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  • Helping SMEs via SHAPE projects

    Dr. Monica de Mier

    CASE Business Development

    15/05/2019 EuroHPC Summit Week 2019

  • About BSC

  • About BSC

    General Purpose for current BSC


    11.15 Petaflops

    3,456 nodes of Intel Xeon Platinum


    390 Terabytes of main memory

    14 PB storage


    Technologies for evaluation

    of 2020 Exascale systems

    3 systems, each of

    more than 0.5 Pflops/s, with

    Power9+NVIDIA, ARMv8,


  • Earth Sciences


    Computer Sciences

    Life Sciences

    To influence the way machines are built, programmed and used: programming models,

    performance tools, big data, computer architecture, energy efficiency

    To develop and implement global and regional state-of-the-art models for short-

    term air quality forecast and long-term climate applications

    To understand living organisms by means of theoretical and computational methods

    (molecular modeling, genomics, proteomics)

    To develop scientific and engineering software to efficiently exploit supercomputing capabilities

    (automotive, aeronautics, biomedical, geophysics, energy, social simulations)

    About BSC

  • 2) Agreements with companies

    3) IPR protection

    1) Spin-offs and Licensing

    5) Exploitation in projects

    Management, support and


    4) Training for researchers

    BSC Technology Transfer

  • BSC Technology Transfer





  • Collaborations with companies

    • Juan Yacht Design (1st call)

    • Vortex Bladeless (2nd call)

    • FDD Engitec (3rd call)

    • BAC EGC (3rd call)

    • Artelnics (4th call)

    • E&M Combustion (5th call)

    • Fluidda (7th call)

    • Polyhedra Tech (7th call)

    SHAPE projects

  • E&M Combustion

    • Spanish SME that designs and manufactures combustion systems for industry, such as burners and boilers

    • Focuses on the energy and metal industries

    • Provides customized solutions for industrial combustion systems, creating equipment and designs that meet the customers’ requirements

    • Its business vision is focused on innovation seeking the highest energy efficiency and the lowest levels of pollutant emissions

  • E&M Combustion SHAPE Project Start date: October 2017 - June 2018 Objective: Characterization of the reacting flow field of the JBD-4500 combustor, with focus on the pollutant emissions Motivation: The R&D Department of EMC participated on this project with the target of evaluating and eventually incorporating high fidelity modeling techniques in their design process, aiming to strengthen the company’s position in the international market Tasks: 1. Setup burner specifications and boundary conditions 2. Pre-processing stage: CAD cleaning and mesh generation 3. Numerical simulations of the burner 4. Final report

  • E&M Combustion CAD cleaning

    Geometry simplification: • Eliminate sections 4 and 5 • Simplify section 3 • Remove screws, logos and rough surfaces

  • E&M Combustion Meshing

    Mesh 1: 2.5 million cells Mesh 2: 20 million cells Mesh 3: 48 million cells

    Unstructured meshes

  • E&M Combustion Numerical simulation

    • Software: ALYA (BSC’s multi-physics FEM parallel code) • Turbulence model: Large Eddy Simulation • Low-Mach number approximation • Projection method based on the Fractional step for velocity-pressure

    coupling in the momentum and continuity equations • Low-dissipation numerical scheme: time integration based on 3rd order

    Runge Kutta scheme for momentum and scalars • Flamelet combustion model • Chemical kinetics: San Diego mechanism • Turbulence-chemistry interaction: Presumed-shape PDF • This simulation was conducted in the supercomputer MareNostrum 4

    with 1,680 cores (35 nodes) spending about 150,000 CPU hours

  • E&M Combustion Numerical simulation

    Temperature Velocity module

  • E&M Combustion

    Time-averaged velocity module Time-averaged temperature

  • E&M Combustion Numerical simulation Distributions of pollutant emissions

    CO CO2 NO

    Snapshots of mass fractions of different pollutants at central plane at t=4.5s after ignition

