganic materials. A photovoltaic material poses difficult challenges in the prediction of morphology, excited state phenomena, transport, and materials aging. Corse-grained MD simulation of phase-separation of a 1:1 weight ratio P3HT/PCBM mixture into donor (white) and acceptor (blue) domains. Science enabled by LCF Capabilities 2013-2016 2016-2020 • Understand growth, interface structure, and • Enable computational screening of stability of heterogeneous polymer blends materials for desired excited-state and necessary for efficient solar conversion. charge transport properties. • Simulations of structure, carrier transport, • Systems-level, multiphysics simulations and defect states in nanomaterials. of practical photovoltaic devices are • Describe excited state phenomena in enabled. homogeneous systems. • Uncertainty quantification enabled for critical integrated materials properties. 7 8 LAMMPS Early Science Project Towards Rational Design of Efficient Organic Jan-Michael Carrillo, ORNL Mike Brown, ORNL Photovoltaic Materials Science Objectives and Impact P3HT PCBM (electron donor) (electron acceptor) • Organic photovoltaic (OPV) solar cells are promising renewable energy sources: – Low costs, high-flexibility, and light weight • Bulk-heterojunction (BHJ) active layer morphology and domain size is critical Corse-grained MD simulation of phase-separation for improving performance of a 1:1 weight ratio P3HT/PCBM mixture into donor (white) and acceptor (blue) domains. Titan Simulation: LAMMPS Preliminary Science Results • Portability: Builds with CUDA or OpenCL • Titan simulations are 27x larger and 10x longer • Speedups on Titan (GPU+CPU vs. CPU: – Converged P3HT:PCBM separation in 400ns 2X to 15x (mixed precision) depending CGMD time upon model and simulation • Prediction: Increasing polymer chain length will – Speedup of 2.5-3x for OPV simulation decrease the size of the electron donor domains used here • Prediction: PCBM (fullerene) loading parameter results in an increasing, then decreasing impact on P3HT domain size 9 Biomass to biofuels Key science challenges: Enhance the understanding and production of biofules from biomass for transportation and other bio-products. The main challenge to overcome is the recalcitrance of biomass (cellulosic materials) to hydrolysis. Lignin interacting with crystalline cellulose. Science enabled by increasing LCF Capabilities 2013-2016 2016-2020 • Atomic-detail dynamical models of biomass • Understand the dynamics of enzymatic systems of several million atoms, permitting reactions on biomass by simulating detailed analysis of interactions interactions between microbial systems and cellulosic biomass • Simulations of pretreatment effects on multi- component biomass systems to understand • Design superior enzymes for the bottlenecks in bioconversion conversion of biomass 10 11 INCITE Program Boosting Bioenergy and Overcoming Jeremy Smith Oak Ridge National Laboratory Recalcitrance 23 M Titan core hours Molecular Dynamics Simulations Science Objectives and Impact • Optimize biomass pretreatment process by understanding lignin-cellulose interactions on a molecular level • Overcome biomass recalcitrance caused by lignin and the tightly ordered structure of cellulose • Improve efficiency of the biofuel production process Interaction between cellulose fibril (blue) and lignin (pink and green) molecules. and make ethanol less costly Vizualization by M. Matheson (ORNL) Science Results Application Performance Published paper in Biomacromolecules in August • 2012: Used GROMACS on Jaguar to monitor 2013 interactions of 3 million atoms that included crystalline and non-crystalline cellulose, lignin, • Discovered amorphous cellulose is easier to and water break down because it associates less with • 2013: Now run accelerated GROMACS that lignin can take advantage of Titan’s GPUs, making the application 10 times bigger and much • Phenomenon is not a result of direct interaction longer. Current simulations monitor 30 million between lignin and cellulose, but is a water- atoms. mediated effect 12 13 ALCC Program Non-Icing Surfaces for Cold Climate Masako Yamada GE Global Research Wind Turbines 40 M Titan core hours Molecular Dynamics Simulations Location of ice Science Objectives and Impact nucleation varies dependent on • Understand microscopic mechanism of water temperature droplets freezing on surfaces and contact angles. • Determine efficacy of non-icing surfaces at different Visualization by M. Matheson operation temperatures (ORNL) Science Results Replicated GE’s experimental results: Hydrophilic Hydrophobic • Hydrophobic surfaces delay the onset of Performance Achievements nucleation • 5X speed-up from GPU acceleration • The delay is less pronounced at lower • Achieved factor 40X speed-up from new temperatures interaction potential for water 14 Center for Accelerated Application Readiness (CAAR) • Focused effort to prepare • Application Teams applications for accelerated – OLCF application lead architectures – Cray engineer – NVIDIA developer • Goals: – Others: local tool & library developers, other – Work with code teams to develop computational scientists and implement strategies for exposing hierarchical parallelism • Single early science problem for our users applications targeted for each app – Maintain code portability across modern architectures • Explore multiple approached for – Learn from and share our results each app – Determine maximum acceleration • Selected six applications from – Determine reproducible path for different science domains and other applications algorithmic motifs 15 Early Science Challenges for Titan WL-LSMS LAMMPS Illuminating the role of A molecular dynamics material disorder, simulation of organic statistics, and fluctuations polymers for applications in nanoscale materials in organic photovoltaic and systems. heterojunctions , de- wetting phenomena and IMPLICIT AMR FOR EQUILIBRIUM RADIATION DIFFUSION 15 biosensor applications CAM-SE Answering questions S3D about specific climate Understanding turbulent change adaptation and combustion through direct mitigation scenarios; numerical simulation with realistically represent complex chemistry. features like precipitation . patterns / statistics and tropical storms. t = 0.50 t = 0.75 Denovo NRDF Discrete ordinates Radiation transport – radiation transport important in astrophysics, calculations that can laser fusion, combustion, be used in a variety atmospheric dynamics, of nuclear energy and medical imaging – and technology computed on AMR grids. applications. t = 1.0 t = 1.25 16 Fig. 6.6. Evolution of solution and grid for Case 2, using a 32 32 base grid plus 4 refinement levels. Boundaries of refinement patches are superimposed on a pseudocolor× plot of the solution using a logarithmic
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