Spécial simulation (2019) - A year of simulation by INFOPRO DIGITAL

www.usinenouvelle.com www.industrie-techno.com

special future magazine 2 . april 2019 . not to be sold separately

AUTOMOTIVE, AERONAUTICS, ENERGY, CHEMISTRY...

A YEAR OF SIMULATION INTERVIEW Ã&#x2030;ric Landel Expert leader in numerical modelling at Renault

INNOVaTION Living organisms go virtual

agRIculTuRE Algorithms for farms

RESEaRcH French AI gets a boost from HPC

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CEA at the heart of innovation for extreme computing and Big Data CEA and Bull are co-designing exascale technologies

Harnessing exascale computing and data processing will open unexplored perspectives for the numerical simulation of complex physical phenomena and

TERA1000,developedinpartnershipwithAtos/BullaccordingtoCEA requirementsandinstalledin2016,isforeshadowing exascalesupercomputers.

industrial objects, by 2020 and beyond. In order to tackle this challenge, CEA, in partnership with Atos, is co-designing technologies to: Reduce energy consumption Process and manage massive flows of data Increase performance, efficiency and modularity of supercomputer architectures Design fault-tolerant architectures

1 - At the scale of a billion of billions of operations per second (exaFlops) and memory bytes (exaBytes).

CEA boosts industrial innovation Located at CEA Bruyères-le-Châtel site, TGCC (CEA Very Large Computing Centre) hosts CCRT (Computing Centre for Research and Technology), a shared infrastructure optimized for HPC. CCRT partners receive 2.4 Pflops of computing power, as well as services and expertise supported by CEA HPC team skills – an essential asset for their numerical simulations. CCRT partners: ArianeGroup, Cerfacs, EDF, IFPEN, Ingeliance, Ineris, IRSN, L’Oréal,Onera, Safran Aero Boosters, Safran Aircraft Engines, Safran Helicopter Engines, Safran Tech, Synchrotron Soleil, TechnicAtome, Thales, Thales Alenia Space, Total, Valeo, CEA as well as France Génomique consortium (supported by French government PIA). 2 TO KNOW MORE

www-ccrt.cea.fr

Numericalsimulationof combusioninanhelicopter turbo-engine. TURBOMECA

Motor-driven fansimulation. VALEO

Simulationofsurface currentsonanaircraft nose radome. THALES

CONTACT christine.menache@cea.fr

SIMULATION SOMMAIRE

INTERVIEW Éric Landel Renault’s expert leader in numerical modeling and simulation P. 4

ESSENTIALS

Strategic Issue

Microsoft has Launched Virtual-Reality Prototyping P. 6 Japan is Building its own Supercomputer Processor P. 8

Europe’s Chip Industry is at a Turning Point P. 14 De Buyer, Simulation as a Growth Driver P. 16

DOSSIER ON THE COVER

Living Organisms Go Virtual

Hybridization with AI is opening up new horizons for simulation.

P. 18

LIVING WORLD

Simulation’s New Horizon

P. 20

INTERVIEW

Hugues Berry, INRIA’s deputy scientific director, in charge of digital health, biology, and earth research P. 22

MANUEL MORAGUES

DEPARTMENT HEAD FOR INNOVATION, DIGITAL AND INDUSTRY OF THE FUTURE

PHARMACEUTICALS COSMETICS Simulation at Every Level

P. 24

AGRICULTURE

Algorithms for Farms

P. 28

SURVEY COMPUTING

Quantum Technology in Industry

P. 32

RESEARCH

French AI gets a boost from HPC

P. 36

SUPERCOMPUTERS

Europe is Going on the Offensive

P. 40

PORTFOLIO

Simulation in all its forms

P. 44

ON THE COVER Numerical representation of the Earth’s core in the plane of the equator, modelled by the Institute of Earth Sciences.

Président, directeur de la publication Julien Elmaleh Directrice de la rédaction Christine Kerdellant Directrice adjointe de la rédaction Anne Debray Responsable éditorial Manuel Moragues Rédacteur en chef édition Guillaume Dessaix Directeur artistique Vincent Boiteux

Secrétariat de rédaction Rebecca Lecauchois, Claire Nicolas Maquette Laurent Pennec, Sylvie Louvet, Philippe Juncas, Carol Müller

TARIFS ABONNEMENTS FRANCE (TVA : 2,1 % incluse) 1 an : 349 euros TTC 1 an étudiant : nous consulter. Étranger : nous consulter. Règlement à l’ordre de « L’Usine Nouvelle ». Pour l’Union européenne, préciser le numéro de TVA intracommunautaire.

ehind the sweet-sounding name of Aurora lies a powerful beast.Thissupercomputer,whosearchitecturewaspresented bythe U.S.Department ofDefenseinmid-March, willbeable to perform more than 1 quintillion floating-point operations per second. That is five times more than the current record held by the Summit supercomputer, which is also American. Manufactured by Intel and Cray, Aurora is due to go into service in 2021. It will be the top exascale supercomputer in the USA, although perhaps not in the world due to fierce competition from China, Europe, and Japan. “Together with Europe, France is in this race for digital equipment,” said a delighted Bruno Sportisse, CEO of INRIA. After losing ground, Europe went on the offensive with its EuroHPC initiative. Within a few months, this project has rallied eighteen European countries to the seven already involved and secured a budget of 1 billion euros. According to Mariya Gabriel, the European commissioner for digital economy and society, this project is “a driving force to reconquer”. It aims to equip Europe not only with exascale supercomputers but also a processor made in Europe, to be free of depending on US technology. There is widespread awareness that high-performance computing isacorestrategicissueforbusinessesandtheeconomy.Ourinterview with Éric Landel, Renault’s expert leader in numerical modelling and simulation, shows this well. Renault’s industrial-scale simulation in its Model Factory achieved unrivalled performance to design the new Clio 5, thus makinghuge savings.The example of Renault also shows how simulation methods are developing, using artificial intelligence (AI) at a time when AI is using supercomputers more and more. This hybridization between high-performance computing and AI is opening up new horizons for simulation. Living organisms are now modelled from every angle. The pharmaceuticals and cosmetics industries use simulation to mass predict molecule properties and to increase in-silico tests before launching expensive clinical trials. Agriculture is at the dawn of a technological leap forward, from research on new plant varieties to using algorithms for farm management. NISQ technology, a sort of proto-quantum computer that industrial groups such as Total and EDF are counting on, could speed up all this progress even more.

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Dépôt légal 2e trimestre 2019 - Autor. minist. 29-957.29382. Imprimé par Imprimerie de Compiègne, avenue Berthelot, ZAC de Mercières, BP 60524, 60205 Compiègne Cedex - Numéro d’enregistrement à la Commission paritaire pour les publications non quotidiennes 0712 T 81903. N° ISSN: 0042.126 X. Éditeur: Groupe Industrie Services Info, Société par actions simplifiée au capital de 38628352euros. Siège social: 10, place du Général-de-Gaulle 92160 Antony. 309.395.820 RCS Nanterre. Directeur de la publication: Julien Elmaleh

PHOTOS DE COUVERTURE : N. SCHAEFFER / ISTERRE / CNRS ; ÉDITO : P. GUITTET

IntervIew Éric landel

“Simulation iS a deciSionmaking tool” Renault’s expert leader in numerical modeling and simulation explains the key role of this activity at the car manufacturer and the changes currently under way.

IntervIewed by Manuel Moragues

What place does simulation have at Renault?

Numerical simulation is a tool to serve engineering. It generates data to help define engines, vehicle systems, and the vehicle itself. It’s an extremely effective tool since working on data avoids physical objects, which are time-consuming and expensive to use. Crash simulation accounts for the bulk of our spending since it involves a very large model with a lot of complex physics. In addition, many test crashes have to be carried out. The aerodynamics model, which needs to be very detailed to capture the phenomena involved, comes second, while the engine combustion model is our third biggest expense.

How do you use simulation to develop a vehicle?

First, there is the design phase, which has to settle on a vehicle sketch. We can use simulation to assess the performance of this sketch, modifying and reassessing it if it’s not up to scratch. Thanks to

increased computing capacity, we can use simulation to explore many concepts. Simulation also has a role in decision-making by measuring the impact of many variants. For example, can we increase mass without ruining mechanical performance? Or can mechanical performance be improved without compromising vibration behavior? Or again, can we reduce aerodynamic drag while also improving crash performance? Simulation helps project managers find the best compromise between often conflicting goals.

Next comes the tuning and validation phase.

Once the design has been settled on, we still have to carry out fine-tuning, especially on the dozens of computers controlling the various sub-systems, and vehicle road tests. Simulation is speeding all this up. In particular, we use a hardware-in-the-loop strategy, in which physical objects are operated in a simulated environment. For example, an engine can be driven by a virtual driver to reproduce situations close to reality. This makes road tests quicker since the engine has been pre-calibrated to be efficient in real conditions. We want to extend this approach to entire vehicles in order to tune and test advanced driver-assistance systems: by tricking vehicles’ sensors, we will be able to confront vehicles with every situation.

l’usine nouvelle SPECIAL FEATURE MAGAZINE 2 § APRIL 25 2019

“We use a hardware-in-theloop strategy, in which physical objects are operated in a simulated environment.”

What computing facilities does Renault have?

We’re currently increasing our HPC capacity and by the end of this year we’ll have around 1 petaflops [ed. note: 1 petaflops equals 1 quadrillion floating point operations per second]. This will place Renault in a good average compared to other car manufacturers. Our computing capacity is centralized in a datacenter near our Guyancourt Technocentre (Yvelines) and is operated as a private cloud by a service provider. These resources are used by all of Renault’s entities worldwide. The point of centralizing them is to facilitate very large-scale computing.

Three years ago, you also centralized your simulation teams in a Model Factory. Why?

The Model Factory centralizes our simulation work on the most complex systems since they need many resources within a very short time to deliver results quickly. We have 500 people in our technocentre and joint Renault-Nissan facility in Chennai, India. These facilities generate big data so that engineers

dominique fontenat

IntervIew

can make the best possible choices. The principle behind the Model Factory is to industrialize simulation. It operates like a factory: stocking up with data, which it transforms and collects to deliver virtual objects that are models of entire vehicles. Roughly the same methods can be applied to these models as to physical production lines: automating operations with robots to speed them up and avoid human errors, carrying out systematic quality controls, etc.

What have you got out of organizing things in this way?

We’ve made enormous progress on the time needed to supply models and on their accuracy. We’ve just seen this with the Clio 5 presented at the Geneva International Motor Show. This is now our benchmark for simulation performance. Crash models in particular have enabled us to very accurately predict how structures will behave. Acoustic and aerodynamics models have also proved very accurate. We’ve produced an excellent set of results that has saved the company a lot of money by avoiding design changes and complex analyses on physical vehicles.

How could you make even more progress? There is a lot of talk about artificial intelligence (AI).

We’re working intensively on AI as part of model

“Numerical simulation will supplement physical validation. It’s something relatively new that’s going to really expand.”

downscaling techniques. For example, a welding point: thousands of components are needed for a detailed model, but it’s impossible to model each of the thousands of welding points on vehicle bodywork. Instead of this, the detailed model will be used to train an AI algorithm to reproduce it. This gives a much smaller model of the initial model, which can be integrated into the bodywork model. It’s a very promising technique since it’s enabling us to change the scale of models. It could have a massive application for indirectly integrating models of very detailed components into system models.

introducing complex perception systems. What’s really new in this respect is the extreme variability of the vehicle’s environment. It’s impossible to physically expose vehicles to every possible situation. Numerical simulation will supplement physical validation. It’s something relatively new that’s going to really expand. It will be especially difficult to prove that autonomous-drive vehicles are reliable. Apart from the mathematical aspect of this proof, which we’re working on, many situations will have to be simulated. We’re talking about numerically simulating hundreds of millions of kilometers driven, for which huge computing resources will be required. We think that most of our investment in computing capacity will be taken up by this need to validate autonomous-drive vehicles. www.usinenouvelle.com

How is simulation affected by the disruptive triangle of electrification, autonomous drive and connectivity technology?

