INNOVATIVES SUPERCOMPUTING IN DEUTSCHLAND N O 19-1 · SPRING 2021 IMPRINT EDITORIAL CONTENTS

Imprint 2

Editorial 3

elcome to the latest issue of InSiDE, the bi-annual NEWS FEATURES W Gauss Centre for Supercomputing magazine showcas- LRZ to Expand its Flagship Supercomputing ing innovative supercomputing developments in Germany. System to Integrate HPC and AI 4 While many of the centres’ staffs have remained working from home to start 2021, the increasing global vaccination Hawk Expansion Will Accelerate Research rates leave us hopeful that the latter half of the year can bring Combining Simulation and Artificial Intelligence 6 Publishers a return to in-person education and training as well as other events at our centres. We look forward to welcoming our German National Supercomputing Centre staff, supporters, and research collaborators back as soon as Provides Computational Muscle to Look for conditions allow. Cracks in the Standard Model of Physics 9

The latest issue of InSiDE is also looking forward. In Gar- SCIENCE FEATURES ching, the Leibniz Supercomputing Centre announced its Researchers Use LRZ HPC Resources to Perform latest addition to the GCS HPC family—SuperMUC-NG Largest-Ever Supersonic Turbulence Simulation 12 Phase 2 is being developed with partners at Intel and Lenovo (Page 4). The centre also inaugurated its Quantum Integra- HPC Helps Scientists in Quest for Advancing tion Centre during the first half of the year, looking to take Hydrogen-Based Energy Storage 14 another meaningful step forward in scaling up the exciting Prof. Dr. D. Kranzlmüller Prof. Dr. Dr. Th. Lippert Prof. Dr.-Ing. Dr. h.c. Dr. h.c. potential hidden in quantum computers (Page 26). In that Researchers Use the Power of HPC to Elucidate Director Director Hon.-Prof. M. M. Resch same vein, HLRS is participating in the SEQUOIA project, Hund Metal Characteristics 16 Leibniz Supercomputing Centre Jülich Supercomputing Centre Director funded by the Baden-Württemberg Ministry of Economic High-Performance Affairs, Labor, and Housing to support bringing the promise PROJECTS Computing Center Stuttgart of quantum computing to industrial researchers, and JSC is SEQUOIA Project to Bring Quantum continuing to extend its Jülich UNified Infrastructure for Computing to Industry 18 Quantum computing, JUNIQ, co-funded by the German Federal Ministry of Education and Research (BMBF) and DEEP-SEA and REGALE Help the Ministry of Culture and Science of the State of North Bolster Dynamic Software for Exascale 20 Rhine-Westphalia. © HLRS 2021 Contributing Authors Advancing AI Technologies Towards InSiDE is published two times a year by the Gauss Centre While all three of our centres aim to embrace new technol- Exascale Computing 22 for Supercomputing (HLRS, JSC, LRZ) Eric Gedenk (eg), GCS, HLRS ogies and equip our users with the skills needed to make the [email protected] most of them, our users are embracing our current generation EVENTS Editor-in-Chief [email protected] of systems for groundbreaking research findings. Staff at JSC JUWELS Booster Early Days Help Users Make Michael Resch, HLRS partnered with researchers at the University of Wuppertal the Most of JSC’s GPU-Accelerated Module 24 [email protected] Christopher Williams (cw), HLRS to run unprecedented simulations of tiny subatomic muons [email protected] in the search for cracks in the standard model of physics. LRZ Steps Into the Quantum Age 26 Editor The work accompanies major findings released as part of Eric Gedenk, GCS, HLRS Sabrina Schulte (sts), LRZ the “muon g-2” collaboration earlier this year (Page 9). Re- SAS Workshop Consider History of [email protected] [email protected] searchers are using HLRS computing resources to develop Imitation, Adaption, and Deception 28 [email protected] more efficient methods for storing energy with hydrogen, a Susanne Vieser (sv), LRZ potential game-changing technology for storing renewable NEWS BRIEFS 30 Production Manager [email protected] energy more efficiently (Page 14). F. Rainer Klank, HLRS INSIDE GCS [email protected] Andreas Lintermann (al), JSC We are still committed to making our resources available Staff Spotlight: Reflecting on 35 Years of HPC, [email protected] to researchers focused on getting the world beyond the 19-1 · SPRING 2021 Recently Retired Application Support Group Leader Design COVID-19 pandemic. These last 18 months have provided Reflects on HPC Developments Past and Present 36 Zimmermann Visuelle Kommunikation Andreas Herten (ah), JSC unprecedented challenges to people all over the world, and www.zimmermann-online.info [email protected] the pandemic has left us with new questions about how to TRAININGS 39 govern certain aspects of our lives moving forward. GCS has Jan Schulze (js), LRZ a long history of embracing new challenges and helping pave CENTRE DESCRIPTIONS This magazine is printed on paper that has been certified [email protected] the way toward solutions. In 2021, our commitment to this INSIDE · 19-1 SPRING 2021 by FSC, the EU Ecolabel, and the Blue Angel Ecolabel. work is as strong as ever. Jülich Supercomputing Centre 40 INSIDE · NO

If you would like to receive InSiDE regularly, please send Prof. Dieter Kranzlmüller Leibniz Supercomputing Centre 42 an e-mail with your postal address to F. Rainer Klank: Visit us at: Prof. Thomas Lippert

2 [email protected] www.gauss-centre.eu Prof. Michael Resch High-Performance Computing Center Stuttgart 44 3 NEWS FEATURES NEWS FEATURES

LRZ TO EXPAND ITS FLAGSHIP SUPERCOMPUTING SYSTEM TO INTEGRATE HPC AND AI

Together with its partners Intel and Lenovo, the Leibniz Supercomputing Centre is designing the second phase of its flagship supercomputer to ensure that users focused on data-intensive applications and emerging technologies can take full advantage of the new system.

ogether with its partners Intel and Lenovo, the LRZ has chosen to partner with Intel in bringing their T Leibniz Supercomputing Centre (LRZ)—one of the SuperMUC system to market based on Intel’s XPU product three HPC centres in the Gauss Centre for Supercomputing portfolio, advanced packaging and memory technologies, (GCS)—will expand its current flagship HPC system Su- and the unified oneAPI software stack to power the next perMUC-NG. In addition to top performance in simulation generation of high-performance computing.” and modeling, phase 2 of SuperMUC-NG will integrate and advance artificial intelligence (AI) methods of computation. Practical experience with using artificial intelligence meth- ods is increasingly becoming a key capability in science. For this purpose, the system will be equipped with This is attracting new user groups to LRZ: Until now, it was next-generation Intel Xeon Scalable processors (codenamed mostly experts from physics, engineering and the natural Sapphire Rapids) and “Ponte Vecchio”, Intel’s upcoming sciences who relied on high-performance computing. With GPU based on the Xe-HPC micro-architecture for high- AI techniques becoming more widely used, demand in HPC performance computing and AI. The storage system will and AI resources is now increasing in the fields of medicine, feature distributed asynchronous object storage (DAOS), life and environmental sciences, as well and the humanities. and leverage 3rd Gen Intel Xeon Scalable processors and For example, practitioners use automated image, speech, Intel Optane persistent memory to accelerate access to large or pattern recognition in earth observation or climate data amounts of data. from satellites, anonymized medical imagery and health records, or data demographics. The more complex these As with Phase 1, SuperMUC-NG Phase 2 will be jointly neural networks and the desired functions, the higher the funded by the Free State of Bavaria and the Federal Minis- demand for computing and fast memory performance. try of Education and Research (BMBF) through GCS. The computing capacities are made available to specially qual- SuperMUC-NG already offers enormous computing power, ified research projects nationwide in a scientific selection but will now be upgraded for more diverse tasks with this SuperMUC-NG already offers enormous computing power, but will now be upgraded for more diverse tasks with this expansion. © LRZ process. expansion: Some of the new technology is currently being tested in the LRZ test environment BEAST (Bavarian, En- New research tasks for supercomputing ergy, Architecture, Software Testbed) to better understand its capability in a future large-scale HPC system. To ensure EMEA Director, HPC & AI, ISG at Lenovo. “Sustainability LRZ training program also offers a wide variety of machine that phase 2 of SuperMUC-NG continues to operate as has also been important for LRZ in its infrastructure proj- and deep learning courses where students and researchers “At the core of all LRZ activities is the user. It is our utmost energy-efficient as possible, the 240 Intel compute nodes ects. That’s why we are pleased to play a part in this ini- learn how to adapt existing algorithms or develop and train priority to provide researchers with the resources and are integrated into Lenovo’s SD650-I v3 platform, which tiative too, as the Lenovo components for SuperMUC-NG their own. sts and sv services they need to excel in their scientific domains,” is directly cooled with warm water, and connected to the phase 2 will be manufactured in our new production says Prof. Dr. Dieter Kranzlmüller, Director of the LRZ. DAOS storage system via a high-speed network. Its capac- facility in Hungary—rather than in our American or Asian “Over the last years, we’ve observed our users accessing ity is 1 petabyte of data storage, but more importantly, this production facilities—further improving the eco-footprint 19-1 · SPRING 2021 our systems not only for classical modeling and simulation, technology enables fast throughput of large data volumes. of our supply chain.” 19-1 · SPRING 2021 but increasingly for data analysis with artificial intelligence This system architecture is particularly well-suited then methods.” This requires not only computing power, but for highly scalable, compute- and data-intensive workloads Consulting and training different computer architectures and configurations as well and artificial intelligence applications. as more flexible data storage. “The Leibniz Supercomputing Centre has been a thought While the DAOS storage system is expected to arrive in “We’re continuously pushing the boundaries of hardware leader in new technologies for many years, setting stan- Garching in the fall of 2021, the compute system will fol- INSIDE · NO and software technology to deliver an easy and scalable dards for research and development and being an important low in the spring of 2022. The LRZ is working with its user INSIDE · NO compute stack in the data center for a wide range of diverse innovation partner for Lenovo. For example, LRZ has al- community in preparation: Researchers already have access and emerging workloads in HPC and AI,” said Raja Koduri, ready installed warm water cooling and is planning to im- to GPU systems specialized on AI applications and LRZ’s SVP, chief architect, and general manager of Architecture, plement an integrated system for artificial intelligence and HPC and Big Data teams consult and support the users in

4 Graphics, and Software at Intel. “We are thrilled that deep learning - all from Lenovo,” emphasizes Noam Rosen, adapting and optimizing their codes and AI algorithms. The 5 NEWS FEATURES NEWS FEATURES

HAWK EXPANSION WILL ACCELERATE RESEARCH COMBINING SIMULATION AND ARTIFICIAL INTELLIGENCE

The addition of HPE Apollo systems with NVIDIA graphic processing units (GPUs) to HLRS‘s flagship supercomputer will enhance the center‘s capacity for deep learning applications and enable new kinds of hybrid computing workflows that integrate HPC with Big Data methods.