  • Fluidda

    • Belgian SME that develops the Functional Respiratory Imaging technology

    • Combines CT scans with flow simulations to provide a service for phenotyping patients and monitoring the effectiveness of novel respiratory drugs

    • Offers this service to medical devices manufacturers and pharmaceutical industry to improve their inhalers and nebulizers for patients suffering from respiratory diseases and sleep-related breathing disorders

    • CFD is applied to the diagnosis and monitoring of respiratory diseases

  • Fluidda

    Computed Tomography scans are taken during inspiration and expiration to obtain data of a patient

    From CT scans, the patient- specific airway and lung structures are segmented and 3D reconstructed. These structures are the basis for functional analysis using CFD

    CFD analyses the motion of fluids and their interaction with surfaces and provide patient-specific parameters such as airway resistance and aerosol deposition characteristics

  • Fluidda SHAPE Project Start date: October 2018 - April 2019 Objective: Perform HPC simulations of particles deposition in human airways Motivation: “So far, we have been using commercial simulation software to provide our services. However, it falls short when accuracy in large-scale problems is required. And this service scenario is more and more frequent. Moreover, when commercial software is used, particle transport and deposition is both inaccurate and inefficient.” Tasks: 1. Geometry generation 2. Computational domain generation 3. Simulations for different type of particles 4. Simulation for different inflow conditions 5. Final report

  • Fluidda Geometry

  • Fluidda Mesh

    • Fine boundary layer mesh -> 70 million cells • Need to optimize the mesh

    Final mesh: 6.7 million cells

  • Fluidda Numerical simulation

    • Software: ALYA (BSC’s multi-physics FEM parallel code)

    • Turbulence modeling: LES Vreman Subgrid Scale Modeling

    • 6,697,178 elements (using ICEM)

    • > 100 inlet/outlet boundary surfaces

    • Total time 1s, time step 5e-4s

    • Density 1.225e-3 g/cm3, viscosity 1.78e-4 g/cm.s

    • Particles: • 21 types • Diameters: 9µm – 30µm • Injection time: 0.0 : 0.005 : 0.35s • Forces: Drag, gravity, buoyancy

    • Simulations run in 336 CPUs for 20 hours in MareNostrum4

    • A total of 240,000 CPU hours have been used

  • Fluidda Numerical simulation

    Particles trajectories

  • Polyhedra Tech

    • Spanish SME that builds simulation tools to optimize systems and operations

    • Its expertise includes: optimization of energy systems in terms of energy efficiency, consultancy for construction industry, near-zero energy buildings analysis, power energy systems, and certification for buildings among others

    • Uses SDL (modelling language) and SDLPS (distributed simulator enabling automatic translation of models defined using SDL into working simulations) * SDL Specification and Description Language * SDLPS Specification and Description Language Parallel Simulator

  • SHAPE Project Start date: October 2018 - April 2019

    Objectives: (1) Investigate novel parallelization strategies that can leverage HPC to accelerate the simulator runtime (2) Test, benchmark and optimize the simulator on social science models

    Motivation: Open up the potential of HPC to applications in social sciences and in particular through the implementation of agent-based simulations

    Polyhedra Tech

  • Polyhedra Tech

    1. System handover

    The SDLPS has been handed over to BSC team, learning of SDL language

    2. Runtime analysis

    Understood the simulator workflow and the technologies used to implement it

    3. Runtime optimisation

    Investigated the feasibility of parallelizing the simulator using OpenMP and MPI. Developed a proof-of-concept that translates a SDL model into C++ code and automatically parallelizes the code.

    4. Model implementation

    A classic social science model (‘Artificial Anasazi’) has been implemented in SDL, translated into compilable code and run on Marenostrum


  • Polyhedra Tech Use case: Artificial Anasazi

    • The agent-based simulations aim to reconstruct the rise and collapse of the ancestral Pueblo people who flourished in central USA between the end of the first century and mid second century BC

    • Artificial Anasazi model is