It’s having a major impact. We need to develop appropriate methodologies, especially for electrification, in which we’re investing heavily. Connectivity also means that vehicles must be modeled in their telecom infrastructure. Finally, autonomous drive is

TheessenTials A YeAr of SimulAtion

Development

nViDiA iS trAining robotS

this very realistic simulator reproduces on a spherical screen headlights illuminating the road.

Car Design

Renault is simulating HeadligHts witH Helios

Software

microSoft hAS lAuncheD VirtuAlreAlitY PrototYPing At the end of October 2018, Microsoft quietly introduced its Maquette software, designed so that developers can create 3D virtual-reality prototypes quickly. Available in a closed beta version, this application recalls creative tools such as Tilt Brush, Google Blocks, Oculus Medium and Quill, although does not extend to outright artistic creation. Microsoft has unveiled several examples of creations: a video-game concept, a representation of a supermarket shopper pathway, a mockup of a neighborhood in a large town, etc. Maquette is intended to be integrated into designers’ and developers’ workflow. Objects and scenes can be imported into Unity (FBX or glTF formats) using a plug-in. This software is compatible with the virtualreality headsets in Windows Mixed Reality ecosystem, as well as with Oculus Rift and HTC Vive. § J. B.

immeRsion

This US company, which specializes in graphics processing units, has developed a hyper-realistic robotics simulator. The latest version of its Isaac platform, launched in March 2018, enables robotics applications to be created directly from a software development kit. NVIDIA is highlighting how simple its framework, which makes it easier to transfer data in robots and modify their architecture by adding or removing sensors and actuators in realtime, is to use. Isaac’s ability to simulate ultra-realistic scenarios is presented as its main benefit. According to NVIDIA, this system can train a robot in just a few minutes. Once a virtual robot has been trained and tested, it can be transferred to a physical robot. This physical robot must obviously be fitted with a Jetson embedded processor. § J. B.

l’usine nouvelle SPECIAL FEATURE MAGAZINE 2 § APRIL 25 2019

On the fringes of the 2018 Driving Simulation Conference in Juan-lesPins (Alpes-Maritimes) last September, Renault announced the creation of a new headlight simulator. Called Helios in reference to the Greek god of the sun, this simulator will enable Renault to run very realistic tests of its vehicle headlights. Ensuring that headlights are illuminating the road properly usually requires many tests with physical prototypes, which are then modified according to testers’ feedback. This is a long, expensive process. Renault realized the advantage of using virtual reality for this task: to cut costs and development lead-times, as well as obtain more agility and leeway for innovation. The technical challenge was to obtain a rendering that matches actual road conditions as accurately as possible.

Renault therefore invested in the Helios solution, which has 4K resolution similar to the human eye, very high contrast (essential to simulate lighting on roads at night), and a stereoscopic spherical screen display. The stereoscopy can perceive depth, which makes the simulator much more realistic. This simulator was designed by Immersion, a Bordeaux-based systems integrator. It features eight Sony VPLGTZ280 laser video projectors and six Arttrack5 motion-tracking cameras. Each projector provides an image at a resolution of 4096 x 2160 pixels. Everything is projected onto a 225-degree spherical screen, with real-time image blending managed by Scalable Display software. All Renault has to do to run its tests is position a prototype in the simulator. It can then quickly iterate and assess the effect of changes made. § Julien Bergounhoux

www.usinenouvelle.com

TheessenTials A YeAr of SimulAtion

research

mineS PAriStech iS Putting PreDictiVe Science At inDuStrY’S DiSPoSAl Since autumn 2018, Mines ParisTech engineering school has been running one of the most ambitious predictive science research projects for industry of the future: the MINDS (Mines Initiative for Numerics and Data Science) program. With a budget of 1.2 million euros, and bringing together fifteen research centers, five postdoctoral researchers and two PhD students, MINDS aims to “create a digital platform for joint research and development, combining the fields of numerical simulation and artificial intelligence to give manufacturers precise, comprehensive answers,” explained Elie Hachem, head of the MINDS program and a professor at Mines ParisTech. These developments seek to speed up the product design/industrial production cycle via real-time machine learning. Artificial intelligence will enable physical parameters to

be tested immediately, studying the effects on a digital twin. Likewise, this tool will be used to predict how materials behave and their life span under specific conditions. “We’re switching to a completely different simulation scale since we’ll be working with a multi-scale, multi-physical model,” added Hachem. For example, this type of platform could further reduce development time for cars (currently 3-4 years) and aircraft (6-7 years). Safran is one of several manufacturers that have expressed interest in MINDS. “AI is currently dominated by the GAFA companies. MINDS is actually intended for our core business,” said Christian Rey, emeritus expert at Safran Tech, the group’s R&T center. It is relevant for many sectors: transportation, obviously, as well as energy (deep drilling, nuclear, etc.), and metallurgy. The

first proofs of concept are expected this year. “It was only logical for Mines ParisTech to lead this program since we devote around half our research potential to predictive science,” said Vincent Laflèche, director of Mines ParisTech. The school has boosted this project by introducing new teaching on big data throughout its engineering courses from September 2019 onwards. Mines ParisTech is also behind many predictive-science research programs in fields as diverse as solar energy (SoDa project), deep drilling (Dig3D), and numerical simulation to model the behavior of materials (Forge). § guillAuMe leCoMPTeBoineT

Augmented Surgery

In September 2018, the Food and Drug Administration (FDA), the US health agency that regulates drugs and medical devices, approved a medical-display device integrating Microsoft’s HoloLens headset. This is a world first. The solution, called OpenSight, is marketed by the US company Novarad, which was set up in 1998 and specializes in medical imaging. The device enables interactive superimposition of 2D and 3D images on patients’ bodies, thus enabling surgeons to prepare operations (the FDA has only approved its use for the pre-operation phase). Images

are projected onto patients to ensure precise positioning. Novarad is highlighting the time saved and the more detailed view of patient anatomy obtained, which ensure higher quality, safer operations. Body parts to be avoided during an operation can be detected, while virtual tools and guides can also be positioned to study the best surgical procedure to adopt. Several headsets can be used simultaneously to train students or enable several surgeons to plan an operation. A learning version of this software is also available. Surgical use of immersive technology is developing rapidly. Several

novaRad

hololenS Are helPing SurgeonS PrePAre their oPerAtionS

solutions using HoloLens are currently being developed for operating rooms, including some in France. § J. B.

surgeons can use microsoft’s Hololens headset to superimpose images of patients’ anatomy onto their body in real-time.

TheessenTials A YeAr of SimulAtion

Strategy

In 2018, Japan passed a crucial milestone in its race for exaflops supercomputers. Last summer, the computer manufacturer Fujitsu finished developing the processor that will power Post-K, Japan’s future exaflops supercomputer. This home-made processor is the first in the world to be based on a 512bit ARMv8-A SVE instruction set made by Advanced RISC Machines (ARM Holdings). This originally British company has been part of the Japanese giant Internet Softbank since September 2016. It is therefore the first 100% Japanese supercomputer processor. Japan’s currently most powerful supercomputer, ABCI, was built by Fujitsu using Xeon processors made by the US firm Intel, which is at the heart of 92% of the world’s supercomputers. With 19.9 petaflops of computing power (1 petaflops equals 1 quadrillion floating

RIken xxxxxxxxxxxxxxxx

Japan is Building its own supercomputer processor

point operations per second), it held seventh place in the 2018 TOP500 ranking of the world’s most powerful supercomputers. It is currently installed in the National Institute of Advanced Industrial Science and Technology, on the University of Tokyo’s Kashiwa campus. In around 2021, Post-K should succeed K-Computer, which has been at Kobe’s Riken

Research Institute since September 2012. The goal is to achieve exaflops power (1 exaflops equals 1 quintillion floating point operations per second), which means a hundredfold increase in current capacity. With 10.5 petaflops of computing power, K-Computer is Japan’s third most powerful supercomputer and the 18th most powerful in the world. It

Video

NVIDIA presented an innovative artificial-intelligence technique at the NeurIPS conference in Montreal (Canada) last December. It uses a neural network to apply in real-time 3D video graphics onto an environment. Traditionally, every object in a 3D real-time scene has to be modeled individually. With this new technique, a neural network trained by videos can create 3D models of buildings, trees, vehicles and objects on its own. According to NVIDIA, this technology will, in the long-term, enable developers to create entire virtual worlds containing photorealistic graphics much faster (and more cheaply) than by doing it manually. These worlds could be used for video games and simulation involving cars, architec-

nvIDIA

A neurAl network CreAting 3D grAphiCS in reAl-time

An impressively realistic virtual world (right) recreated by AI in 3D and real-time from a video (left). ture, and robotics. The most obvious use case would be to recreate highfidelity versions of existing locations. Nevertheless, Bryan Catanzaro, vicepresident of applied deep learning research at NVIDIA, stressed at a press conference that the project is only at the research stage, and that it will take several years before this result is possible. According to

l’usine nouvelle SPECIAL FEATURE MAGAZINE 2 § APRIL 25 2019

Catanzaro, one of the first actual uses will be to create photorealistic personalized avatars for the videogame industry. “You’ll be able to play as yourself.” The example presented at the conference was a small car driving game, which takes place in a town the neural network reconstructed from videos. § J. B.

TheessenTials A YeAr of SimulAtion

Destined to succeed the Riken Institute’s k-Computer in kobe, Post-k will have computing power of 1 exaflops.

was built by Fujitsu using UltraSPARC processors; this technology was supplied by the US firm Oracle.

InspIred by ChIna

The Post-K project was launched in 2014 with a 130-billion yen investment (1.2 billion dollars). Fujitsu was initially hesitating between

Intel’s Xeon processors and Oracle’s UltraSPARC processors. In 2016, it decided to develop its own processor, copying China which had just unveiled its first supercomputer powered by a 100% Chinese processor. Japan justified this change by saying it wanted to be free of depending on US technology and because it had to meet the challenge for power consumption presented by switching to exaflops scale. ARM architecture is known for its energy efficiency and is therefore the preferred technology for mobile devices. The challenge lies in achieving the power required by supercomputers. Post-K should consume 30 to 40 megawatts; this is expected to make it 30 to 40 times more energy efficient than the current K-Computer, which guzzles 12.7 megawatts. The processor developed by Fujitsu is still at the prototype stage. It features 48 processing cores, with another 4 cores for input-output and interfaces. In June 2018, Fujitsu presented its processor at the ISC supercomputing conference in Frankfurt, Germany. But the details were unveiled in August at the Hot Chips 30 symposium in California. Etched using the 7-nm process, this chip, called

Report

mAnufACturerS prefer AugmenteD reAlitY Although augmented reality appeared later, it has now overtaken virtual reality among manufacturers. According to a report published by the consulting firm Capgemini in September 2018 (which surveyed the CEOs of 709 companies), 66% of them think “augmented reality is more applicable to their business than virtual reality.” This report, entitled Augmented and Virtual Reality in Operations: a Guide for Investment, also shows the differing degree to which this

technology has been implemented. In the companies surveyed that use augmented reality, 45% are still at the rollout stage (the rest are experimenting with it). This compares to 36% of companies that opted for virtual reality. “Virtual reality isn’t that suitable for us,” explained Antti Aarnio, head of digital services at Fingrid, the operator of Finland’s national electricity transmission grid, in the report. “In contrast, once it passes safety standards, augmented reality could provide added value for our employees in high-risk situations, for example, being able to tell if a piece of equipment is under high voltage or high temperature.” “Augmented reality provides virtual added value to physical operational realities. It creates a digital link with the real world, opening up possibilities for many innova-

A64FX, contains 8.7 billion transistors and has computing power of 2.7 teraflops (1 teraflops equals 1 trillion floating point operations per second). To achieve exaflops power, 370,000 of these chips will have to be combined in the same supercomputer. This development is being closely monitored in Europe, where the consortium European Processor Initiative run by the French firm Atos is also developing a supercomputer processor. This is considered a strategic project for Europe’s technological independence. The question remains as to which technology Europe should rely on. Although ARM would have been the ideal solution, it is no longer a European company. § Ridha LoukiL www.usinenouvelle.com

tive applications. The benefits and return on investment are obvious and immediate,” summed up Patrice Duboé, innovation executive vice-president within the CTIO office of Capgemini and CTO of Capgemini engineering services, to L’Usine Nouvelle. He added: “It has many advantages: saving time on installation and repair work, limiting interpretation errors, improving efficiency, traceability, inspection, and validation. But the most fundamental advantage is in improving the environment and working conditions. This is a major issue for new generations.” § MaRion GaRReau

TheessenTials A YeAr of SimulAtion

BMW

The Car industry

BMW is stepping up its AutonoMous Driving

ast summer, the BMW Group began building a new driving simulation center at FIZ, its main research and innovation center, north of Munich (Germany). Some 160 staff will work at this 11,400 square meter site, which will have fourteen simulators: those that BMW already possesses, together with two high-tech simulators to be built by Bosch Rexroth. The visual component of these units, as well as the software integration, will be supplied by Autonomous Vehicle Simulation, a joint venture between Oktal and Renault set up in July 2017. This 100 million euro investment will have to cater to research requirements on autonomous vehicles, which BMW regards as one of its strategic priorities. The project is part of BMW’s FIZ Future plan, which aims to double the group’s R&D facilities by 2050. The future center’s star piece of equipment will be a high-fidelity dynamic simulator, enabling

A high-fidelity simulator, combining transverse, lateral and rotational movements, will simulate driving in urban environments, which autonomous cars still find challenging.