Resch. “For many years this has meant basing our flagship For technical reasons, such deep learning approaches do systems on CPUs to support codes used in computationally not run efficiently on CPU processors, but benefit from a intensive simulation. Recently, however, we have seen different type of accelerator called a graphic processing growing interest in deep learning and artificial intelligence, unit. Originally designed to rapidly re-render screens in which run much more efficiently on GPUs. Adding this action-packed video games, GPUs are also capable of an- second key type of processor to Hawk’s architecture will alyzing the large matrices of data required for algorithms improve our ability to support scientists in academia and using neural networks. industry who are working at the forefront of computational research.” Whereas CPUs are best suited for diverse calculations, GPUs are better at flying through repetitive tasks in parallel. Two approaches to computational research: In deep learning and AI this can mean simultaneously com- paring hundreds of thousands of parameters in millions of simulation vs. deep learning large datasets, identifying meaningful differences in them, and producing a model that describes them. In the past, HLRS’s flagship supercomputers — Hawk, and previously Hazel Hen — have been based exclusively Hybrid methods that integrate HPC and AI can on central processing units. This is because CPUs offer the best architecture for many codes used in fields such as com- accelerate computational engineering putational fluid dynamics, molecular dynamics, climate modeling, and other research areas in which HLRS’s users Although some have speculated that AI could eventually are most active. Because the outcomes of simulations are replace high-performance computing altogether, the truth often applied in the real world (for example, in replacing is that some of the most interesting research methods right automobile crash tests), simulation algorithms must be as now lie in combining these bottom-up and top-down accurate as possible, and are thus based on fundamental approaches. HLRS and HPE at the contact signing. (l-r) Heiko Meyer (Chief Sales Officer, Hewlett Packard Enterprise), Prof. Michael scientific principles. At the same time, however, such Resch (Director, HLRS), Aron Precht (VP Channels & Ecosystem DACH, HPE), Jan Gerken (Chancellor, University of methods require large numbers of computing cores and Deep learning algorithms typically require enormous Stuttgart). © HLRS long computing times, generate enormous amounts of amounts of training data in order to produce statistically data, and require specialized programming expertise to run robust models — a task that is perfectly suited to high-per- efficiently. formance computers. At the same time, models created using deep learning on GPU-based systems can inform In recent years, researchers have begun exploring how deep and accelerate researchers’ use of simulation. Learning awk, a Hewlett Packard Enterprise (HPE) Apollo sys- (AI), but also enable new kinds of hybrid computing work- learning, high-performance data analytics, and artificial algorithms can, for example, reveal key parameters in data, H tem installed in 2020, is already one of Europe’s most flows that combine traditional simulation methods with intelligence could accelerate and simplify such research. generate hypotheses that can guide simulation in a more powerful high-performance computing (HPC) systems. In Big Data approaches. As opposed to simulation, in which a complex system is directed way, or deliver surrogate models that substitute 19-1 · SPRING 2021 November it placed 16th in its debut on the Top500 list of modelled in a “top-down” way based on scientific princi- for compute-intensive functions. New research methods 19-1 · SPRING 2021 the world’s fastest supercomputers, based on the High-Per- The expansion also offers a new AI platform with three ples, these newer methods use a “bottom-up” approach. have begun integrating these approaches, often in a circu- formance Linpack (HPL) benchmark. times the number of NVIDIA processors found in HLRS’s Here, deep learning algorithms identify patterns in large lar, iterative manner. Cray CS-Storm system, its current go-to system for AI ap- amounts of data, and then create a computational model Through an agreement signed with HPE in December, plications. It will enable larger-scale deep learning projects that approximates the behavior of the actual data. The Examples of interactions between HPC and AI HLRS will soon expand this world-class CPU-based and expand the amount of computing power for AI that is “trained” model can then be used to predict how other computing system by adding 24 HPE Apollo 6500 Gen10 available to HLRS’s user community. systems that are similar to those in the original dataset will INSIDE · NO Plus systems with 192 NVIDIA A100 GPUs based on the behave. Although such models are not guaranteed to be as In 2019 HLRS made a significant leap into the world of INSIDE · NO NVIDIA Ampere architecture. The addition of 120 peta- “At HLRS our mission has always been to provide systems precise as simulations based on first principles, they often deep learning and artificial intelligence by installing an flops of AI performance will not only dramatically expand that address the most important needs of our key user provide approximations that are close enough to be useful NVIDIA GPU-based Cray CS-Storm system. The addition HLRS’s ability to support applications of deep learning, community, which is largely focused on computational in practice, complementing or sometimes even replacing has been well received by HLRS’s user community, and is 7 6 high-performance data analytics, and artificial intelligence engineering,” explained HLRS Director Prof. Michael more computationally intensive approaches. currently being used at near capacity. NEWS FEATURES NEWS FEATURES

GERMAN NATIONAL SUPERCOMPUTING CENTRE PROVIDES COMPUTATIONAL MUSCLE TO LOOK FOR CRACKS IN THE STANDARD MODEL OF PHYSICS

Physicists have spent 20 years trying to more precisely measure the so-called “magnetic moment” of subatomic particles called muons. Findings call into question long-standing assumptions of particle physics.

hysicists have spent 20 years trying to more pre- Both the experimentalists and theoretical physicists agreed P cisely measure the so-called “magnetic moment” that further research must be done to verify the results of subatomic particles called muons. Findings call published this week. One thing is clear, however: the HPC into question long-standing assumptions of particle resources provided by GCS were essential for the scientists physics. to achieve the precision necessary to get these ground- breaking results. Since the 1970s, the Standard Model of Physics has served as the basis from which particle physics are investigated. “For the first time, lattice QCD results have a precision Both experimentalists and theoretical physicists have comparable to these experiments. Interestingly our result tested the Standard Model’s accuracy, and it has remained is consistent with the new FNAL experiment, as opposed the law of the land when it comes to understanding how the to previous theory results, that are in strong disagreement subatomic world behaves. with it,” said Prof. Kalman Szabo, leader of the Helmholtz research group, “Relativistic Quantum Field Theory” at JSC Recently, cracks formed in that foundational set of as- and co-author of the Nature publication. “Before deciding sumptions. Researchers of the “Muon g-2” collaboration the fate of the Standard Model, one has to understand the from the Fermi National Accelerator Laboratory (FNAL) theoretical differences, and new lattice QCD computations in the United States published further experimental find- are inevitable for that.” ings that show that muons—heavy subatomic relatives of electrons—may have a larger magnetic moment than earlier Minor discrepancies, major implications Standard Model estimates had predicted, indicating that an unknown particle or force might be influencing the muon. The work builds on anomalous results first uncovered 20 When BNL researchers recorded unexplained muon years ago at Brookhaven National Laboratory (BNL), and behavior in 2001, the finding left physicists at a loss— Various interaction patterns between AI and simulations: a) generation of data for AI training from simulations; b) finding simulation calls into question whether the Standard Model needs to be the muon, a subatomic particle 200 times heavier than parameters by AI; c) generation of initial solutions by AI; d) choosing the right path by AI; e) replacing iterations in simulation by AI; f) rewritten. an electron, showed stronger magnetic properties than replacing specific functions/equations by AI. predicted by the Standard Model of Physics. While the Meanwhile, researchers in Germany have used Europe’s initial finding suggested that muons may be interacting most powerful high-performance computing (HPC) in- with previously unknown subatomic particles, the re- frastructure to run new and more precise lattice quantum sults were still not accurate enough to definitely claim a Although the Cray CS-Storm system is well suited for workflows in separate stages will practically disappear. Users chromodynamics (lattice QCD) calculations of muons in new finding. both standard machine learning and deep learning proj- will be able to stay on the computing cores they are using, a magnetic field. The team found a different value for the ects, the experience has nevertheless revealed limitations run an AI algorithm, and integrate the results immediately.” Standard Model prediction of muon behavior than what Over the next 20 years, heavy investments in new, hy- in using two separate systems for research involving hy- was previously accepted. The new theoretical value is in per-sensitive experiments done at particle accelerator brid workflows. Hawk and the Cray CS-Storm system use HLRS users will also be able to leverage the NVIDIA NGC™ agreement with the FNAL experiment, suggesting that a facilities as well as increasingly sophisticated approaches 19-1 · SPRING 2021 separate file systems, meaning data must be moved from catalog to access GPU-optimized software for deep learn- revision of the Standard Model is not needed. The results based in theory have sought to confirm or refute the BNL 19-1 · SPRING 2021 one system to the other when training an AI algorithm or ing, machine learning, and high-performance computing are now published in Nature (https://doi.org/10.1038/ group’s findings. During this time, a research group led using the results of an AI model to accelerate a simulation. that accelerates development-to-deployment workflows. s41586-021-03418-1). by the University of Wuppertal’s Prof. Zoltan Fodor, These transfers require time and workflow interruptions Furthermore, the combination of the new GPUs with another co-author of the Nature paper, was progressing and that users master the ability to program two very the In-Networking Computing acceleration engines of The team primarily used the supercomputer JUWELS at with big steps in lattice QCD simulations on the super- different systems. the HDR NVIDIA Mellanox InfiniBand network enables the Jülich Supercomputing Centre (JSC), with the compu- computers provided by GCS. “Though our results on the leading performance for the most demanding scientific tational time provided by the Gauss Centre for Supercom- muon g-2 are new, and have to be thoroughly scrutinized INSIDE · NO “Once NVIDIA GPUs are integrated into Hawk, hybrid workloads. puting (GCS) as well at JSC’s JURECA system, along with by other groups, we have a long record of computing INSIDE · NO workflows combining HPC and AI will become much more extensive computations performed at the other two GCS various physical phenomena in quantum chromodynam- efficient,” said Dennis Hoppe, who leads artificial intelli- Hoppe also anticipates that in the future the new GPUs sites—on Hawk at the High-Performance Computing Cen- ics.” said Fodor. “Our previous major achievements were gence operations at HLRS. “Losses of time that occur because could be more easily used to run certain kinds of traditional ter Stuttgart (HLRS) and on SuperMUC-NG at the Leibniz computing the mass of the proton, the proton-neutron 9 8 of data transfer and the need to run different parts of the simulation applications more quickly. cw Supercomputing Centre (LRZ). mass difference, the phase diagram of the early universe NEWS FEATURES NEWS FEATURES

and a possible solution for the dark matter problem. These paved the way to our most recent result.”

Lattice QCD calculations allow researchers to accurately plot subatomic particle movements and interactions with extremely fine time resolution. However, they are only as precise as computational power allows—in order to perform these calculations in a timely manner, researchers have had to limit some combination of simulation size, resolution, or time. As computational resources have got- ten more powerful, researchers have been able to do more precise simulations.

“This foundational work shows that Germany’s world- class HPC infrastructure is essential for doing world-class science in Europe”, said Prof. Thomas Lippert, Director of the Jülich Supercomputing Centre, Professor for Quantum Computing and Modular Supercomputing at Goethe Uni- versity Frankfurt, current Chairman of the GCS Board of Directors, and also co-author of the Nature paper. “The computational resources of GCS not only play a central role in deepening the discourse on muon measurements, but they help European scientists and engineers become leaders in many scientific, industrial, and societal research areas.”

While Fodor, Lippert, Szabo, and the team who published the Nature paper currently use their calculations to cool the claims of physics beyond the Standard Model, the research- ers are also excited to continue working with international colleagues to definitively solve the mystery surrounding muon magnetism. The team anticipates that even more powerful HPC systems will be necessary to prove the ex- istence of physics beyond the Standard Model. “The FNAL experiment will increase the precision by a factor of four in two years. We theorists have to keep up with this pace if we want to fully exploit the new physics discovery potential of muons.” Szabo said. eg 19-1 · SPRING 2021 19-1 · SPRING 2021

Does the magnetic moment of muons fit into our understanding of the laws governing the physical world around us? © Uni Wuppertal/thavis gmbh INSIDE · NO INSIDE · NO 11 10 SCIENCE FEATURES SCIENCE FEATURES

RESEARCHERS USE LRZ HPC RESOURCES TO PERFORM LARGEST-EVER SUPERSONIC TURBULENCE SIMULATION

A multi-institution team from Australia and Germany simulates turbulence happening on both sides of the so-called “sonic scale,” opening the door for more detailed and realistic galaxy formation simulations. I

hrough the centuries, scientists and non-scientists dynamics representing a wide variety of scales. Specifically, Turbulence shaping the interstellar medium. The T alike have looked at the night sky and felt excitement, the team needed to simulate turbulent dynamics on both image shows a slice through the turbulent gas in intrigue, and overwhelming mystery while pondering sides of the sonic scale in the complex, gaseous mixture the world’s highest-resolution simulation of turbu- questions about how our universe came to be, and how travelling across the ISM. This meant having a sufficiently lence published in Nature Astronomy. Turbulence humanity developed and thrived in this exact place and large simulation to capture these large-scale phenomena produces strong density contrasts, so-called shocks time. Early astronomers painstakingly studied stars’ subtle happening faster than the speed of sound, while also ad- (see zoom-in). The interaction of these shocks is movements in the night sky to try and determine how our vancing the simulation slowly and with enough detail to believed to play a key role in the formation of stars. planet moves in relation to other celestial bodies. As tech- accurately model the smaller, slower dynamics taking place © Federrath et al. (2021). nology has increased, so too has our understanding of how at subsonic speeds. Nature Astronomy. DOI: 10.1038/s41550-020-01282-z the universe works and our relative position within it. “Turbulent flows only occur on scales far away from the en- What remains a mystery, however, is a more detailed un- ergy source that drives on large scales, and also far away from derstanding of how stars and planets formed in the first the so-called dissipation (where the kinetic energy of the place. Astrophysicists and cosmologists understand that turbulence turns into heat) on small scales” Federrath said. the movement of materials across the interstellar medium “For our particular simulation, in which we want to resolve (ISM) helped form planets and stars, but how this complex both the supersonic and the subsonic cascade of turbulence mixture of gas and dust—the fuel for star formation— with the sonic scale in between, this requires at least four moves across the universe is even more mysterious. orders of magnitude in spatial scales to be resolved.” In order to accurately simulate the sonic scale and the super- team planned to start incorporating the effects of magnetic sonic and subsonic scales on either side, the team worked fields on the simulation, leading to a substantial increase in To help better understand this mystery, researchers have In addition to scale, the complexity of the simulations is with LRZ to scale its application to more than 65,000 memory for a simulation that already requires significant turned to the power of high-performance computing (HPC) another major computational challenge. While turbulence compute cores on the SuperMUC HPC system. Having so memory and computing power as well as multiple petabytes to develop high-resolution recreations of galactic phenom- on Earth is one of the last major unsolved mysteries of many compute cores available allowed the team to create a of storage—the current simulation requires 131 terabytes of ena. Much like several terrestrial challenges in engineering physics, researchers who are studying terrestrial turbulence simulation with more than 1 trillion resolution elements, memory and 23 terabytes of disk space per snapshot, with and fluid dynamics research, astrophysicists are focused on have one major advantage—the majority of these fluids are making it the largest-ever simulation of its kind. the whole simulation consisting of more than 100 snapshots. developing a better understanding of the role of turbulence incompressible or only mildly compressible, meaning that in helping shape our universe. the density of terrestrial fluids stays close to constant. In “With this simulation, we were able to resolve the sonic Since he was working on his doctoral degree at the Uni- the ISM, though, the gaseous mix of elements is highly scale for the first time,” Federrath said. “We found its lo- versity of Heidelberg, Federrath has collaborated with Over the last several years, a multi-institution collabora- compressible, meaning researchers not only have to account cation was close to theoretical predictions, but with certain staff at LRZ’s AstroLab to help scale his simulations to tion being led by Australian National University Associate for the large range of scales that influences turbulence, they modifications that will hopefully lead to more refined star take full advantage of modern HPC systems. Running the Professor Christoph Federrath and Heidelberg University also have to solve equations throughout the simulation to formation models and more accurate predictions of star largest-ever simulation of its type serves as validation of Professor Ralf Klessen has been using HPC resources at know the gases’ density before proceeding. formation rates of molecular clouds in the universe. The the merits of this long-running collaboration. During this the Leibniz Supercomputing Centre (LRZ) in Garching formation of stars powers the evolution of galaxies on large period, Federrath has worked closely with LRZ’s Dr. Luigi near Munich to study turbulence’s influence on galaxy Understanding the influence that density near the sonic scales and sets the initial conditions for planet formation Iapichino, Head of LRZ’s AstroLab, who was a co-author on formation. The team recently revealed the so-called “sonic scale plays in star formation is important for Federrath on small scales, and turbulence is playing a big role in all of the Nature Astronomy publication. 19-1 · SPRING 2021 scale” of astrophysical turbulence—marking the transition and his collaborators, because modern theories of star this. We ultimately hope that this simulation advances our 19-1 · SPRING 2021 moving from supersonic to subsonic speeds (faster or formation suggest that the sonic scale itself serves as a understanding of the different types of turbulence on Earth “I see our mission as being the interface between the ever- slower than the speed of sound, respectively)—creating the “Goldilocks zone” for star formation. Astrophysicists and in space.” increasing complexity of the HPC architectures, which is largest-ever simulation of supersonic turbulence in the pro- have long used similar terms to discuss how a planet’s a burden on the application developers, and the scientists, cess. The team published its research in Nature Astronomy proximity to a star determines its ability to host life, but Cosmological collaborations and which don’t always have the right skill set for using HPC (https://doi.org/10.1038/s41550-020-01282-z). for star formation itself, the sonic scale strikes a balance resource in the most effective way,” Iapichino said. “From between the forces of turbulence and gravity, creating computational advancements this viewpoint, collaborating with Christoph was quite INSIDE · NO the conditions for stars to more easily form. Scales larger simple because he is very skilled in programming for HPC INSIDE · NO Many scales in a simulation than the sonic scale tend to have too much turbulence, While the team is proud of its record-breaking simulation, performance. I am glad that in this kind of collaborations, leading to sparse star formation, while in smaller, sub- it is already turning its attention to adding more details application specialists are often full-fledged partners of To simulate turbulence in their research, Federrath and his sonic regions, gravity wins the day and leads to localized into its simulations, leading toward an even more accurate researchers, because it stresses the key role centres’ staffs 13 12 collaborators needed to solve the complex equations of gas clusters of stars forming. picture of star formation. Federrath indicated that the play in the evolving HPC framework.” eg SCIENCE FEATURES SCIENCE FEATURES

HPC HELPS SCIENTISTS IN QUEST FOR ADVANCING HYDROGEN-BASED ENERGY STORAGE

Researchers are working to identify materials and methods to improve water electrolysis, a promising approach that could more efficiently store energy generated from renewable sources.