BMW has invested 100 million euros in its future autonomous-driving simulation center. Based in FIZ, north of Munich, it will become operational in 2020 and will feature 14 simulators.

longitudinal, transverse, and rotational acceleration movements of up to 1 g to be carried out simultaneously. This will make the simulator more realistic and enable new types of simulation, including urban driving, which is very tricky for autonomous vehicles to cope with. The tool will replicate evasive maneuvers, emergency braking, and hard acceleration. The second simulator will provide a very realistic experience on a 400 square meter motion area. It will be used for braking and accelerating on bends, negotiating roundabouts, and rapid series of complex maneuvers. Both systems will be able to accommodate complete replicas of vehicles attached to a platform mounted on a hexapod system. A stereoscopic reproduction of the environment will be presented via projectors. The objective is to quickly test solutions to improve vehicle reaction time and make the human-machine interfaces better adapted to human behavior. Furthermore, the capacity of these simulators will enable BMW to run laboratory tests of many scenarios hitherto confined

l’usine nouvelle SPECIAL FEATURE MAGAZINE 2 § APRIL 25 2019

to roads. BMW will be able to change every aspect of a given scenario so that all eventualities are taken into account very early on in system development. As a result, systems will not have to be changed when they are almost finished. BMW also plans to exploit simulation to more precisely establish the right balance between performance and user comfort. In addition, simulation will be used to detect situations in which drivers are distracted. Which is a better way to learn these lessons rather than later on the road. § Julien Bergounhoux www.usinenouvelle.com

Invented in the 1800s. Optimized for today.

l h von Mises stress distribution d b h housing h Visualization off the in the off an induction motor by accounting for electromechanical effects.

In the 19th century, two scientists separately invented the AC induction motor. Today, itâ&#x20AC;&#x2122;s a common component in robotics. How did we get here and how can modern-day engineers continue to improve the design? The COMSOL MultiphysicsÂŽ software is used for simulating designs, devices, and processes in all fields of engineering, manufacturing, and scientific research. See how you can apply it to robotics design. comsol.blog/induction-motor

TheessenTials A YeAr of SimulAtion

Supercomputers

Supercomputing is strategic for research, innovation, and long-term competitiveness. It is a major area of the technology race engaging the two greatest economic powers. In 2018, the USA stepped up its counteroffensive to regain top place in the TOP500 ranking of the world’s most powerful supercomputers. Its Summit computer, built by IBM, was commissioned in June 2018 at the US Department of Energy’s Oak Ridge National Laboratory. According to the LINPACK benchmark, this computer then had 122.3 petaflops of computing power (1 petaflops equals 1 quadrillion floating point operations per second). This figure rose to 143.5 petaflops over the course of the year. Summit enabled the USA to oust China after two years of domination with its Sunway TaihuLight supercomputer, which has compu-

oAk rIdge nATIonAl lABorATory

the uSA hAS Widened the GAp With ChinA

ting power of 93 petaflops. This supercomputer has in fact dropped to third place since Sierra, IBM’s supercomputer in the US Department of Energy’s Lawrence Livermore National Laboratory, increased from 71.6 petaflops to 94.6 petaflops. The USA now monopolizes five places in the top 10 most powerful supercomputers. This compares to two for China, two for Europe (Piz Daint in Switzerland holds fifth place, with 21.2 petaflops of power; SuperMUC-NG in Germany comes ninth, with 19.5 petaflops), and one for Japan. Losing the top two places has not stopped China extending its overall domination, with

Summit, commissioned by the USA, is the most powerful supercomputer in the world.

227 of its supercomputers in the latest TOP500 compared to 206 in the June 2018 ranking. The USA has slipped to 109 supercomputers, its lowest ever figure, compared to 124 six months’ earlier. But thanks to some more powerful than average supercomputers, the USA wins in terms of installed computing power, owning 38% of the TOP500’s power compared to 31% for China. § ridha loukil

augmented reality

ToyoTA

toYotA fACtorieS Are teStinG hololenS heAdSetS

This technology is speeding up quality control and facilitating space layout.

l’usine nouvelle SPECIAL FEATURE MAGAZINE 2 § APRIL 25 2019

The Japanese manufacturer Toyota is taking a close interest in augmented reality. Since November 2018, it has been assessing the roll-out of Microsoft’s HoloLens headsets on its production lines in answer to various needs. They are initially being used to inspect car-body paint thickness, a laborious process in which cars are covered with sheets of paper, a job that can take two workers an entire day to complete. Thanks to augmented reality, one person can do it in just two hours. Another use is the possibility of placing full-scale virtual representations of machine tools into factories to check if they fit into their allocated space without encroaching on surrounding equipment and blocking access to it. Toyota is using the Dynamics 365 Layout software for this purpose. The other

software on Microsoft’s shelf, Dynamics 365 Remote Assist, is also being studied to help technicians share problems they encounter and hence resolve them faster. Implementing these digital tools is part of Toyota’s philosophy of continuous improvement (kaizen). But Toyota is not the first company to take an interest in HoloLens. Mercedes-Benz, Volvo Cars, Ford, and Renault Trucks have already presented use cases with HoloLens in the past, and most car manufacturers use immersive technology on a daily basis. § J. B. www.usinenouvelle.com

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TheessenTials A YeAr of SimulAtion

P. guITTeT

menting artificial intelligence in Europe is driven by the development of assisted driving in the car industry and by SMEs switching from traditional data analysis models to learning models. Europe has real know-how in these two areas. The issue here is knowing how to industrialize it, and which data and algorithms should be used.”

In the STMicroelectronics factory in Rousset (Bouches-de-Rhône).

artificial intelligence

EuropE’s Chip industry is at a turning point What can be done for Europe to excel in artificial intelligence? This was the topic of the round table bringing together, among other people, three champions of the European chip industry: Jean-Marc Chéry, CEO STMicroelectronics; Reinhard Ploss, CEO of Infineon Technologies; and Kurt Sievers, president of NXP Semiconductors. The round table took place on 13 November 2018 as part of the Electronica trade show in Munich, Germany. “The USA and China are leading the artificial intelligence race,” said Sievers. “Europe must adopt a strategy to make up for lost time. It could play the security and safety card to boost consumer confidence.” While the internet giants Amazon, Google, Microsoft and Facebook prefer centralized AI on cloud servers, European companies have focused their effort on edge computing, i.e. delocalizing

l’usine nouvelle SPECIAL FEATURE MAGAZINE 2 § APRIL 25 2019

intelligence to embedded systems in cars, robots, drones, and sensors.

Focus on EdgE computing

STMicroelectronics offers a software tool converting a cloud-trained AI model into a model executable in STM32 microcontrollers. This solution is available for Amazon Web Services, IBM, and Microsoft clouds. The offer should be beefed up in 2019 to include a computing acceleration circuit, followed by a solution integrating the microcontroller and accelerator. But switching to the cloud is out of the question, even though the group has developed a dedicated artificial intelligence processor based on its 28-nm FD-SOI technology for Alibaba. At least, not for the time being. NXP and Infineon Technologies have a similar strategy. Ploss underlined the challenges for industrial production and data: “Imple-

AccElErAtion

Data is considered a crucial issue. “Obtaining large amounts of high-quality data is a great challenge,” said Ploss. “In this area, China has a great advantage over the rest of the world. We must speed up in Europe to develop thousands of use cases. This will not be achieved with artificial intelligence alone, which isn’t the answer to everything. It must be combined with traditional analytical models,” he said. Customers want to speed up the implementation of AI. Things are not that simple for European semi-conductor manufacturers. “It’s a great challenge since it’s hard for us to work so quickly,” said Chéry. “We would have to invest hundreds of millions of dollars to do this. We prefer to proceed in stages. We now have a microcontroller solution meeting the needs of as many people as possible, which is enabling us to work faster. We will gradually add to it for applications requiring more performance.” § Ridha LoukiL www.usinenouvelle.com

TheessenTials A YeAr of SimulAtion

augmented Reality

microSoft hAS Signed A huge contrAct With the uS ArmY At the end of November 2018, Microsoft won a 480 million dollar contract to supply the US army with augmentedreality headsets. The agreement makes provision for 100,000 headsets to eventually be deployed to soldiers. This will “increase the armed forces’ lethality by enhancing their ability to detect, decide and engage before the enemy.” Magic Leap (a start-up), Booz Allen Hamilton, Lockheed Martin, and Raytheon also took part in the call for tenders. Microsoft will initially supply prototypes based on its HoloLens headset, which will be used to develop a device meeting the army’s specific needs. The final system, called Integrated Visual Augmentation System (IVAS), will need to be improved for use in the field. Enhancements will include night vision and thermal sensing, extreme temperature resistance, ability to measure soldiers’ vital signs, and built-in hearing protection. Although HoloLens quickly captured the market for augmented-reality headsets when it appeared in 2016, it has not been widely implemented. According

to Bloomberg, a video made for the European Patent Office in summer 2018 states that 50,000 devices have been sold. With this contract, the US army could become Microsoft’s biggest customer by far. The agreement makes provision for 2,500 headsets to be delivered within two years of signing. In addition, Microsoft must demonstrate its mass-production ability. While this is a great commercial victory for Microsoft, it remains to be seen how the company’s staff will react. Use of Microsoft’s technology by the US

Immigration and Customs Enforcement Agency (very controversial in the Trump era) caused an in-house outcry last June. In October, the JEDI military cloud contract (which Google was working on) caused a scandal. Brad Smith, CEO of Microsoft, replied that although the company would always pay attention to ethical use of its technology, it would not pull out of military contracts. He argued that technology companies would not improve things by refusing to take part in discussions. § J. B.