dvances in renewable energy technologies continue effective in order to develop an efficient method for using how the reaction changes under the influence of small full advantage of increasingly powerful architectures such as A to move humanity closer to being able to power our hydrogen to store energy on a global scale. I changes in voltage or of variations in the composition of those made available by GCS at its three centres. lives using cleaner, safer methods. Whether it is wind tur- metal alloys being used as the catalyst, among other inputs. bines or solar panels, researchers have made great strides in “It really is a million-dollar question about why iridium While Jones indicated that faster, larger computers make making these sources more efficient. is so special,” said Dr. Travis Jones, Fritz Haber Institute Through its work, the team identified a particular alloy, it possible for the team to study larger molecular systems

scientist and a researcher on the project. “There are a lot of iridium oxide mixed with niobium (Ir60Nb40Ox) that or more permutations of a given system, the investigators One major issue remains, though, and it is unlikely to go ideas out there, and many of them revolve around the idea behaves nearly as stably as pure iridium, but requires 40 are still limited in the number of atoms they can simulate away any time soon—humans have no influence over when that the absorption energy of different intermediates in the percent less of the precious metal. While the team knows during each run. Next-generation systems will help address the wind blows or the sun shines. This means that in order reaction is ideally balanced. That said, a deep understanding that much more work needs to be done to identify other some of these computational hurdles. At the same time, to use renewable energy on a global scale, researchers must is lacking, so we can’t just look at the periodic table and also devise methods for efficiently storing excess energy say iridium works for electrolysis because of how many generated during “boom” times so there is ample power electrons it has. We would love to know what it is about stores for moments when renewables are not keeping up iridium makes it work so well in this context.” with demand. Viewing fine-grained interactions Among the promising contenders for storing excess energy, hydrogen is among the most popular. In a process called through two different lenses water electrolysis, scientists can create chemical reactions to break down the molecular bonds of water molecules Gaining a more fundamental view into how molecules behave so they become their constituent parts—hydrogen and during electrolysis requires both world-class computing re- The solid-liquid interface at the iridium rich surface of an oxygen. The resulting hydrogen molecules must then be sources and high-end experimental facilities. Scientists need Ir-Nb mixed oxide water oxidation catalyst. Iridium atoms compressed into storage containers where they can be used to observe these chemical reactions at the atomic level, chart- are shown as blue, niobium as green, oxygen as red and as replacements for dirtier energy sources coming from ing the paths of electrons for individual atoms while watching hydrogen as white. © Travis Jones fossil fuels. several hundreds of these atoms interacting with one another. Moreover, they would like to study these phenomena under While researchers have made some progress identifying a variety of conditions, an approach that would be impos- materials that might be suitable as an electrocatalyst, it however, simulating ever larger systems will introduce a ways to do electrolysis at an industrial scale, there is still sible experimentally but can be done using computational feels confident that the two-pronged approach of spectro- new problem: his team will primarily be limited by system one major hurdle to clear—currently, iridium is the only modeling. Computational scientists then share these models scopic experiments and large-scale simulations is the ideal memory availability—an increasingly common challenge catalyst proven to remain both active and stable enough to with experimentalists, providing further insights into spec- method for moving the research forward. The results were for researchers at the forefront of computational science in facilitate water oxidation, a key step in water electrolysis. troscopic experiments that use focused light to illuminate published in ACS Appl. Mater. Interfaces. (https://doi. many research domains. Unfortunately, natural sources of iridium are vanishingly atomic-level behaviors in a chemical reaction. org/10.1021/acsami.0c12609) rare on the Earth’s surface. Without having the technol- Despite more technical hurdles to overcome, the team feels ogy to drill down to the Earth’s core or harvest iridium This is only the first point when HPC plays an import- Today’s supercomputers focused on confident that using HPC to accelerate experimental efforts from passing meteors, researchers must search for either ant role, though. “Simulating the electrons by solving will prove indispensable moving forward. While water an entirely new material or develop metal alloys—mixes Schrödinger’s equation is the first step. Here, we are basi- tomorrow’s reimagined energy grid electrolysis may not immediately become the dominant of two or more different metals that retain certain char- cally guessing what we have in the system by uncovering method for changing the world’s energy grid, Jones feels acteristics from their constituent materials—in order the atomic structure of the catalysts during experiments,” Like many researchers in his field, Jones indicated that being confident that hydrogen will prove to be a game-changer 19-1 · SPRING 2021 to scale up water electrolysis to the point where it can Jones said. “What the experiments can’t tell us, however, is able to scale up electrolysis to the point it can function on a in electrical energy storage and conversion. Whether sci- 19-1 · SPRING 2021 make a meaningful contribution to global energy storage how the reaction mechanism works at the atomic level, but global level still faces many challenges. But the promise of entists wind up finding a cheaper, more readily available requirements. the simulations can.” using clean hydrogen gas to spin turbines in power plants replacement for iridium or developing alloys that can use or developing new fuel cells that could supplant combus- iridium in sparing amounts, the promise of clean energy Recently, researchers from the Fritz Haber Institute in Ber- In essence, the first phase of modeling and experimental tion-based automotive engines has scientists focused on storage motivates the team to keep searching. lin have been using high-performance computing (HPC) work allows the researchers to get accurate, atomic-level finding ways to make the process more efficient. resources at the High-Performance Computing Center detail of water atoms on the surface of the catalyst. Once “Electrolytic water splitting links the electrical and chemi- INSIDE · NO Stuttgart (HLRS) to model the complex chemical reactions the researchers feel confident that they have an accurate Through a large, international effort, the code used by Jones cal sectors, and when we think about going climate-neutral INSIDE · NO that take place during electrolysis at a molecular level. The picture, they begin the second phase, which allows them to and his collaborators was recently modified to run on hybrid by 2050, that link becomes critical,” Jones said. “It is not team hopes that by using both cutting-edge experimental make slight modifications to inputs and model how the re- supercomputing architectures—machines that use graphics just energy storage that we have to worry about; it is also techniques and world-class supercomputers for simulation, action proceeds under different conditions. This rapid-fire processing units (GPUs) in addition to traditional CPUs. The sustainable chemical production. Green hydrogen could 15 14 they can gain a greater insight into what makes iridium so approach to modeling allows the researchers to observe team also began working on scaling its application to take help solve both of these issues.” eg 16 INSIDE · NO 19-1 · SPRING 2021 FEATURES SCIENCE though, researchers still encounter difficulties instudying encounter still difficulties researchers though, methods,Even withthe most experimental advanced subatomic worlds. more into insight gain to theallow atomic researchers and among innovations, other technical facilities, These tools. of sensitive experimental neutronsindividual at avariety shoot to allow that researchers facilities neutron research on technological advancements,building focused scientists level, at afundamental Inorder materials entists. study to one for of new became frontiers sci the largest research the system. through for on which the the are to move electrons line the refers energy white The states. quantum for itsvarious insuch amaterial trum spec aview provides of bottom the electronic energy image The sites inthe MnSicrystal. moveelectrons between place when takes that character lobes) and (blue spin arrows) (green/violet of orbital the fluctuation describes top image The I matter physics, and elementary particle physics particle physics, andmatter elementary condensed science, materials 100years, n the last on understandinganovel stateofmatterthatmayhave implications A cross-disciplinary, isworking internationalresearch consortium RESEARCHERS USE THE POWER OF HPC HUND METAL CHARACTERISTICS for advanced electronics anddatastorage. © Frank Lechermann Frank © TO ELUCIDATE - - comes to either conducting for or insulating against electric comes electric either to conducting for or against insulating when it of characteristics display avariety can Materials magnet. and shaping it into arefrigerator material amagnetic fying identi just than straight-forward less and are magnetism magnets lives, inourtheir daily nearly ubiquitous nature generally advance our understanding of materials’ atomic of materials’ our advance understanding generally andthe atomic properties, level inorder specific impart to at materials existing modify tists uncover new materials, Taken together, approaches these two have helped scien with computationally intensive modeling and simulation. research pair to experimental started many researchers computing the adventWith of (HPC), high-performance or environments. pressure only display novel temperature when properties inextreme or have amajor still on influence amaterial, can that ways with one another interact ticles inextremely short-lived can conditions—atomic under par interactions certain particle science classrooms or Despite on their classrooms homescience refrigerator. Growing up, most people play inelementary withmagnets Lechermann said. said. Lechermann physics Very intriguing pop up withthismaterial,” phases. magnetic and stranger even of transport, phases phases, youknown if that apply different you reach pressure, can and itisfor instance thismaterial, people“Many studied (https://doi.org/10.1038/s41467-020-16868-4). Communications publishedThe. team inNature itsresults relatively hidden of thismaterial’s behavior.aspects record to and confirm withexperimentalists partnered Lechermann Dr. Frank researcher of Hamburg University led by team aresearch In order MnSi, understand better to mysterious. somethingto metal subtler and more a run-of-the-mill like behaving from however, MnSishifts cold temperatures, When brought down manyto extremely to other metals. behave to seems similarlya compoundglance, at first that, monosilicide (MnSi), ismanganese Among these materials of conditions. underinteractions avariety The search todefineHundmetalphysics

- - -

complicated.” so it isamany-bodytrons, problem—that becomes very elections more are that withinteracting sophisticated, you the correlation understand to effects—interac want on your you run but ownthat theories machine, when can do We of simpler, course, demanding. really can, standard problem “The is said. Lechermann computing facilities,” incredible super to have to access itwas thismaterial, “For play role an essential indiscovery. simulations HPC for Hund’s metals, list of characteristics develop to trying amore still are comprehensivesearchers however, expensive, are sources and re that considering done Experiments at neutronperiments at neutron sources. involving both supercomputing simulations ex well as as To developed approach researchers atwo-pronged end, that works of how at the the material derstanding atomic level. un need have to first afundamental researchers though, order exploit to unique Hund’s characteristics, metals develop to ers and new electronics other technologies. In for present research possibilities metals stances—Hund’s superconductors lossless circum under as the right serve can that metals Much cuprates—copper-infused like at other metal moments. typical behavingstill as some above ordering magnetic of the while time, peratures and at tem properties magnetic transport shows unusual it is, that metal;” a“Hund’s as uncovered MnSiacts that researchers at cold temperature, state occurring naturally a conductor andas demonstrating ordered in its magnetism serving such common as metals, to characteristics typical exhibits manyMnSi isagood example—while the material technologies. for manufacturing cheaper, more alternatives effective hope discover to researchers and settings, pressure ture behave tempera under more materials radical how certain or of more understanding exotic agreater materials, With communication technologies. computers role andcentral other incommercializing tele semiconductors playing a with silicon-based advancement, of inanew era ushered subatomic of interactions materials zoom to inand look at ability the atomic Our and stances. environmental under magnets the circum right as and act reliably iron like conduct can electricity things that learned and error, humans have trial extensive Through charges. act in a specific manner. Depending on the material in on the manner. material Depending inaspecific act or any other number its electrons must often of properties, a conductor, as an insulator, serve be to magnetic, material motionselectrons’ For a and inagiven system. interactions on must focus researchers circumstances, under different behaviors change In order how understand to materials’ Fuzzy focusonelectron motion ------of technological advancement. tions on anatomic level for and help anew era set the stage interac they more help about illuminate material facilities, experimental and state-of-the-art resources both HPC and discovery, frontier by of that leveraging scientific true of this workpart is knowing sitson the their that research the most and exciting hiscollaborators, For Lechermann of conditions. thosetell would if behave the under same awider variety but early itistoo MnSi, to as characteristics Hund’s metal novel ironand compounds certain show many of the same conditions they most are Other silicides likely occur. to and underdemonstrate properties, which Hund’s metal more comprehensive of which materials understanding he andin developing interested were his collaborators a that indicated Lechermann computer,flagship JUWELS. current itscode able on efficiently to JSC’s install was the that ensured team working staff Further, withJSC approach. feelsthe confident team initstwo-pronged completedHaving investigation an initial into MnSi, isat the root of thisrestraint. character dependence and on spin the orbital electrons’ The actual only showed window. in amuch these properties narrower Hund’s metal these aspecific ing coherent MnSias paths, have relatively that windowsrelated metals large for form found theIn itsinvestigations, other team unlike that cor the inthe shaking environment.” acoherent of all chart path to because much more difficult is now playing and ishopping everyone it making around, the itislike band the you temperature, if raise stage—but apath see move to herence—meaning the to itcan toward level of co acertain has movement. Such aquasiparticle of this because but many affected are othering, particles ismov foris what particle itislike aquasiparticle—one people That follow etc. you’re apath, you making because other people inyour stand way, and behind you some “Yousaid. know some what happens, people aside, step about play, to Lechermann soyou go to the want to stage,” “Assume and you you the that see band go aconcert, to is alongparticles agiven path. cloud and itsattached particle of withother interactions the given anew to entity: flowthis correlated gives rise other. witheach Inasecond electrons step, interact cause of other the state electrons nearby, alsoaffects always be the means that motionbasically of electron anindividual which Moving electrons “quasiparticles,” inMnSibehave as time moving or another to morean easier difficult position. rotation (‘spin’), may have quantum and withacertain bital atomic or position, or acertain acertain off from starting electrons negativelyquestion, inanatomic charged system, Frontier life SCIENCE FEATURES SCIENCE eg ------

17 INSIDE · NO 19-1 · SPRING 2021 PROJECTS 18 INSIDE · NO 19-1 · SPRING 2021 Fraunhofer IAO will lead the project, which will operate operate which IAO will Fraunhofer the lead project, will and Labor, Housing. of Economic Affairs, Ministry berg the Baden-Württem 19million from Euro totaling grants SEQUOIA isone of through sixnew projects funded computing for industry. and demonstrateand the AI, potential benefits of quantum HPC facing challenges plications both that resolve current computing theshould results quantum to lead ap partners, inthe of context collaboration this research withindustry intelligence By (AI)methods. pursuing and artificial (HPC) computingcomputing high-performance withexisting on developing hybrid approaches quantum integrate that computing. focus for Additionally, will quantum HLRS improve of algorithms the performance to conduct research will HLRS partners, IAO)(Fraunhofer and five additional Engineering for Industrial Institute Working together withthe Fraunhofer Applications and Algorithms). Quantum Hybrid for Industrial Engineering ware nounced SEQUOIA (Soft project called these ambitious goals inanewly an aims helpto fulfill (HLRS) Stuttgart ter Computing Cen The High-Performance computing could offer. of the power quantum that advantage full take to necessary be will that infrastructure and IT algorithms, the software, isneeded develop to in industry. the At research time, same would computing, particularly benefit quantum most from whichis anurgent need kinds identify to of applications however, use, there into practical theoretical research from isonly the technology now moving Because percomputers. ways tointegrate themwithconventional systemsforhigh-performancecompu- F HLRS willhelpdevelop new software forquantumcomputersandinvestigateHLRS promises to offer advantages over even the fastest su over the even fastest promises offer to advantages kinds computing of problems, quantum or certain SEQUOIA PROJECT TO BRING QUANTUM COMPUTING TO INDUSTRYCOMPUTING TO ting and artificial intelligence. ting andartificial ------this goal.” problemsmental achieve to need beaddressed to will that funda investigate SEQUOIAsolutions will and expertise. the to alsohave necessary access thisnew technology from our across region community whohigh-tech could benefit inthe industrial researchers that we ensure that important computing however, itis systems, high-performance “As with HLRS’s isthe Resch. Michael case Director HLRS development in the field computing,” said of quantum computer. gence applications simply cannot onto be ported a quantum intelli computingtional and high-performance artificial designed and for algorithms tradi software means that inthe technology, difference however, fundamental This architectures. traditional on supercomputers than more running faster calculations accomplishment computers inwhich perform quantum supremacy,” an of “quantum demonstrate the possibility physics, they have begunto already ofprinciples quantum on Based computingkinds of systems. high-performance other from different they substantially that are the fact from computers results quantum The surrounding excitement New software forquantumcomputing a European center for research and center fora European research of Baden-Württemberg and the State computer make Stuttgart quantum will IBM first Germany’s to access “The town south just asmall ofgen, Stuttgart. puter, in early 2021 in Ehnin installed com quantum One QSystem of anIBM the and testing use center ismanaging The competence Baden-Württemberg.” Computing “Quantum Center petence in coordination withthe national Com

------tigating their potential improve to tigating applications. industrial place inthe of context take demonstrationwill projects inves developmentmore efficiently. and software This algorithm make them that and them run optimizing inways systems on quantum for intelligence simulationperform and artificial how include well will algorithms existing evaluating This computing inreal-world and scenarios. their systems usage tions for important are the of that programming quantum ques investigate will at HLRS researchers For thisreason, and linearalgebra. fieldsmachine learning, of optimization, monly encountered problems inthe hybrid applicationsinvestigate for com will at HLRS researchers Specifically, proaches involving computers. quantum of hybrid ap and avariety test evaluate, develop,computing will inindustry, HLRS at potentialLooking applications of quantum computingand platforms. classical computers quantum between interfaces software ficiently, develop to the however, isnecessary research approaches. In order maketo such workflows ef operate and other AI, more established computing with HPC, into hybrid workflows optimally that combine quantum them by integrating research the most impact for future them have to expect applications, researchers certain ning at computers run Although promise quantum befaster to Integrating quantumcomputing into hybridworkflows - -

Fraunhofer-Institut für Produktionstechnik und (IPA) fürProduktionstechnik Fraunhofer-Institut Automatisierung

Fraunhofer-Institut für Arbeitswirtschaft und Organisation (IAO) und Organisation fürArbeitswirtschaft Fraunhofer-Institut Fraunhofer-Institut für Angewandte Festkörperphysik (IAF) Festkörperphysik fürAngewandte Fraunhofer-Institut - - - - Universität Stuttgart, Höchstleistungsrechenzentrum Höchstleistungsrechenzentrum Stuttgart, Universität Universität Stuttgart, Institut für Architektur von fürArchitektur Institut Stuttgart, Universität outcome of thisproject.” computers be a valuable and will quantum power of HPC al-world applications combine that of the hybrid scenarios computing of quantum possibilities and demonstrating re “At of the understanding abetter the gaining time, same inSEQUOIA. activities Hoppe, HLRS’s who oversee will comparison approaches,” withmore Dennis said traditional in productivity increase to offerthat opportunities clear applications identify to computing of“We quantum expect and healthcare. finance, energy, engineering, logistics, robotics, computing manufacturing, such as for industries plans look to at the currently of relevance team quantum but the bedetermined, to still are investigate project will applications The exact the that the of success SEQUOIA. to beimportant will cooperation withindustry Close wLehrstuhl Eingebettete Systeme(EKUT) Eingebettete wLehrstuhl FZI Forschungszentrum Informatik (FZI) Informatik FZI Forschungszentrum of Economic Affairs, Labor, and Labor, Housing of Economic Affairs, Eberhard Karls Universität Tübingen, Tübingen, Universität Karls Eberhard Anwendungssystemen (US-IAAS) Anwendungssystemen Baden-Württemberg Ministry Ministry Baden-Württemberg quantum computinginindustry 01.01.2021 –31.12.2022 Stuttgart (US-HLRS) Stuttgart Potential applicationsof Funding amount: amount: Funding 6,162,226 Euro SEQUOIA Runtime: Partners: Funding: Funding:

cw - PROJECTS

19 INSIDE · NO 19-1 · SPRING 2021 PROJECTS 20 INSIDE · NO 19-1 · SPRING 2021 getting the Joule? per most science more are simply: users that centres ensure how do HPC Stated of of thisnew area HPC. the most aspects important and becomemanagement dynamic allocation resource will technologiesdifferent efficiently and Power effectively? The question applications is: How these will leverage their applications. in increases workloads performance inorder get to massive have design to moretists will dynamic applications and computational scien and FPGAs, GPUs like accelerators with CPUs mixtraditional that heterogenous architectures toward systems more HPC drives performance exascale As computing systems. (HPC) high-performance and use well-known parts of this Munich Software Stack. Stack. well-known of thisMunich parts Software are or DCDB implementations, PMIx SLURM, its various on and existing proven solutions. and Among MPI others, based stack workingare closely together asoftware build to Supercomputing of Munich and the Leibniz Centreversity The Technical and adapt hardware. existing to tems, Uni workdynamic, with highly sys heterogeneous integrated be to Ithas demands. have meet to somewill specific systems for such heterogeneous stack exascale A software on node-level. theseto isthe ever-growing complexity and heterogeneity Adding the across cores. of frequencies awide variety cause low-power limitations, operationcan of CPUs ufacturing man to of Due processors: the like variability issues ware behaviorphase of applications. And some hard basic are Some the like dynamic quite sophisticated, are challenges. some constraints under poses powersystems and energy application on heterogeneousOptimizing performance E Centre (LRZ) are workingtogethertocreate aproduction-ready software stack Future exascalehigh-performance computersrequire anewkindofsoftware The Technical University andtheLeibniz ofMunich(TUM) Supercomputing They might be a game-changer to the to we design way They beagame-changer might supercomputers knocking are at the door.xascale BOLSTER DYNAMIC FOR EXASCALE SOFTWARE that allows dynamic workloadstorunwithmaximumenergy efficiency Optimization ischallenging to enablelow-energy, high-performanceexascalesystems. on thebest-suitedhardware available inthesystem. DEEP-SEA AND REGALE HELP - - - - - sophistication inorder equip to supercomputing systems appropriate inthissystem and incorporate system, totype apro build define aimsto anopen architecture, REGALE systems. ofenization approaches optimized for power and energy and homog for standardization better the co-founders, one withTUMas of aninitiative, PowerStack, is the HPC stack foundations for generation the of next thissoftware of One the and DEEP-SEA.” REGALE era: in the exascale become they commonplace will as and dynamic systems, onof more deeper integrated thisstack heterogeneous, development projects for further research European two now, in Supercomputing we engaged are “Right Centre. of at the Munich Leibniz and Director University nical at the Systems Tech and Parallel Computer Architecture for Chair supercomputer Schulz, at the Martin LRZ”,says on the SuperMUC-NG running is already stack basic “The Schulz Martin Prof. EU projects addressEU thequestions