MIcRoSofT

Software

WhY optiS hAS Joined AnSYS In May 2018, the French company Optis, specializing in the simulation of light and human vision, became part of the leading US numericalsimulation company Ansys. Set up in 1989 and based in La Farlède (Var), almost 95% of Optis’s business is on the international market. The company serves 2,500 customers in various sectors (car industry, aeronautics, cosmetics...), including Audi, Ford, Toyota, Ferrari, Boeing, Airbus, GE, Swarovski, and L’Oréal. “When you’re an SME with 250 employees and constantly expanding on the international market, you’re ultimately confronted with ever bigger customer needs and challenges, even though your simulation capacity remains modest. By joining forces with Ansys, we’re entering the premier league,” Jacques Delacour, CEO of Optis, told L’Usine Nouvelle last spring. Ansys has 3,000 employees and its software covers several key sectors: structural mechanics, fluid dynamics, electronics, semi-

conductors, embedded systems, safety, and 3D design. Ansys is delighted with this acquisition since it will extend “its portfolio of multi-physics solutions to optical simulation, which is increasingly present in product development.” Although the initial discussions date back to early 2017, Optis and Ansys have already worked together, each on their own specific solutions, for their customers in common. “There are always interactions with thermal phenomena in optics, for example lenses and light beams are distorted by heat,” said Delacour. “Our technology is therefore highly complementary, as are our markets in terms of customer type and geographical coverage. We have everything to gain by combining our expertise,” he added. Now that it has become part of Ansys, Optis plans to speed up its developments, especially in the area of autonomous vehicles. § JEaN-ChRiSToPhE BaRLa

TheessenTials

Company Example

De Buyer, Simulation aS a Growth Driver

t the back of a workshop, a robotic arm behind a barrier guard stands opposite two machine tools. On the side, a sorting auto maton takes pastry rings to be machined out of a tub and presents them to the robot. One by one, the robot takes the rings with its gripper and passes them successively through both machine tools. Once the pastry rings have been machined, the robot retrieves them and puts them back into the sorting automaton. On the way, the robot readjusts the grasp of its gripper by striking the ring on a small flange. Fifteen years after purchasing its first robot, De Buyer, which specializes in cooking utensils, is innovating with this new robotic unit. The company bought the bare bones of an ABB robot but ev erything else, gripper, machine tools, and sorting device, was designed and manufactured inhouse, without involving an integrator. This performance is the result of a long development process. Although De Buyer traditionally targeted the consumer market, this family SME established in Vald’Ajol (Vosges) in 1830 had to refocus on the professional market after competition from Asia appeared at the end of the 1980s. This refocusing meant a move upmarket, with products sold as work tools. Innovating with materials and ergonomics was a major challenge, leading to an innovation culture and the use of 3D modeling software. Innovation is a daily occurrence in the workshops employing 120 of the company’s 180 staff. The mechanical engineering workshop contains the machining cen ters that De Buyer purchased from its former tool manufacturer when it went into liquidation; De Buyer also hired the employees who were working on its

This Vosges-based manufacturer of cooking utensils is constantly investing to modernize its production tools. duct prototypes every week,” said Mathieu, who always has a ball of plasticine handy on his desk since it is more effective than software for working on ergonomics. De Buyer also has a 3D printer, which works 24/7 to make maintenance parts and manufacturing accessories.

The FacTory’s DigiTal Twin

projects. Standing on a long workbench, a stamping machine used to make molds for cannelés, a small French pastry typical of the Bordeaux region, was designed using 3D software and manufactured in house. “Being able to design our own machines and tools helped us develop innovative processes and be more responsive, even though our 7,000 com ponents are all machined differently,” said Jean Noël Mathieu, deputy general manager of De Buyer. This autonomy is a lever for creativity and agility in the company, which designs both customized products and medium series. “We print new pro

l’usine nouvelle SPECIAL FEATURE MAGAZINE 2 § APRIL 25 2019

In 1999, De Buyer did not think twice before inves ting in the 3D CAO software SolidWorks and went on to buy a module to extract its 3D pictures and films. “Our objective was for customers to be able to visualize a product to ensure it matched their needs. Our culture of 3D representation and demonstration stems from there,” said Mathieu. When designing injection molds, De Buyer uses SolidWorks to simulate stresses and deformation in their materials and also simulate filling flow. It has also developed a digital twin of its factory, used to model buildings, workshops, machines, and even tools developed in house. Over the past few years, modernization and growth, the company’s turnover rose from 23 million euros in 2012 to 32 million in 2017, have complet

P. guiTTeT

TheessenTials

years, she trained herself to become independent in robot programming, for Kuka and ABB robots “only”. In 2018, she asked to take a virtualrobotics training course so that she could computer simulate her programs before installing them in real robots. Mathieu’s sights are also set on collaborative robots. As president of the culinary arts committee of the Technical Center for Mechanical Industry (Cetim) and a member of his regional innovation and technology commission, he regularly discusses industry of the future. Nevertheless, he remains cautious about some subjects, especially machine connectivity. “Although our machines are full of sensors, they’re not connected and data does not leave the works hops. We’re still concerned about cybersecurity.”

an erP accessible To subsiDiaries anD cusTomers

ely transformed the buildings. In 2013, a third of the factory was demolished so that 3,600 square meters of workshops and 1,500 square meters of offices and showroom could be built. In 2017, an additional 3,000 square meters were constructed. The digital twin was used to simulate the workshops and moves. “Before moving our production lines, we were able to test the new layouts and discuss where to put machines and pallets with our ope rators to suit how they move around,” explained Noémie Charpentier. This engineer joined De Buyer in 2009 as the maintenance manager. Over the

Nevertheless, De Buyer is preparing to open up to the outside world. With cooking recipes on Face book Live and a CRMsystem extension to opti mize customer relations, the company has several digital projects up its sleeve. “The factory has been constantly modernizing over the past ten years since we’re expecting digital technology to boost sales,” explained Sophie Hesse, marketing and communi cation director. For De Buyer, 2018 was supposed to be, and almost was, the year of ‘commercial digital revolution’. Tucked away behind Col du Peutet, the company had to wait a long time (until last August) for fiber broadband access. The arrival of broadband changed everything. The company’s subsidiaries are now connected with exactly the same response time as local connections. Optimizing the ERP, Sage X3, is now done remotely rather than onsite. This ERP “means our commercial subsidiaries abroad and our customers can see our product range, stock level, and production progress in realtime,” explained Mathieu. This will enable De Buyer to implement its productcustomization strategy and be more responsive.

When designing injection molds, De Buyer uses software to simulate stresses and deformation in their materials and also simulate filling flow.

Broadband has also boosted development of electronic data interchange (EDI) with customers. To reduce its carbon footprint, De Buyer prefers to hold international meetings via video teleconferencing systems. File transfer and updating can now also be done in digital media. However, for realtime logistics work in its factory, the company continues to use WiFi antennas on mobile terminals linked directly to the ERP. § Marion GarrEau www.usinenouvelle.com

SIMULATION On the COver

Living Organisms

l’usine nouvelle SPECIAL FEATURE MAGAZINE 2 § APRIL 25 2019

o .j

u CH

SIMULATION

Go Virtual

RAPID DEVELOPMENT In less than a decade, living organisms, from biomolecules to organisms, have become a fertile ground for simulation.

IN SILICO With molecule screening and virtual tests, pharmaceuticals and cosmetics laboratories are using industrial-scale simulation for their R&D.

AGRICULTURE Coupling traditional ‘plant models’ with big data-based approaches is luring us with the promise of automated farm management.

ALAIn CLAPLAUD, FLOrIAne LeCLerC, MAnUeL MOrAGUeS, MArIne PrOtAIS

C. joUAnneT ; P. CAre

SIMULATION

The University Hospital of Angers (Maine-et-Loire) was one of the first in France to set up a simulation centre.

Living WorLd

Simulation’S New HorizoN

Models of cells, plants and organs are increasingly used for medical and industrial applications. Living organisms are emerging as a key field for simulation. Marine Protais

l’usine nouvelle SPECIAL FEATURE MAGAZINE 2 § APRIL 25 2019

umerical simulation can be used to predict how much fruit will grow on trees, how tumors will develop, towns expand, and herds of mountain sheep move about. Have living organisms, molecules, cells, organs, plants, and behavior become something we can model like anything else? Various applications may lead us to think so. At Angers University Hospital (Maine-et-Loire), surgeons can manipulate digital anatomy tables and train for cataract operations on computers. The hospital was one of the first to set up a simulation center in 2013, around forty hospitals have now followed suit. “Over the past few years, the pace at which digital models are being created for medicine has really increased. We sometimes find it hard to keep up,” said Professor Jean-Claude Granry, head of the simulation center at Angers University Hospital. TexiSense is a start-up in Torcy (Seine-et-Marne) with expertise for modeling patient-specific buttock tissue. Data in very high pressure areas is collected using a smart cushion and fed into a personalized model, which can predict the risk of

SIMULATION bedsores. In a completely different field, beet growers are using Previbet, a tool that simulates their crops’ daily growth on the basis of meteorological data. Simulating living organisms for research purposes is nothing new. “Truly integrative models appeared in plant biology in the 1970s and in biomedicine in the 1980s,” said Franck Varenne, associate professor of the philosophy of science at the University of Rouen (Seine-Maritime) and a modeling historian. Over the past ten years or so, their use has really taken off, “thanks mainly to big data,” observed Varenne. As well as the amount of data available, multi-scale and multiprocess simulation methods are making models more reliable [see interview, p. 22].

a complex and imperfect modeling

This progress is giving rise to new non-laboratory applications. Just like mechanical engineering and electronics, living organisms have become a market for software vendors. In 2012, Dassault Systèmes set up a life-sciences branch. Although unwilling to state the turnover generated by this activity, Jean Colombel, vice-president of life sciences, says he works with “thousands of clients, including the top 20 medicaldevice companies.” The US firm Ansys also has this type of business, which only accounts for 5% of turnover but is “one of the group’s strongest” growth areas, said Thierry Marchal, global industry director for healthcare at Ansys. While the medical field drives a significant part of this market, other sectors are interested. For example, the agri-food industry, which uses plant and ecosystem models for yield planning [see investigation, p. 28]. Manufacturers less directly linked to the life sciences are also taking an interest. “Consumer goods, sport, and construction companies increasingly incorporate simulation of living organisms into their product-design work,” said Marchal. Unilever used a digital model of a hand to develop its ketchup bottles. This was to check that young children and elderly people would be able to squeeze hard enough for the ketchup to come out. Although applications exist, many challenges still need to be overcome before we obtain perfect digital models of living organisms. “It’s currently impossible to simulate an entire plant, i.e. to use a simulation model that takes into account all phenomena relating to its growth and function. And yet plants are the least complex living organisms to model since, unlike in animals, plants’ living cells remain virtually immobile within them once they are formed,” said Varenne.

“Consumer goods, sport, and construction companies increasingly incorporate simulation of living organisms into design work.”

In-sIlIco tests are stIll too expensIve to replace anImal testIng one of the goals of simulating living organisms is to put to an end to the use of animals in laboratory testing. This is a welcome undertaking at a time when regulations and public opinion are hardening against these experiments. In 2013, the eU banned the sale of animal-tested cosmetics. In-silico tests (using numerical simulation) are an alternative. The healthcare industry also uses in-silico tests to supplement animal tests, which are still authorized in this sector. “Digital models of human organs come closer to human beings than a rat,” said Thierry Marchal, global industry director for healthcare at Ansys and the secretary general of Avicenna Alliance, a lobby for in-silico

medicine. Animal rights associations also encourage these methods, but scientists and manufacturers remain hesitant. In january, a panel of researchers, manufacturers, and representatives of associations met at the French national Assembly to discuss this issue. Scientists and representatives of industry agreed that, for the time being, alternative methods (including in-silico tests) are not effective enough to completely replace animal testing. Their high cost, linked to the computing power required, remains prohibitive.

The great diversity, many scales, and various principles governing living organisms mean they are very complex to model. Another difficulty is the definition of living organisms, which can vary from one school of scientific thought to another. “Simulation is reviving epistemological disputes, especially between physicalists, who rely on physical principles only, and neovitalists, who believe that other principles are necessary,” said Varenne. These issues strike us less forcefully when we are simulating turbines. Nevertheless, even imperfect digital models of living organisms are proving useful. Although virtual humans used in the car industry for crash simulations are incomplete, how the body is distorted has been modeled well enough to improve vehicle safety. The Human Brain Project, a European brain modeling project due to be completed in 2022, will certainly not enable every subtlety of brain functioning to be understood. Nevertheless, it will be a way to test how various drugs affect neurons.