© Andreas Heddergott Muenchen TU / Andreas ©

- - - get the most out of supercomputers come.” to inorder management to power andan integrated energy workingare holistic, on approach and an open, scalable to TUMand LRZ Stack, the Munich With Software tem. plications the power needed and increases by the sys of the ap suboptimal to thisleads performance end, Inthe stack. workthat on of alllayers the software interfaces nents; we have of alack standardized “We little see integration ofsaid. the compo Schulz isdone today management site-specific,” inthe field research of“Most power and energy Stack. Software ware-Testbed) the for testbed the Munich at the LRZ, and Soft Architecture- Energy-, (Bavarian on BEAST and testing automationelaborate established being are approaches play will arole: Continuous Integration with Toyield development result. the greatest agile this end, can stack on efforts top of an software existing targeted where determine, to find beto ways will and REGALE of the upcoming inDEEP-SEA research Part themselves. methodsuling must that bedeveloped centres by HPC novel alsorequire But itwill codes. sched and elaborate of the parts complete of certain and insome rewrites cases, some require will refactoring, This more dynamic systems. and for ready only might static are codes today bepartially Many accelerators: existing leverage dynamic sothey can on codes existing more making Both focused projects are playwill amajor role inREGALE. the controlimplemented chain inDEEP-SEA, and used technologies the basic be While will stack. of the software capable of adapting at alllevels systems, exascale European deliver will the environment programming SEA for future and of execution complexutilization applications. DEEP- with the and resource for mechanisms policies effective Need forholisticapproach - - - - agreement numbers 955606 (DEEP-SEA) and 956560(REGALE) agreement numbers 955606 (DEEP-SEA) js - EuroHPC Programmes + involved Programmes under grant memberEuroHPC states 15 Mio Euro (DEEP-SEA) & 7,5 Mio Euro (REGALE) Euro &7,5Mio (DEEP-SEA) Euro 15 Mio TWT GmbH Science &Innovation GmbHScience TWT Technical Darmstadt University Leibniz SupercomputingLeibniz Centre Technical of Munich University DEEP-SEA DEEP-SEA Jülich Supercomputing Centre Fraunhofer Gesellschaft Fraunhofer German Partners: Partners: German Funding Source: Funding 2021 –2024 Runtime: Funding: & REGALE

PROJECTS

21 INSIDE · NO 19-1 · SPRING 2021 PROJECTS 22 INSIDE · NO 19-1 · SPRING 2021 itself, must be taken into account. To intoitself, must account. betaken cover a theor application from stemming workflow architectures or heterogeneousform HPC complexity, This inthe often infrastructures. and complex moreever powerful hardware by leveraging discovery scientific accelerate working innovative AItechniques, further to and HPC converges traditional RAISE CoE hardware. HPC future on efficiently utilizing focus special the continuously field emerging witha of AI, by and the cover funded EC the other 15CoEs of the additional third parties project jointwo and partners The 11full importance. societal of cases use along various exascale towards on developingfocused novel AI technologies are countries European 10different from and industry representing academia researchers RAISE, InCoE Jülich. Supercomputing at Forschungszentrum (JSC) Centre ofa grant roughly 5million and Euro isled by the Jülich Exa at and Engineering onSimulation-Based AI- “Research Computing of Center ExcellenceEuropean inExascale the form the to Commission European from (EC) funding received has sciences and natural ligence (AI),engineering, of CoE RAISE. cases use 1:Compute- andFig. data-driven S scale” (CoE RAISE). The project has been awarded been The projecthas RAISE). (CoE ­scale” high-performance computing (HPC), artificial intel computing artificial (HPC), high-performance ince the of beginning 2021,agroup in of experts CoE RAISE receivesCoE RAISE fundingfrom theEuropean Commission TOWARDS COMPUTING EXASCALE ADVANCING AI TECHNOLOGIESADVANCING loop 2:Full model optimization. Fig. - processing big data inefficient workflows. bigprocessing data on have astrong focus cases use the data-driven contrast, and components optimizing 2).In have recurrent Fig. (see and output workflows to advanced —are processes that workflowstraditional —comprised of simulation, input, emphasis on the developmentspecial where loops,“ of “full The project places a problemsmulti-scale scale. at large codes and workflows dealwithsolving that multi-physics, develops RAISE CoE HPC For the cases, compute-driven 1). Fig. (see have selected been cases use and data-driven of compute-driven applications, several broad spectrum

© CoE CoE © © CoE RAISE RAISE

dustry and academia. and academia. dustry stakeholdersand in AIamong from various the uptake of increase exascale to services as and software platforms, infrastructures, well as onsupport the and unique training as AIframework providing abusiness establish will RAISE CoE horizon, beyond of the funding self-sustainability reach to is, That communities. user various to providingness new services isclosely This linked the to centers. development of abusi and HPC academia, (SMEs), enterprises medium-sized and education for support, industry, and small practices, develop network European will RAISE’s and provide best CoE readiness. exascale and processing establish to data in exploreto increase ayet-unachieved performance prototypes, and HPC systems, annealing quantum tures, modulartechnologies, supercomputing such as architec The developments on novel performed are hardware methods. and evolutionaryby computation reinforcement learning driven techniques search architecture or neural learning, transfer networks, neural pre-trained techniques, tation augmen data deep auto-encoders, belief stacked networks, networks, residual units, recurrent gated such as gorithms withcomplementary AIal advanced intertwined are that workloads the needsaddresses of of HPC abroad range workflow 3isdeveloped. framework This shown inFig. aunique means that the according to This AIframework for enormous quantities of scale to ready data. structure infra software application and versatile inafunctional for universal begeneralized will relevant for cases the use AI methodologies sense. in a co-design tightly intertwined and application AI, domain developmentsThe HPC, are al - Forschungszentrum Jülich GmbH (DE), University of Iceland (IS), University Jülich GmbH(DE), Forschungszentrum Framework Programme H2020-INFRAEDI-2019-1 under grant H2020-INFRAEDI-2019-1 Programme Framework The Cyprus Institute (CY), RWTH Aachen University (DE), University Aachen RWTH (CY), Institute The Cyprus European Union’s Horizon 2020 – Research and Innovation Union’s 2020–Research European Horizon Barcelona Européen Supercomputing Conseil Center (ES), pour la Recherchepour Nucléaire Européen la (CH),Centre de Scientifique (FR), Bull SAS (FR), Rigas Tehniska (FR),Rigas (FR), Bull SAS Scientifique - - - - - Recherche et Avancée de Formation Calcul en Universitate (LV), Make VZW(BE),Universitate Flanders Fig. 3:DevelopmentFig. withinCoE of RAISE aunique AIframework Safran HE(FR),ParTec AG (DE), Safran Runtime (funding period): period): Runtime (funding Technische Universiteit agreement no. 951733 Partner institutions: Partner 4.97 million Euro Funding Source: Funding 2021 –2023 Delft (NL) Delft Funding: RAISE

.

PROJECTS © CoE RAISE

23 INSIDE · NO 19-1 · SPRING 2021 24 INSIDE · NO 19-1 · SPRING 2021 EVENTS hydrologic performance great simulations, measured provements. for ParFlow, modeling for example, alibrary im good performance reported The majority results. domains set of presented scientific their adiverse from participants Program Colloquium, 11 EA the EA During Booster. on JUWELS withajump-start researchers porting Workshop, Porting Booster JUWELS first at aiming sup (online). event the to the The colloquium preceding was 2021 Colloquium Access Early in January Booster JUWELS the organized staff Booster, JSC early of days JUWELS these during obtained and lessons learned measurements, performance In order results, present to scientific the first the to insights behavior of the system. important administrators system while alsoproviding JSC their stack, applications for and the software new hardware prepare to andallowed optimize teams the participating The program Program). (EA Program Access Early Booster of application and their teams codes withinthe JUWELS months for itspaces through several number by aselected put been already had itscommissioning, to thePrior system supercomputer. fastest Europe’s itbecame licly available, put online into When itcame and production. made pub qubit (bottom axis), the number of GPUs is doubled (top axis) to beat the otherwise exponential increase in run time. qubit (bottom axis),the inrun isdoubled number of increase GPUs exponential (top axis)to the beat otherwise into the on time spent computation nearly (blue, and constant) communication MPI additional (yellow, linearly). every With increasing split time, run number Shown of isthe qubits. normalized withanincreasing Weak for circuits results the simulation of scaling quantum I JUWELS BOOSTER EARLY DAYS HELP USERS MAKE THE MOST OF JSC’S GPU-ACCELERATED MODULE the officially Jülich Supercomputing was (JSC) Centre module Booster n November at 2020,the JUWELS Multi-day event focusesongivingusersadeeperintroduction