Thierry Marchal, global industry director for healthcare at Ansys

SIMULATION IntervIew

“It has become a massIve movement” Hugues Berry

INRIA’s deputy scientific director, in charge of digital health, biology, and earth research, believes that we will have access to many very reliable models of organs in 20–30 years’ time. IntervIewed by Manuel Moragues and MarIne ProtaIs Photos Pascal guIttet

Interest in simulating living organisms has grown in recent years. Why is this? The growing use of simulation is related to our desire to make living organisms a quantitative science so that we can make predictions. Fifteen or so years ago, only a few researchers, mainly from mathematics and physics, were interested in simulating living organisms. Now biologists and clinicians share this interest and it has become a massive movement. Under the leadership of its then CEO Gilles Kahn, INRIA began focusing on living organisms in the mid-2000s. Today, around 20% of our teams, i.e. 250 people are working on living organisms. We have programs at every level: molecules, cells, organs, and cell/micro-organism ecosystems. What is the main challenge of living organisms? Their extremely multi-scale, multi-physics nature. Take the heart: it is distorted, pumps 22

blood, sends and receives electrical signals, etc. You have to combine various physical phenomena to simulate it, drawing on biomechanics, biophysics, fluid physics, etc. Simulating living organisms also involves working on very different scales, from biomolecules to cells and organs. This is very complex since living organisms are highly disorganized, heterogeneous, and move around. Time scales also vary from nanoseconds for molecules, years for organs, and microseconds for cells. Although we’re starting to have methods that take into account these various sizes and time scales, it’s not enough.

l’usine nouvelle SPECIAL FEATURE MAGAZINE 2 § APRIL 25 2019

What major progress has been made? Non-linear mixed-effects models are a major advance and are enabling us to take account of individual variability in populations. Until now, we’ve regarded every bacterium in a population of bacteria as having the same characteristics. When we were interested in treating cancer, we used to think that each patient would react in the same way. Now we’re managing to treat patients and bacteria as individuals. As a result, we can simulate different responses to treatment and better understand the dividing line between normal and disease-caused conditions.

SIMULATION

several decades to do so. Digital twins will enable doctors to prescribe the most appropriate treatment and dosage.

“Simulating living organisms involves working on very different scales, from biomolecules to cells and organs. This is very complex since living organisms are highly disorganized, heterogeneous, and move around.”

What about big data’s contribution? Another advance is more frequent access to quantified data, obtained by new scientific methods. Cell-level research has been revolutionized by fluorescent molecules, which are used to quantify how many molecules such as proteins are in cells. Improved techniques for analyzing medical images are also enabling us to automatically measure tumor size, for example. For the past three years or so, access to quantified data has resulted in the development of big data applied to living organisms. This is making digital models more accurate and is opening the way to simulating patient-specific organs. At INRIA, we have teams working on the heart and the liver. We’ll therefore have access to many very reliable models of organs in about 20– 30 years’ time. How do you create reliable, personalized digital twins of organs? The principle behind this work involves taking a generic model and personalizing it

with patient-specific data such as X-ray images. The challenge is to do this reliably and automatically. Meteorology has given us a way to do this: meteorologists use equations to work out an expected weather forecast. They then compare it with data collected locally and correct their model. This technique, called data assimilation, has been developed since the 1970s. In 2006, INRIA’s researchers applied this technique to heart simulation in order to predict heartbeat. They adapted their heart model to a specific patient’s medical images to simulate his heart’s electrical activity. This could be useful when fitting pacemakers since it tells surgeons where to position them to achieve the best possible heart synchronization.

The Human Brain Project, an iconic brainsimulation project, has been criticized. What are the reasons for this? Some people think that a multi-scale model extending from molecules to organs, such as the one put forward by the Human Brain Project, will not help us understand brain function and that more advanced theories are needed for this. In the same way, understanding how a metal bar bends is not achieved by starting from atoms but by the concepts of torsion, force, and vectors. Nevertheless, brain modeling could be very useful for insilico drug tests. Rather than testing a whole range of potential molecules on mice, we’ll test them on computers to choose the most effective molecules. In-silico tests are going to become essential to comply with ever tougher EU animal-testing regulations. The pharmaceutical industry is already using digital technology to predict the effects of drugs. Machine learning-based approaches involving AI algorithms, which use databases to establish a drug’s likely effects, are often employed. There’s no simulation and nothing is explained. Although you know that the molecule will have such and such effect, the algorithm doesn’t tell you why. The advantage of simulation is that you can deconstruct a digital model to understand why an effect has occurred.

What about digital twins of patients? So far, no one has managed it. Making a patient’s digital avatar would mean combining all organ simulations and modeling a system to control the whole thing. We still haven’t reached this stage and it will take 23

SIMULATION Pharmaceuticals-cosmetics

Simulation at EvEry LEvEL Digital models are spreading throughout every level of research in laboratories, which need to invest in facilities and review their work methods. Floriane leclerc

n-silico research is gaining more and more ground. Pharmaceuticals and cosmetics laboratories have embraced numerical simulation after being won over by its performance. “Methods are constantly developing and improving in this field. They’re now enjoying a phenomenal boom,” said Antoine Bril, scientific director at research and partnerships in the Servier Group. This technology was previously confined to a few steps of R&D but is now used during the entire process: “Upstream, for virtual screening of new molecules; in the clinical phase, to assess molecules’ toxicity before they are synthesized; and during the pharma-

“It’s becoming possible to test many molecules” RobeRto SantopRete,

program manager and research associate at L’Oréal Research & Innovation Increasingly, you are using numerical simulation for skin. What applications does it have? As a tool helping chemists design small molecules, simulation is now also used by physicists for upstream design work on polymer-based systems. In addition, mechanical and optical simulation is being used to predict the post-treatment visual appearance 24

of wrinkled skin. Further downstream, simulation is used to increase the capacity of measuring instruments. It is also used by mathematicians and biologists to discover new biological targets, and by pharmacologists to predict drug safety.

Union’s Cosmetics Directive. Simulation can therefore be used at every stage of our products’ safety assessment: from the initial virtual-design phase to drawing up regulatory dossiers, where it supplements evidence from in-vitro tests.

How is simulation meeting safety and regulatory requirements? In-silico simulation methods are one of the suggested alternatives in response to the ban on animal testing for cosmetics introduced by the seventh amendment to the European

How are you benefiting from in-silico methods? Simulation is enabling us to screen many potential candidate molecules; we would never have been able to test all of them with experiments. A few years ago, we had suppliers offering

l’usine nouvelle SPECIAL FEATURE MAGAZINE 2 § APRIL 25 2019

us over 500,000 molecules. Our molecular-modeling tools enabled us to reduce the number of molecules bought and tested to 200. We detected 7 active molecules and patented their chemical families for the activity we were targeting. Simulation is also enabling us to design new systems, optimizing their properties virtually before synthesizing them.

D.R. ; blOOmbERg vIA gEty ImAgES ; J.-P. KSIAzEK / AFP

SIMULATION

the world leader in cosmetics uses in vitro culture of skin cells to avoid overly invasive skin tests.

l’Oréal uses simulation very early on to study hair movement and conduct tests in a safe manner.

cokinetic modeling –studying what happens to a substance in the human body– and pharmacodynamic modeling – studying a substance’s activity in the body– phases to establish the best dosage,” said Bril. Using a corpus of 9,000 studies, the European eTOX project, which should improve drug safety assessment, has helped implement more than 130 in-silico models. These models are now used to predict molecules’ toxicity before they are synthesized. This is resulting in real economic benefits, although they are still hard to quantify. “At this stage, simulation is enabling us to test many combinations and hypotheses, and then adapt our research. This means we target and manufacture only molecules that are very likely to succeed,” explained Bril.

extending the realm of possibilities

Cosmetics laboratories are saying the same thing. “Simulation is used far upstream in our design process. As a result, we reach the clinical testing stage with candidate molecules that are more likely to be effective. Simulation has also extended the realm of possibilities. For example, we can study the dynamic visual performance – movement – rather than

just static –color and shine– of hair after the application our products,” said Anthony Galliano, international manager for product performance assessment at L’Oréal R&I, who is researching various haircare product formulas. “Thanks to simulation, we can model the movement of single hair strands. We can also manage how these hair strands interact, integrating into our models how they rub and adhere, etc. to obtain the desired hair movement,” he continued. Another benefit is that: “Although simulation is not replacing experimental tests, which is still used to confirm the results, it does nevertheless enable us to carry out our initial tests safely. This is because any sensitization, irritation and mutagenic problems caused by our potential candidate molecules are detected very early,” said Galliano. While hair is becoming accustomed to simulation, skin has not been forgotten at L’Oréal, which uses digital technology to formulate skin treatments and study their effects on skin ageing. “Unlike haircare product tests, which can be done on cut hair, skin tests can be more invasive. In the initial stages, numerical simulation is therefore an excellent replacement for biological tests,” concluded Galliano. The ‘laboratory tool’ developed by L’Oréal has become essential in French research departments and is due to be industrialized worldwide. It has already been rolled out in the USA and will be shortly in Brazil. “Each of L’Oréal’s hub’s – India, China, Japan, South Africa, etc. – will have the same tool. This is to ensure a standard model that can assess and obtain effects tailored to each market’s specific needs,” explained Galliano. To carry through this industrial development, laboratories have invested in new computer facilities and techniques to acquire the necessary computing power. The Roche Group has its own computer farms and does not think twice about renting computing time to various players such as the French Alternative Energies and Atomic Energy Commission (CEA) to model its clinical trials. This stage involves analyzing 25

SIMULATION La base de données de l’industrie et de ses décideurs

D.R.

Nouvelle version en ligne 7 JOURS DE TEST GRATUIT

“The challenge is to access reliable data sets, which are scattered in many silos. But we must remain humble in the face of living organisms’ complexity.” patrice Denèfle, head of the Roche Institute for Research and translational medicine

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thousands of pieces of data for several days. Things are the same for the Servier Group, which currently has an in-house computing capacity of 400 teraflops and is using supercomputers on the Paris-Saclay cluster to increase its strike force. By 2021, the group will be present on the cluster, “to draw closer to this ecosystem conducive to developing numerical simulation,” said Bril. Anticipating a significant long-term increase in its digital technology needs, the Servier Group is currently assessing what quantum computing can provide. “Although the technology is still in its beginnings, a small team of experts is studying this topic. We don’t need it for the time being, but our computing needs are expected to increase.” continued Bril. This will be especially true if the digital twin projects materialize.

Working on a network

These virtual representations of generic, or even specific, organs and patients could one day enable scientists to predict the effects of drugs. This will enable each patient to be administered the right drug, at the right dose, and at the right time. “We should then be able to calculate a drug’s effects at various levels, from molecular scale to each patient’s entire body,” explained Bril. “Computing power can’t do everything,” said Patrice Denèfle, head of the Roche Institute for Research and Translational Medicine. The big groups have had to change their work habits and teams to use simulation. “Twenty years ago, we were working with bioinformaticians. Now we’re looking for profiles more trained in pure mathematics and engineering,” added Denèfle. The very closed world of laboratories has also opened up to new players: IT companies such as Microsoft, which provide computing and storage capacity for researchers; software vendors such as Dassault Systèmes; and start-ups able to make specific algorithms. “Above all, we’ve had to learn about inter-laboratory collaboration and working in a network,” said Bril. The Innovative Medicines Initiative, a major European project launched by the European Commission and the European Federation of Pharmaceutical Industries and Associations (EFPIA) in 2008, was already promo-

SIMULATION

ting pre-competitive research consortia made up of public and private partners. The use of numerical simulation has reinforced this trend. “The real challenge today is to access reliable, complex data sets, which are currently scattered in many silos,” said Denèfle. “To obtain bigger, more varied and better consolidated databases enabling us to make better predictions, we’ve had to work more openly and pool our data,” explained Bril. Major projects such as Electronic Health Data in a European Network (EHDEN) are bringing together industrialists, university laboratories, hospitals, SMEs, and patient organizations in research based on using common data models to create highquality data networks. “But we must remain humble in the face of living organisms’ complexity. Even by working together, a lot of research will be required to collect and link up new data sets –especially on the development and dynamics of various diseases such as cancer, Alzheimer’s and autism – before we can model and simulate behavior that will help better care for and perhaps cure patients,” said Denèfle.

Iktos’s algorItHm Is boostIng servIer’s researcH laboratories no longer think twice about approaching companies able to supply them with the latest technology. Sevier is therefore collaborating with Iktos, a start-up specializing in artificial intelligence (AI) applied to chemistry. based on deep learning models, Iktos’s algorithm uses data already generated by research projects to design and optimize molecules in silico, addressing every parameter in the project specifications. this technology answers one of the big problems encountered in upstream pharmaceutical R&D: the search for a molecule that simultaneously meets all

the in-vitro criteria required for a preclinical candidate (pharmacological activity, selectivity, non-toxicity, etc.). When applied to analyzing a data set of over 800 molecules tested on 11 criteria, Iktos’s algorithm suggested 150 molecules virtually optimized for each objective. Servier successfully synthesized and tested 11 of these molecules, which met, on average, 9 of the 11 objectives. One molecule matched every point in the project specifications.

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SIMULATION

AgriCulture

Algorithms for farms

The future of agriculture will involve big data and plant simulation. Researchers and start-up founders are combining these two approaches to help farmers’ daily life. AlAin ClApAud

may have heard of ‘plant models’, which use equations describing plant growth and the processes by which fruit appears. Agronomy researchers have been making these models since the 1990s, maize, wheat, sugar cane, and tomatoes all have one. These mechanistic models have resulted in software to simulate plant growth and estimate harvests according to how much sunshine and water a given land parcel receives. This provides farmers with a real decisionmaking tool for choosing which seeds to sow and tree species to plant. But things are now progressing further, even to the point of running farms on a day-to-day basis, from seeds to phytosanitary treatments and watering.

More and more wireless sensors

According to Éric Brajeul, director of the operations center at the Interprofessional Technical Center for Fruit and Vegetables (CTIFL), this leap forward is possible “thanks to available computing power and significant progress on algorithms, which are enabling simulation at speeds and iterations unimaginable just a few years ago.” ‘Standard’ numerical simulation is now boosted by big data algorithms. Cheap wireless sensors can be deployed on a large scale in fields and greenhouses to feed data into algorithms. By coupling this environmental data with plant models, predictive computing promises to anticipate changes in ecosystems and, for example, adjust watering, input doses, lighting, and CO2 levels in greenhouses to maximize production. The promises of simulation and big data are winning over agriculture, which is turning increasingly to digital technology. While the sector is developing via incremental innova28

l’usine nouvelle SPECIAL FEATURE MAGAZINE 2 § APRIL 25 2019

Data from sensors (here a dendrometer, measures the diameter of a stem) feed predictive calculation algorithms to anticipate crop development.

tion, digital technology is the only real leap forward in technology expected over the coming years. This is the conclusion reached by the French Academies of Technology and of Agriculture in a report entitled Addressing Agriculture’s Technical Challenges. “Digital technology in its various forms is going to have an impact on all agricultural operations. In particular, simulation will speed up research on new molecules and on improving plant varieties,” said Bernard Le Buanec, a member of the Academy of Agriculture.

d.R. ; F. Bessac / PuRPan

SIMULATION HigH-Performance comPuting for Better Pesticide control

Numerical simulation is helping assess how pesticide molecules spread through the soil, carried down to the groundwater by water molecules.

The report mentions the importance of digital technology for developing precision agriculture and agricultural robotics. “Digital technology is used to make new phytosanitary products, as well as by cereal producers to develop new seeds and by farmers themselves. Processing big data from drones and satellites is helping recognize diseases affecting land parcels and identify areas that need weeding.” Less phytosanitary inputs and optimized watering in water-deficit areas are all valuable economic and ecological assets for the future of French agriculture. This thorough work by the two academies stresses that mechanistic model-based simulation and big data’s approach complement one another. “Big data is supplementing

The purpose of the project run by Fabienne Bessac, assistant professor in the Quantum Chemistry and Physics Laboratory at the University of Toulouse III-Paul Sabatier and at Toulouse INP-EI Purpan, is to assess how pesticides spread through soil. “We’re working at molecular level, reproducing blocks of 600 atoms in all spatial directions to simulate solids, in this case clay. This approach is enabling us to assess how a pesticide interacts with clay. From these molecular calculations, we hope to extrapolate the results to macroscopic scale to assess how much pesticide a ‘real’ soil will retain. The model will be adjusted by correlating these results with field experiments. The project involves

calculating every interaction between atomic nuclei, between nuclei and electrons, and between electrons, which represents a huge volume of calculation. We’re using supercomputers in several of France’s regional and national centers, which amounted to more than 2 million computing hours last year. Our simulation methods are accurate but very expensive. We aim to develop cheaper methods in terms of computing time and disk space before broadening our research to other pesticides. In the future, we intend to assess new pesticides whose effects are not yet known,” he explained.

rather than replacing simulation. Living organisms use complex systems, and by coupling both approaches we can make significant progress,”said Christian Saguez, a member of the Academy of Technology, former president of Teratec, and founder of the start-up CybeleTech, a spin-off from the École Centrale de Paris. According to Denis Wouters, CybeleTech’s CTO and an expert in combining data technology and simulation: “Our approach regards plant-model data as 29

SIMULATION

an input stream to supplement sensor data. In my opinion, plant models are essential since it’s hard to model a living system reacting to multiple factors using a big databased approach only. You’d have to process huge amounts of data to be representative of all pedological and climatic conditions.” The Magestan project, on models for running greenhouses, stems directly from this approach and has received 1.3 million euros of funding under the ‘Investment for the Future’ plan. Run by CybeleTech in partnership with Wi6labs, the French National Institute for Agricultural Research (INRA), and the CTIFL, the project will enter its pilot phase this year. “The idea is to improve management of greenhouse crops, tomatoes in this case, by using numerical-simulation models and wireless sensors placed in greenhouses,” said Brajeul.

Optimizing greenhouse crops

Although in the past, greenhouses were closed and production focused on quantity, priorities have changed in recent years. Farmers want to increase both the yield and quality of fruit and vegetables, while also reducing inputs. Greenhouses are becoming increasingly complex systems with many actuators. “Improving how modern greenhouses function involves neural networkbased climate modeling to control greenhouse temperature, watering, and CO2 levels on the basis of sensor data. Simultaneously, optimum set-points for these parameters must be determined over time, which is where plant models are used.” The CTIFL is working with CybeleTech, which uses plant simulation models. These hitherto theoretical models can now be used operationally. “Various models are interacting under the term ’plant model’. By testing various scenarios, they’re enabling us to determine optimum set-points, which we will strive to achieve optimally by acting on greenhouse actuators.” Just like the Netherlands, France’s great competitor on the international market, and its recent autonomous greenhouse challenge [see box], many other countries are trying out this approach coupling simulation and big data to manage greenhouse crops. Saguez believes that progress is needed for this research to spread throughout the agricultural sector. First, he explained, “it’s still difficult 30

D.R.

ai, King of cucumBers

An unprecedented competition was held in the Netherlands last December. Funded by the Chinese internet giant Tencent, the autonomous greenhouse challenge pitted five teams of Chinese, Mexican, and Dutch researchers against one another. Their challenge was to design the most efficient management algorithms to run a greenhouse, the aim being to produce

cucumbers as economically and sustainably as possible. The greenhouse, fitted with many sensors and actuators, was completely controlled by machinelearning algorithms, which agronomists, developers, and data scientists optimized for more than six months. Team Sonoma, comprising researchers from Microsoft Research and the Universities of Wageningen

to completely control areas in which big data models are valid because their robustness depends directly on the data fed into them. In addition, one of the big challenges is to adapt optimization methods by coupling big data models and mechanistic models,” he said. Everything can progress very quickly, with models made available to farmers as cloud services. “Contrary to generally accepted ideas, I’ve noticed that the agricultural sector is far more receptive to these simulation methods than some manufacturers. This is especially true of young farmers, who really love new technology,” said Saguez.

l’usine nouvelle SPECIAL FEATURE MAGAZINE 2 § APRIL 25 2019

(the Netherlands) and Copenhagen (Denmark), won the competition. The team’s results were even better than those from the greenhouse run by a farmer. Although this challenge is still only a scientific experiment, it foreshadows what agriculture of the near future will look like.

Publi communiqué

PERVASIVE SIMULATION:

the new imperative For nearly half a century, ANSYS has been instrumental in helping customers drive innovation with engineering simulation, while also reducing costs and product development time. From cars, planes and trains to consumer electronics, industrial machinery and healthcare solutions, ANSYS software has helped create products that have transformed their respective industries. Probably the most important change today is a more pervasive, consistent use of simulation at all stages of a product’s lifecycle. Once a specialized activity wedged between initial design and physical testing, today simulation is recognized for the significant strategic value and financial returns it can deliver from the earliest design phases through the product’s working life in the field. In a world where millions of rows of data are updated, calculated and charted in real time in Excel, and where

Google gives us immediate access to billions of websites, it is almost incomprehensible that simulation is not equally accessible to every engineer. At ANSYS, we are making breakthroughs with a wide range of solutions to make this a reality. In a few years, it will be unimaginable to innovate without native and pervasive use of simulation by every engineer. Simulation is also increasingly applied to the manufacturing phase, where it significantly improves the efficiency, cost effectiveness and flexibility of production. For example simulation is key to unlocking the potential of 3D printing and Additive Manufacturing on a large scale. And as Industry 4.0 matures, Digital Twins (virtual replica of a product) will also become increasingly commonplace, running on demand either in the cloud or on the asset itself, to be able to predict critical failure or maintenance requirements.

Autonomous Vehicule

Optical Simulation

Embedded Software

If you want to know more about ANSYS solutions, please go to www.ansys.com 31 or contact us for more information contact-france@ansys.com

SIMULATION

CoMputIng

Quantum technology in industry

Progress in quantum computing over the past few years is encouraging industrialists to assess the potential offered by qubits. Manuel Moragues

Rather like a Jack that has popped up out of its box, quantum computers have come out of laboratories and started to conquer industry. After pioneers such as Airbus and Volkswagen tried out Canada’s D-Wave supercomputer, a second wave of industrialists is now interested in quantum computing. Evidence of this is the success of Atos’s simulator, which has been on the market for the past eighteen months. “Alongside universities, which were our main target, other types of client have appeared: research centers and industrialists such as Bayer and Total have bought our computers. And that’s not all. We have many contacts with manufacturers,” said a delighted Philippe Duluc, CTO for big data and cybersecurity at Atos. In France, Teratec, an association for high-performance numerical simulation, is setting up a quantum-computing working group with half a dozen leading industrialists.

Welcome to the nIsQ era

If quantum computing is generating such enthusiasm, it is because its exotic qubits [see opposite page] are promising the earth for sorting and searching data. They could even help manage deep learning algorithms, as well as with optimization issues, molecule simulation and calculations such as prime number factorization, which is central to crypto32

l’usine nouvelle SPECIAL FEATURE MAGAZINE 2 § APRIL 25 2019

The University of Innsbruck in Switzerland is carrying out research on trapped ions, which are a promising candidate for creating qubits.

graphy. Just when digital technology, simulation in particular, is taking every area of economic activity by storm, quantum computers are emerging as a strategic tool, especially since traditional computing power is tailing off. “We’re interested in quantum computing in terms of developing high-performance computing. Although Moore’s law [ed. note: an empirical law which states that processing power

SIMULATION ToTal a Specially DeDicaTeD Team Total has no shortage of applications for quantum technology: to invent new electric batteries and materials, to optimize how refining facilities are managed, etc. Total’s R&D department has decided to launch a dedicated research program. “This year, we’re setting up a full-blown project team. We’re in the process of hiring a project leader and, with PhD students and postdoctoral researchers, we’ll have about half a dozen people in the team,” said Henri Calandra, an expert in numerical methods and highperformance computing who is the project’s scientific advisor. Calandra has been working on this topic with a colleague for just over a year. Faced with accelerating progress, the challenge was to decide on a time-scale and the types of problems that could be addressed. “We have two topics that we think we’ll be able to tackle within 3–5 years using currently emerging NISQ technology. The first topic is quantum chemistry, i.e. calculating molecular energy

levels and interactions, which has applications for refining and battery chemistry.” The second topic is optimization issues and coupling with machine learning, whose applications include managing power distribution networks. “We want to work on industrial applications within these medium-term topics, using simplified problems to test how to use quantum algorithms and what they can provide. at the same time, the team will be examining longer-term topics: how to use a genuinely quantum computer, in all its complexity, for simulation and modeling, especially in seismic work.” Finally, we will be conducting crossdisciplinary research on algorithmics and hardware. “We’re aiming to become involved in co-design work with computer manufacturers.”