Normalized elapsed time [s] 10 120 140 160 180 20 40 60 80 0 G q u PU 3 2 b 2 i ts s M Compu G q PI u PU 3 4 b 3 i ts to the newest JUWELS module. to thenewest JUWELS s t e GPU q u 3 8 b © JUQCS-G Developers, presented in pre-print https://arxiv.org/pdf/2104.03293.pdf inpre-print presented Developers, © JUQCS-G 4 i ts s GPU q u 16 3 b 5 i ts s GPU q u 32 3 b 6 W i ts s ea - - - G q k sc u 64 PU 3 b 7

i time, thetime, application able deliver to was input important ofputing the capabilities A100 extensively. the At same for the their lower simulations, com utilizing precision reductions intimes-to-solution large saw community An application the physics theoretical particle from the new GPU. for specifically their algorithms and tune able analyze to which theythe were during Helmholtz Hackathon, GPU in of participated the their team preparation, part As cases. benchmarks test anderations for new scientific different improvements saw formation, rial gen over previous GPU anapplication modelingSOMA, the kinetics of nanomate tion abreeze. for thiscommunication-intensivemade scaling applica high-bandwidth networkBooster. The InfiniBand-based theto new A100Tensorcore inthe JUWELS used GPUs when architectures comparing previousincrease GPU good saw performance simulator JUQCS The quantum consistent over hundreds of nodes. node, inaBooster CPUs to speed-up comparing GPUs lor-made with up 26-foldto proved for GPUs successful, node. The new methods and into tai ParFlow built just improvements inaBooster when CPUs to comparing GPUs ts s a l i n GPU q 128 g u 3 b 8 i ts s G q 256 u PU 3 b 9 i ts s G q 512 u PU 4 b 0 i ts s GPU 1024 q u 4 b 1 i ts s G 2048 q u PU 4 b 2 i ts s

- - - - - during the lectures and additional hands-ontime. the lectures during on topics advanced focused days two the last general, more were days two the first While remainder of the days. followed by amounts generous of hands-ontime for the and itsprogram-ming, architecture theintroducing system online workshop inthe morning, consisted of lectures The 4-day topics. of awide scientific range covering teams Workshop, Porting Booster fifteen from withparticipants followed Colloquium was by JUWELS theThe first EA lence of the involved projects. excel Booster, the attesting sci-entific for JUWELS Call Scale computepants Large re-quested time GCS inthe first partici Program AllEA under still construction. was that thoughendeavours, even on thismeant asystem preparing new scientific for day first their challenging, the very from module they the could 75-petaFLOPS as use Program, EA they satisfied were withthe indicated Users early access. projects due the to their to research start andmance afaster or upcoming results anticipating were great good, perfor Colloquium either reported participants Most of the EA performance. inimproved resulting overall and software, hardware adoptionsticipants able were trigger to inthe systems’ par Program and EA staff JSC operation: theto system Kollet, https://doi.org/10.1007/s10596-021-10051-4 S. Hokkanen, © J. speedup. Relative axis: Right of numbers nodes. of and different GPUs CPUs comparing formenting GPUs, support imple Weak Booster after on JUWELS behavior of ParFlow scaling Performance (cells/s) 0 1 2 3 4 5 6 1e6 0 Relative performance 48 Epyc cores 4 Epyc cores +4 A100s 50 100 Weak scaling Nodes 150 200 250 0 5 10 15 20 25 30 - - - - - Relative performance (multiple) chine will enable. enable. chine will outcomes what seeing to new scientific the ma forward looking isalready of and theuse the machine, center staff showing are alike full interest inmaking long-time users Both new and got Booster off astrong to The start. JUWELS advice and providing professional support. throughoutavailable of the course the workshop, giving were that and NVIDIA JSC from additionalwell experts as at the as beginning assigned by the was mentors team each doneapplications. instruction Allof under thiswas expert on progress making their GPU-accelerated to way cussions, workedsions, teams on their codes and in-depth dis had the intensive hands-onses During andBooster itsGPUs. their on applications porting them JUWELS to get to started approachThis up quickly, speed to got new users allowing Booster resolution). (1-kilometre JUWELS on simulated withParFlow inSouth America, drainage Surface © J. Hokkanen, S. Kollet, B. Naz Kollet, B. S. Hokkanen, © J. ah - - - EVENTS

25 INSIDE · NO 19-1 · SPRING 2021 the and Science for Minister State underlines President Söder (left) Minister Right: at the QIC opening. Bavarian ValleyMunich beinthe future,” Quantum will Silicon Valley What istoday, inBavaria. We district innew dimensions withaquantum of for enable research the the future. research drive isthe warp “This Arts Bernd Silber © LRZ 26 INSIDE · NO 19-1 · SPRING 2021 EVENTS • • • Agenda: Hightech Bavarian contributionand animportant making supporting to the ambitious three the goals LRZispursuing the QIC, With new technology. but exciting withthisdisruptive associated and challenges computing quantum on community the hopesthe Bavarian and from scientists researchers well as as experts quantum Sibler, withLRZ Bernd led alively discussion Science, of Minister along President, with the Bavarian Minister the Bavarian Computing in Bavaria,” of Quantum Future Shoulders: The Heisenberg’s “On event, the virtual During Supercomputing at the (QIC) Centre Leibniz (LRZ). Centre ing end-user needs. end-user ing and com current and identifying technology emerging assessing forcommunity networking, collaboration, Exchange quantum and with the international local stack. software brid hy developing including systems, the necessary (HPC) computing high-performance acceleration into future and developmentResearch quantum integrating towards flexible manner. and inareliable, secure, scientists for research services computing and expand and quantum resources Establish I Markus Söder opened the new Quantum Integration Söder opened the new Quantum Markus President Minister 2021Bavaria’s n mid-March, the centre demonstrates itscommitmenttoarchitectural diversity With theinauguration ofLRZ’s quantumintegration centre, LRZ INTO STEPS THE QUANTUM AGE and anembrace ofemerging technologies. - - ment and Partnerships at LRZ. Schulz largely influenced Schulz at LRZ. ment and Partnerships Develop of Head Strategic Schulz, Laura said forward,” and direction and helpto stir the future era, quantum isthe time get into to of the this field,“This be part to the QIC. establish to strategy LRZ’squantum facilitated and workshops,for seminars initial early BQCXmeetings In addition ideasto opportunities. education and training providers for and andcollaborations, software hardware technologies,with emerging one another for research connected are and industry academia from researchers the communities. Through BQCX, quantum international astrong channel as withand for bothserve and the local Computing (BQCX) in 2019 to eXchange Quantum ian To LRZfounded withneeds, the Bavar fitofferings best powering of up 42qubits. to summer 2019and withthe provides comput researchers since on SuperMUC-NG and running installed been already simulator Intel’s had some back: quantum years started computing of intheefforts quantum area already had the thisintegration, opening of While the symbolizes QIC of the LRZ. Director explains Prof. Dieter Kranzlmüller, Agenda,” under Hightech the umbrella of the Bavarian Valley inthe Munich Quantum withour partners forward computingbundle them our and quantum drive activities Integration iswhere really Centre we LRZQuantum “The

- - - for Quantum Security and Data Science (BayQS), led by Science and Data Security for Quantum Competence Centre inthe Bavarian institutes Fraunhofer Munich and universities with the various two partnering and development LRZis side of things, on the software Supporting possible. the and research make other services computers at LRZhelp high-performance accelerate to among other will, things, QPU The resulting alogue QPUs. an but universal less and the QPUs powerful of digital ity get theessentially of best both worlds the flexibil inusing computing to allowing researchers units, digital-universal of withthat combines of the technology analogue circuits that (BMBF) of and Education Research Ministry Federal (DAQC), Computing” by theQuantum a project funded In another development, recent the “Digital-Analogue computer architectures. in itshigh-performance and put years itinto few inthe operation next unit (QPU) develop processing LRZwill Infineon, arobust quantum and chip Jülich, manufacturer Forschungszentrum Berlin, Technical of Universität Munich (TUM),Freie University Together IQM, topic. start-up withthe Finnish-German workshop training hosted just afirst on theLRZ staff at LRZand installed been up has 38qubits, to offering Machine (QLM), Learning The Quantum up Atos speed: have picked activities quantum the opening, QIC With development. early inits technology emerging animportant embracing and feels strategy, confidentthe LRZis that LRZquantum ereignisse/2021-04-30-Quantum-Computing/ ereignisse/2021-04-30-Quantum-Computing/ https://www.lrz.de/presse/ for inthis interview: QIC about steps concrete next talk Computing GroupQuantum LRZ’s Huber from and Dr. Stefan on: Dr. IapichinoRead Luigi The QuantumIntegration Centre isthenovel prototype ofapioneeringexperiment quantum technologieswithfundingfrom theHightechAgendaBavaria. It islocatedintheperfectplacewithLRZ asoneoftheworld’s “Munich istobecomeoneoftheleadinghotspotsinfield

for combiningquantumandsupercomputing.

most powerful computingcentres.” Bavarian Minister of Science Bernd Sibler Bernd of Minister Science Bavarian - - experts.” said Prof. Dieter Kranzlmüller, Director of the LRZ. of the Director LRZ. Dieter saidProf. Kranzlmüller, experts.” computing quantum for and future todays training offers programme our course Inaddition, thetems cloud. or through sys integrated inour HPC to researchers itavailable and making on site computingworking hardware on up setting quantum “As already we computing are centre, international a leading search efforts for future capability development. sv and sts capability for efforts future search its portfolio to and its re advance to and services resources Along the way, addto additional the is preparing QIC for and reliable of society. inbusiness the use technology computing for quantum and the foundationsprototypes project evaluates This inGarching. the AISEC Fraunhofer https://www.youtube.com/watch?v=-16tw-VKbtg online:watched be can event, live-streaming ofThe the recording one-hour