R. BlaTT

eDF in The ReFining phaSe

doubles every eighteen months] is coming to an end, computing requirements are growing constantly,” explained Stéphane Tanguy of EDF [see opposite]. Faster technological progress over the past three years, led by digital giants such as Google, IBM and Intel, start-ups such as Rigetti and institutions such as the University of Innsbruck, has stepped up the pace. But despite the race for numbers of qubits – synonymous with computing power – that has received wide media coverage, universal quantum computers remain a distant goal that will probably take at least a decade to achieve. Among other things, this is due to the difficulty

“although universal quantum computers are not going to happen any time soon, we’re very interested in exploring quantum programming, which is a real breakthrough. We want to train up our researchers in the topic and assess this technology’s potential,”said Stéphane Tanguy, head of digital technology research at EDF R&D and the entity’s CIO. He has been running a dedicated project, “admittedly modest but nevertheless very real” since the end of 2018. after spending about two years examining and assessing the current state of the discipline and its stakeholders, “around ten researchers, not necessarily full-time, are now refining questions in algorithmics and drawing up PhD topics. Experiments on quantum computers will come next,” he explained.Optimization issues are the first topics that will be addressed.

EDF is involved in the European PaSQuanS project, which is aiming to develop an adiabatic quantum computer. This technology is suitable for optimization: “We plan to assess what this could provide for energy management and production since the emergence of decentralized electricity systems is challenging existing simulation models.”Using quantum technology for deep-learning algorithms (clustering) is also on the agenda, as is cryptography, “if only to provide EDF with the understanding it needs to assess vulnerabilities and identify post-quantum encryption, which would be resistant to quantum computers,» said Tanguy.

SIMULATION in correcting qubit errors caused by perturbations, i.e. noise linked to decoherence phenomena [see next page]. But, regardless of this, we have now entered the NISQ era, as the American physicist John Preskill said in a keynote speech given in December 2017 that attracted a lot of attention. NISQ (noisy intermediate-scale quantum) refers to technology that will be available over the coming years: 50-100 qubit computers without reliable error correction. While these computers will certainly not revolutionize the world, they will nevertheless be able to perform certain tasks beyond the capacity of traditional computers. Atos believes in this technology. “In July 2018, we announced our intention to bring out an NISQ quantum accelerator by 2023,” said Duluc. “We’re completely committed to this approach and are backing noisy technology for molecule simulation and optimization issues,” said Henri Calandra of Total [see box on previous page].

Quantum Mechanics

QubiTS

In traditional computing, the smallest data unit is a bit. Its value is either 0 or 1 and it is materialized by either a switching or a blocking transistor. In quantum computers, we speak of qubits (quantum bits). a qubit corresponds to an object, such as a trapped ion or superconducting junction that obeys quantum physics and has two characteristic states, which we can label 0 and 1.

The following explanations will make sense of the key central ideas in quantum computing power: qubits, coherence, entanglement, etc.

SupeRpoSiTion

a quibit’s quantum behavior means that instead of being in either state 0 or state 1 it is a superposition – blend – of states 0 and 1. When a logical operation is performed on a qubit, it is therefore performed simultaneously on state 0 and state 1. With a traditional bit, it would have to be performed successively on state 0 and state 1 to process both potential values.

enTanglemenT

This power still needs to be utilized. Reading a quibit destroys its quantum superposition by plunging it into a single state (0 or 1), which means losing all quantum efficiency. algorithms must therefore use tricks to benefit from parallelism and extract results. In particular, they use entanglement: a system of interacting qubits forms an ensemble, which is in a state of superposition of the various combinations of qubits’ individual states. Consequently, touching one qubit instantly changes the others. This projects qubits into states corresponding to the result of one calculation by changing others.

DecoheRence

JUlIaN KElly / GOOGlE

poweR

The advantage of simultaneous processing increases as the amount of data becomes bigger: a 10-quibit system is in a superposition state of 210 = 1,024 potential values in a traditional 10-bit system. Processing 10 qubits amounts to processing 1,024 values at once. With 30 qubits, over 1 billion operations are processed simultaneously. “It’s this massive parallelism that is at the heart of a quantum computer’s power,” said Eleni Diamanti, a researcher in the CNRS computer science laboratory at Paris 6 University.

NISQ computers are fast approaching and their future users are starting to learn about quantum programming. “This represents a real paradigm shift and training will be essential,” said Tanguy. The effort will be all the more worthwhile since an explosion of algorithmics research lies behind the latest advances in hardware. Ideas are flowing and significant progress is being made. Standard, hybrid and quantum algorithms are all drawing inspiration from quantum technology, which is unlikely to get back in its box.

l’usine nouvelle SPECIAL FEATURE MAGAZINE 2 § APRIL 25 2019

This is the absolute enemy! Decoherence means the loss of quantum superposition and hence of computing power. Usually linked to environmental perturbations, decoherence threatens qubits and their entanglement. It is expressed by errors, which must be corrected using entanglement and redundancy. Depending on the type of qubit, up to 10,000 physical qubits can be required to create 1 reliable logical qubit.

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SIMULATION research

French AI gets A boost From HPC The installation in Saclay of the nation’s most powerful supercomputer, dedicated in part to AI research, should enable France to keep up with the GAFA companies. Manuel Moragues

n early January, GENCI (the organization pooling computing facilities for French scientific research) purchased a 25 million euro supercomputer. Commonly known as HPC-IA, it will be installed this spring at the CNRS IDRIS computing center in Saclay (Essonne). With 14 petaflops of computing power (i.e. 14 quadrillion floating point operations per second), it will double the computing power available in France. Although the HPC-IA will also be used for standard simulation, its architecture – the computer features 1,000 GPUs, the graphics processing units, so popular with deep learning, [see box, p. 38] – and its availability to researchers for on-the-fly computing, make it France’s top super-

computer for AI. “We absolutely had to have a supercomputer worthy of the name or else only the tech giants would have had the capacity for AI,” said Bruno Sportisse, CEO of INRIA [see opposite]. Deep learning and its huge neural networks need ever more computing power, which is where the GAFA companies are overwhelmingly dominant. “We’re not in the same league,” summed up Marc Schoenauer, an AI researcher and head of INRIA’s TAO project (optimization, machine learning, and statistical methods). “There are two types of presentation at scientific conferences: those given by the GAFAs, which present results obtained by running thousands of GPUs for several months, and those given

“this is a long-term digital arms race” Bruno SportiSSe,

CEO of INRIA

How is computing capacity important for AI? A significant part of AI is using bigger and bigger neural networks, with sometimes billions of parameters to be calculated. These huge algorithms cannot run without massive computing capacity. Installing this supercomputer at GENCI shows that digital technology too recognizes its need for large 36

technological infrastructures. It’s more virtual but just as important as a large telescope. Is the supercomputer that will be installed this year enough? It’s a start. Thanks to a 3 million euro donation from Facebook, it will be expanded. In four years’ time, an exascale computer [ed. note: able to perform 1 quintillion floating point operations per second] will be built under the European EuroHPC program

l’usine nouvelle SPECIAL FEATURE MAGAZINE 2 § APRIL 25 2019

and will be partly used for AI. This is a long-term digital arms race. And France along with Europe is in the running. What other progress has been made by France’s national AI research program? The four interdisciplinary institutes for AI research have just submitted their final documents and will be approved in April. Progress is being made with setting up 190 AI chairs and with plans

to double the number of PhD students in AI. We’re about to launch a Franco-German call for proposals. It’s been a long time since we’ve had such coherent action: infrastructures, major challenges for France’s Innovation Council, and support for research and training.

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by academic institutions, which have run 20 GPUs for three weeks!” French researchers have of course made great progress without supercomputers. “If you don’t work on really huge databases, you don’t necessarily need a lot of computing power,” said Fabien Moutarde, a professor at PSL University and deputy director of Mines ParisTech’s center for robotics. Furthermore, open source rules supreme in AI and the GAFA companies’ research is made public. “We can retrieve the neural networks they’ve already trained and adapt them to issues we want to address. So the GAFAs’ domination isn’t that a big of a deal for the applied research we do,” continued Moutarde. Nevertheless, he acknowledged that: “We were to some extent practicing self-censorship. In contrast, we’re now doing cutting-edge research on reinforcement learning for autonomous driving. As we encroach on DeepMind’s [ed. note: Google subsidiary] territory, we realize that we’re reaching the limits of our computing power.” In conclusion, Moutarde said: “If we want to carry out pure research and not settle for reusing what the GAFA companies have developed, we need supercomputers.”

essential for pure research

“Without supercomputers, we won’t be able to develop new algorithms, challenge the tech giants, or even reproduce their results,” said Sportisse. This last point is something that Schoenauer finds especially disturbing: “Deep learning is still a very experimental science and has sometimes been compared to alchemy in the Middle Ages. We’re proceeding by approximation and trial and error, carrying out tests, adding a little coefficient, etc. Without theory, experimentation, i.e. computing, is the only way to reproduce and hence validate results,” he explained. But having computing power is not enough to reduce the gap with GAFA companies. This is because designing a neural network to perform calculations in thousands of GPU

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SIMULATION GPUs Are essentIAl What are these GPus at the heart of France’s HPC-IA supercomputer? Graphics processing units were originally used to relieve the central processing unit (CPu) of calculations for monitor screen display. Designed to process millions of pixels simultaneously and boosted by video games’ requirements, GPus have emerged as deep learning’s driver. There is good reason for this: “Deep learning is based on matrix calculations, involving a great many identical

operations. It’s therefore possible to make deep learning almost entirely parallel on GPus,” explained INrIA’s marc schoenauer. Performing calculations in parallel rather than one after another in central processing units speeds things up considerably. so much so that the stock price of NvIDIA, the GPu world leader, has increased tenfold over the past four years.

cores involves an entire system, combining several layers of software. Building a model, processing data, defining calculations, distributing tasks over GPUs, etc. all require software. And this all has to be kept compatible and running smoothly on a daily basis, despite updates and the other finer points of IT systems, not to mention the operating system and management of the calculation queue. The scale of the task can be crippling for researchers. “We did wonder about buying a fairly robust shared supercomputer for 40,000 euros. But we abandoned that idea since there was no one to manage it,” said Moutarde. In Schoenauer’s team, “two computer geek PhD students are looking after everything for the time being. We’ve arranged things so that this work replaces the teaching load they would normally carry out, but it’s a makeshift solution. Hiring system technicians to install and maintain the entire chain is essential,” he said. Although technical support is a clearly identified part of France’s national strategy and is regarded as crucial by Bruno Sportisse, its details remain to be worked out. Implementing technical support is essential to ensure this incredible supercomputer does not run idle.

CFD

FEM

l’usine nouvelle SPECIAL FEATURE MAGAZINE 2 § APRIL 25 2019

P.I.L

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activities here, covering the entire value chain of high-performance computing, from components and systems to software and applications..

Research. Industrial research laboratories work on developing, mastering and deploying new technologies in the HPC and big data fields.

INDUSTRIAL USERS TECHNOLOGY COMPANIES ND EDUCATION

Contact & Information Jean-Pascal Jégu jean-pascal.jegu@teratec.fr • Tel. +33 (0)9 70 65 02 10 Campus Teratec 2 rue de la Piquetterie - 91680 Bruyères-le-Châtel - France

www.teratec.eu

simulation

SuperComputerS

EuropE is GoinG on thE Offensive To acquire exascale supercomputers, the EU has launched an unprecedented plan to invest in high-performance computing. AlAin ClApAud

attle stations! Europe has decided to acquire computing power in line with its position as the world’s second biggest economy. The time has come for Europe, which has lost ground to its main international rivals, to surge forth. As Mariya Gabriel, the European commissioner for digital economy and society, hammered home: “Europe’s undeniable asset is its research, which represents 30% of research worldwide. We have extremely diverse data sources, giving great added value. It isn’t

just about the car industry, but also healthcare, transportation, etc. It’s important to show how supercomputers provide concrete benefits for Europe’s citizens.” Whereas less than ten years ago, Europe had four supercomputers in the world’s top 10, it now only has two. Not only has Europe been overtaken by the USA and China in terms of computing infrastructures, it can no longer rely solely on US technology to acquire world-class supercomputers. With its Teratec association and single manufacturer (Atos Bull), France used to resemble a Gaulish village in the Asterix series, determined to fight tooth and nail for its lost sovereignty. But France’s perseverance in holding out for a HPC strategy paid in the end. Its talk about the major role of highperformance computing for Europe’s independence has been heard and, above all, echoed by the European Commission. Mariya Gabriel, who took over from Andrus Ansip, has far more resources. “The movement was launched at the Digital Days in March 2017, when seven EU member states decided to join forces and work to achieve a truly European simulation project,” said Gabriel. She has since managed to negotiate a 1 billion euro budget to structure the EuroHPC initiative so that it “drives Europe’s reconquest.”

developing its own technology

The EuroHPC joint undertaking has drawn up a roadmap. Under this plan, the first two pre-exascale supercomputers, expected to be among the world’s top 25, will be rolled out in 2021, followed in 2023 by two exascale supercomputers expected to rank in the world’s top 5. The EuroHPC joint undertaking has a governing board, responsible for supervising Europe’s strategy and making budgets available. In addition, there are two advisory groups: one for large infrastructures and another for scientific research. “These independent advisers will ensure that European-level decisions take account of reality and will guarantee our independence as Europeans,” said Gabriel. But Europe does not just plan to acquire supercomputers since it is also aiming to develop HPC technology. No fewer

Public budgets, the Key to success Daniel Verwaerde, general administrator of the French Alternative Energies and Atomic Energy Commission until 2018, became president of Teratec in October of the same year. This is an association he knows well since he was actively involved in setting it up in the early 2000s. According to Verwaerde, member states and the European Commission have an essential role if Europe wants to get back in the running. 40

“The budgets of private companies are no longer enough to develop this technology. In whatever country or region, significant state aid is available. In the early 2000s, I encouraged France to make a budget available to develop computing technology, which is what Teratec achieved,” he said. Verwaerde now sits on the EuroHPC’s advisory group, the working group that will decide on Europe’s next

l’usine nouvelle SPECIAL FEATURE MAGAZINE 2 § APRIL 25 2019

major investments as it moves towards exascale capacity. “Europe is going to fund projects that, in the future, will enable a supercomputer to be built using European technology. Europe’s industry regularly sells supercomputers with 20-30 petaflops of computing power. What Europe has hitherto lacked to progress further is a client!”

89 rESEArCH PrOJECTS FOr A EurOPEAN SuPErCOmPuTErlEs INDuSTrY lEsEnQuÊtEs

Europe is to earmark 480 million euros to develop the next-generation supercomputers. This huge project is focusing on three main priorities: supercomputer installation, computing architecture, and components. FINLANDE

X Nombre de projets ONLY THE INSTITUTIONS MANAGING THE PROJECTS ARE INDICATED

CSC-Centre ﬁnlandais d’expertise en TIC

SUÈDE

5 Université d'Édimbourg

Université Queen's de Belfast Intel Université nationale d'Irlande à Galway

IBM

5 5

Institut royal de technologie

5 7

IRLANDE

STFC-Laboratoire de Daresbury Centre européen pour les prévisions ROYAUME-UNI météorologiques Maxeler à moyen terme Technologies

5 6

Université de Manchester ARM Allinea Software SURFsara

PAYS-BAS

Inria

Université technique de Rhénanie-Westphalie

5 14

ALLEMAGNE

Université technique d'Ostrava

8 13

Institut Fraunhofer Société Max-Planck pour le développement des sciences École polytechnique fédérale de Zurich

8 SUISSE 6

École polytechnique fédérale de Lausanne

POLOGNE

RÉPUBLIQUE TCHÈQUE

Atos Bull

FRANCE

Centre de recherche de Jülich Université de Stuttgart

CEA

Institut de chimie bio-organique de l’Académie polonaise des sciences

Université d'Amsterdam

CNRS

7 12 13 11

Université de technologie de Chalmers

École polytechnique de Milan

Cineca ITALIE

ESPAGNE

Fondation pour la recherche et l’éducation de Chypre

Barcelona Supercomputing Center (BSC) Fondation pour la recherche et la technologie - Grèce

than 89 research projects funded by the Horizon 2020 program, involving almost 1,350 partners in 43 countries, are rallying to achieve this goal. The research covers many fields: parallel programming, new materials for high-performance semiconductors, the cloud, reducing energy consumption, software, etc. The most iconic research project in this effort is without doubt the European Processor Initiative (EPI) to develop a low-power processor. The project brings together 23 partners, including the French Alternative Energies and Atomic Energy Commission, the Barcelona Supercomputing Center (BSC), the Fraunhofer Institute, STMicroelectronics, the French firm Kalray, and several car manufacturers. A few years ago, it may have seemed pointless to produce better processors and computing accelerators than those made by the US firms Intel, AMD, and NVIDIA for powering highperformance supercomputers. But China has since led the way: its Sunway TaihuLight supercomputer, the third most powerful in the world, is driven by chips designed and made in China.

Réseau grec de recherche et de technologie

5 CHYPRE

“The USA’s budget to achieve exascale capacity is an estimated 5-6 billion dollars,” said Daniel Verwaerde, president of Teratec and member of the EuroHPC’s infrastructures advisory group. “With Atos Bull, Europe can already design and build supercomputers with several dozen petaflops of computing power. The main thing Europe lacks is a processor. It’s essential for Europe to reposition itself on this industry, especially since these processors won’t just be used for massively parallel computing in supercomputers. They could also end up in our smartphones, digital tablets, computers, and connected objects.”

two areas of r&d

This challenge has been fully integrated into the EuroHPC roadmap. The first generation of processors, expected by 2021 and that will power one of Europe’s two exascale supercomputers, will be launched at the same time as a demonstrator of an embedded version for the car industry. Two areas of R&D are expected to run simultaneously on this project: one using ARM chips to create a general-purpose 41

SOURCE : EUROHPC.EU

GRÈCE

simulation processor for supercomputers; the other on RISC-V architecture to design an accelerator. The second generation, expected by 2023, will power Europe’s exascale supercomputer, while the third generation, scheduled for 2025, is expected to combine the supercomputer processor and accelerator and develop a processor for the car industry. Europe hopes to finalize the design phase for the initial version of its first-generation European chip by the end of this year.

“EuropE has bEcomE GEnuinEly awarE” Mariya Gabriel

What are your goals for europe’s computing? Our goal is very clear: we will have a European exascale supercomputer by 2022–23. Although we’ll have to work hard to do this, we’ve already made a good start. We’ve obtained a 1 billion euro budget within a year, provided equally by the European Commission and member states. In addition, we’ve set up the EuroHPC joint initiative and created a legal entity to facilitate how it runs. In November 2018, the EuroHPC governing board held its first meeting with member states’ appointed representatives; it now has the resources it needs to move forward. the number of states represented in the eurohPc project has risen from 7 to 25 within a few months. how do you explain this enthusiasm? Europe has become genuinely aware that we should be acting jointly rather than leaving action to the only member states advanced in this field. We need to ensure that every EU state participates. We also had to include SMEs from the outset, giving them access to computing. This was a very strong message. 42

J. JACquEmArT

According to the European commissioner for digital economy and society, the conditions are ripe to carry through Europe’s exascalesupercomputer project and promote the use of simulation.

Nevertheless, there are still many technological uncertainties and obstacles, which must be resolved before Europe’s first supercomputer can be powered by processors made in Europe. The commissioning of this supercomputer is expected to start in 2023. Europe has finally given itself the means that match its goals.

Will the research effort under horizon 2020 enable industry champions, which europe’s computing still lacks, to emerge? It’s true that Europe has fallen behind, but it’s not too late. We have the resources and assets to quickly get back in the running. We’ve made a considerable budgetary effort in a context of many new priorities, such as security, migration, and defense. The budget earmarked for digital technology over the coming period has increased 98%. It’s not just about Horizon 2020, but also the Digital Europe Program, which has dedicated 2.8 billion of its 9.2 billion euro budget to supercomputers.

l’usine nouvelle SPECIAL FEATURE MAGAZINE 2 § APRIL 25 2019

Apart from this research and infrastructure component, what can europe do to encourage companies to use simulation? EuroHPC represents a considerable effort, and not just in terms of budget. We want to pool resources to build a true network via Digital Innovation Hubs. This initiative makes provision for an innovation center in every region of Europe to work in networks, avoid duplication, and quickly identify good practices, scaling them up and giving them visibility. interviewed by A. C.

5 th ed

TROPHĂ&#x2030;ES

iti

2019

Lâ&#x20AC;&#x2122;Usine Digitale highlights your innovative projects ? Digital Simulation ? High Performance Computing ? Big data and virtual reality

Details and application form: http://events.usine-digitale.fr Contact: trophee_simulation@infopro-digital.com Organized with:

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Submit your application by April 30th, 2019! Supported by:

How do we explain that massive fuel-starved stars generate explosions 10 to 100 times brighter than a conventional supernova? Thanks to the powerful and orderly magnetic fields due to the dynamo effect that occurs when these stars collapse. This has been demonstrated by astrophysicists at the California Institute of Technology through simulation.

lâ&#x20AC;&#x2122;usine nouvelle SPECIAL FEATURE MAGAZINE 2 Â§ APRIL 25 2019

SIMULATION a tool developed by the fraunhofer IWm Institute in freiburg determines how the abrasive particles of toothpaste interact with the bristles of a toothbrush. It also calculates cleaning efficacy and the effects of brushing on tooth enamel. material, particle size and quantity, shape and elasticity of the bristles can be modified in one click.

a solution developed by Total to convert a seismic image into geological data, Sismage has gradually been enhanced with multiple functionalities in order to become the foundation of the Total exploration and Production geosciences software chain.

A standard tool in geological sciences and the design of aerodynamic objects, simulation is also used to explore submarines, optimize tooth brushing and to study forests.

portfolio

Simulation in all its forms manuel moragues

CalTeCH ; G. leImdorfer / ToTal ; d.r.

To make a helmet dedicated to both cycling and speed skating, louis Garneau Sports studied the differences in airflow according to the position of the shoulders in each sport in order to find the best possible profile for each discipline.

SIMULATION developed by the CNrS, the dynamic simulation of the biomechanical behaviour of the human foot helps to visualize stress on ligaments and planar pressure during a walking session and to better understand the distribution of strain. This will reduce potential trauma.

o. le ComTe / eCPad / defeNSe

modelled by the Institute of earth Sciences, this section of the earth’s core in the plane of the equator shows the temperature variations (negative in blue, positive in gold) that animate the liquid iron convection movements, at the origin of the magnetic field that protects the earth. When will the next pole reversal take place?

CIrad

N. SCHaeffer / ISTerre / CNrS

Naval Group designed Ship Inside to train the crew of its future Barracuda nuclear attack submarines. a complete simulation of these 5000-ton vessels in which, using virtual reality headsets for total immersion, sailors learn to operate the various systems, the equipment and how to react to damage.

l’usine nouvelle SPECIAL FEATURE MAGAZINE 2 § APRIL 25 2019

The Heterofor model created at the Catholic University of louvain, Belgium, integrates different modules (light interception, carbon allocation, mineral nutrition etc) to describe individual tree growth in mixed stands taking into account their interactions. Here, a forest of oak and beech in the Belgian ardennes.

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