- - EVENTS

27 INSIDE · NO 19-1 · SPRING 2021 28 INSIDE · NO 19-1 · SPRING 2021 EVENTS and motivations. only the world capabilities around but our even personal us questionsincluding not about we interpret how accurately considered deception apsychological from perspective, models, simulation. Talks and scientific AI language also of and illusion deception deepfakes, instances such as on contemporary withpresentations focusing dialogue brought were into these studies from derived Insights level possible backstage.” on atechnical actually and what ishow frontstage deception and arise illusion both for understanding related cognition,to specifically model shared for participants an interest considering that on the contributions theater, which auseful focused offers of Prof. Dickhaut the “Many explained, As sets. theater and gardens, Renaissance-era the design of church altars, in including the past, examples from of such practices workshop at the SAS considered lectures For thisreason, andtainment manipulate to ways. others inmore malicious both for havedeception used been enter technology using andThroughout illusion, history, modern imitation, tional Science). of Philosophy Department of Computa HLRS (Leader, Kaminski and Andreas of Stuttgart), University Literatures, Dickhaut (Professor of Romance Kirsten HLRS), (Director, by Resch Michael organized was of Cologne, and the VDE, University of Tübingen, University of Stuttgart, versity the Uni which from The meeting, included researchers research. and computational media digital in the of context today’s fortechnology deception and both and inthe illusion past history, look to psychology, closely of at uses and pedagogy philosophy,sciences, sociology, humanities, art the digital computer studies, literary scholars from event gathered theHeld pandemic, online due the to ongoing COVID-19 on deception’s relationshipcus and imitation to adaptation. fo withaparticular of deception many perspectives, from looked at the (HLRS) history Computing Stuttgart Center workshopSimulation (SAS) at the High-Performance of and Art Science 16-17,2021,the sixth February On human cognition. deceiveto others or old bedeceived to isperhaps as as the potential unique threats, faces era digital our current that suggest might media formation insocial campaigns intelligence (AI)and disin growing of influence artificial In this multidisciplinary meeting,scholarsexchangedIn thismultidisciplinary perspectives onhow these SAS SAS WORKSHOP CONSIDER HISTORY OF IMITATION, I ception can take many forms. And although the many forms. ception take can self-delusion counterfeits, —de scams, llusions, related practices have emerged andchangedover time. ADAPTION, AND DECEPTION ------schenbild) provides that afoundation how for predicting perception of humans (Men withaspecific associated “Concepts and technologies indeception used often are assumptions of what itmeans behuman. to and cultural social changing to withrespect particularly contexts, logical of deception forms understand to sought intheir anthropo often of the topics, studies thiswideDespite diversity - - out not be new to at all.” turn in might some today actually new us to ways appears of forms such phenomena.contemporary Perhaps what of understanding abetter over but time, changed alsogain not how we onlythiness can these conceptions learn have examples of deception and questions trustwor related to historical studying “By Kaminski. remarked Andreas could ofa person bebrought confusion,” into astate cw - Royale at the Petit-Bourbon in Paris. at theRoyale Petit-Bourbon inParis. by the 11650 on February, Troupe performed first as dromède’’ ‘’An Corneille’s for 3of design Pierre Set Act illusion: Theatrical © Wikimedia Commons © Wikimedia - EVENTS

29 INSIDE · NO 19-1 · SPRING 2021 30 INSIDE · NO 19-1 · SPRING 2021 BRIEFS NEWS Last year, thisamounted about to Last 70applications. of simulation applied are projects that for at LRZ. locally computing merit theallocates scientific time and evaluates Committee The LRZSteering Foundation (DFG). Research and (BADW)emy Humanities and the of German Sciences Acad the Bavarian of representing the 15scientists LRZ, and consists years of a total two every is elected Committee The (KONWIHR). LRZSteering Computing inBavaria Performance Network Technicalpetence High Scientific who is also the spokespersongen-Nuremberg, for the Com of Universität Wellein Erlan the Friedrich-Alexander from isProf.position Dr. deputy Gerhard for the His third time. the to elected was Computing forCenter (IWR), Scientific allel working Computing” group at the Interdisciplinary who heads the “Par Bastian, committee meeting, steering the At last committee at of LRZ. the steering chairman as continues of HeidelbergProf. University Dr. Bastian Peter RE-ELECTED HEAD AS OF THE LRZ STEERING COMMITTEE PROF. DR. PETER BASTIAN

- - - - mate Protection and the Energy Sector. and Protection themate Energy of the Environment, Cli Ministry Baden-Württemberg by the The project isfunded heating. for building recycled could be sector heat produced byin which the waste IT and groups, could symbioses help and identify to citizen for stakeholders government, industry, politics, from provide will The aguideprojections. atlas digitalization to and data, numerical of relevanta geographic facts, overview provides that for Baden-Württemberg atlas” duce a“digital pro will the At conclusionsector. ENRICH of the project, incomputing and efficiency the centers IT energy well as and procurement as supplysustainable management, chain develop the project will lization, recommendations for ongoing drive digita will that megatrends of long-term Following astudy more sustainable. sector make the IT to opportunities and identify to Baden-Württemberg, of the across state of digitalization theinvestigate future acollaborative to lead effort will HLRS Rechenzentren), und inIT Ressourceneffizienz Nachhaltigkeit, (Energie, center for ENRICH coordinating anew project called As technologies. billion for euros quantum two which isproviding government, some the federal from ing Valley fund receive the will In addition, Munich Quantum years. beinvestingwill over 120million two euros the next To of Bavaria centers. State technology the Free thisend, and compete is to with international strategy quantum Valley in a national and is be to a pillar European Quantum the initiative, Munich aBavarian As cluster. technology of BAdW, aninstitute As the LRZsupports market. to this technologies computing andtum them quantum and bring ties for cooperation and in order exchange developto quan find astimulating will small environment and opportuni big and industry and private research, (MQV). Science, Valleythe jointly to year the Munich Quantum establish at thein aMemorandum of beginning of Understanding and bothciety, Munich pooled universities their expertise So Planck the Max the Gesellschaft, (BAdW), Fraunhofer and Humanities Academy of Sciences The Bavarian GUIDING SUSTAINABLE DIGITALIZATION MUNICH’SQUANTUM VALLEY IN BADEN-WÜRTTEMBERG

------search the Royal Opera at the Palace of Versailles. at the Palace the Royal Opera search tools re to digital inusing interested inFrance colleagues with underway are additional discussions Studies, Literary for Institute Together of Stuttgart’s with the University the to technology. historic without damage the need risk to the public itsdesign and function and scholars observe to make itpossible will for that machinery mation of the stage ani interactive alsoincorporates twin The digital century. have itmight looked as inthe 18th backstage, including the of illusion moving experience the through theater,can visitors Wearing 3D glasses, CAVE VR facility. HLRS’s in installation reality into an immersive virtual the data converted apoint the researchers erate cloud of the facility, gen to a3Dscanner using of the theater. After twin digital a have creating been Department Visualization of the HLRS members preservation, digital chinery. towards Inaneffort ishome the to Palace world’s ma oldest stage functioning The baroque inside theater Residential the Ludwigsburg TORIC LUDWIGSBURG PALACE THEATER HLRS CREATING DIGITAL OF HIS TWIN - - - - - policy and a clear roadmap for the future. and roadmap aclear forpolicy the future. inboth regions helppolicymakers will define acoordinated and researchers between interaction while the structured HPC, provide American will activities a boost Latin to The training requirements. and policy infrastructure, HPC for collaboration areas of inthe realms applications,specific deliverable beacooperation roadmap identifies that will project The main America. events in Europe and Latin HPC coincide to withmajorworkshops organized and trainings promote will through the of exchange practices best RISC2 and years. half for two Itruns and Chile. Rica, Colombia, Uruguay, Costa gentina, Mexico, Ar Brazil, from actors and theand HPC JSC) main INRIA, CINECA, BSC, stakeholders Atos, (including HPC together keyployment. eight European The projectbrings de applications both HPC and infrastructure surrounding communities and industrial the research eration between coop greater encourage well as as America rope and Latin Eu between supportto research the coordination of HPC anetwork 1,2021as January project started RISC2 The EU COORDINATING HPC RESEARCH RISC2: EU AND LATIN AMERICA

NEWS BRIEFS NEWS - - - -

31 INSIDE · NO 19-1 · SPRING 2021 32 INSIDE · NO 19-1 · SPRING 2021 BRIEFS NEWS efficient inthe world. supercomputer inEurope and one of the most energy- itthe making fastest second, per calculations quadrillion or 85 modulesBooster together capable are of 85 petaflops, and Cluster The JUWELS supercomputer,lar JUWELS. componentmodule, aGPU-accelerated modu of JSC’s Booster itsJUWELS finished installing JSC after over right takes Lippert Frankfurt. Computing at University Goethe of Supercomputing Modular the Chair as and Quantum alsoserves Lippert for 17years, predecessor organization position and andIn addition its havingled JSC his GCS to of LRZ. Director succeeds Prof. Dr. Dieter Kranzlmüller, Lippert Board of Directors. of the GCS the new Chairman is of JSC 8,2021,Prof. Dr. Dr. of Lippert Thomas April As PROF. DR. DR. LIPPERTTHOMAS THE BOARD OF DIRECTORS NAMED GCS CHAIRMAN OF

-

Computing GmbH, will run until 2025. until run Computing will GmbH, Quantum Berlin and the companies Infineon AG and Parity Universität the well Freie departments as as ious institute but alsothe Jülich Supercomputing withvar (JSC) Centre GmbHand involving by IQMnated Germany not only LRZ coordi The project, computingwhich quantum isbased. or cooling on device for the low temperatures a cryostat, LRZisprocuring Forthispurpose, there. their reliability computing at LRZand prove systems high-performance control work initially unitswill inconjunction withthe methods and control to electronics innovative These them. the well 5,20,and withinitially as thenresult as 54qubits, will processors quantum Step-by-step qubit. with each computers, whose computingquantum power increases controllableanalog, of withthat digital-universal systems The DAQC combine project aimsto of the technology Computing (DAQC) which by BMBF. isfunded project, Quantum of the Digital-Analog marked the start February and security techniques. techniques. and security encryption of current able being crack quickly to suspected computers already are Quantum computer systems. and IT concepts well existing as as on how secure to data, process to software also needs trustworthy The industry term. the computing over smallest the long and sustained units, upbe built on the qubits, them extremely unstable using and monitor computing so that these processors power can at present challenge reliably isto The greatest controlunits. processing on quantum the optimizing first in particular The joint andprotection. work testing focus research will and data and for security for well software initial as as concepts and solutions for technology reliable quantum develop the LRZwill Munich universities, thewell two as as (IIS), and for Circuits Integrated (IKS) Cognitive Systems for (AISEC), for AppliedInstitutes Security and Integrated Together at thetablished end of April. withthe Fraunhofer es (BayQS) was Science and Data Security for Quantum Competence Center by companies,be used the Bavarian development soon However, itcan that ensure to stage. at the isstill computing. of technology the This future pinned on quantum currently are and industry science hopes much of more faster—the even Processing data PROJECT DAQC: DIGITAL-ANALOG QUAN DEVELOP QUANTUM COMPUTING RELIABLY AND SECURELY TUM COMPUTING

- - - - tific curiosity, but alsobenefits mankind. curiosity, tific not show only thisresearch that scien satisfies COVID-19 Theother projectsaround consequences of change. climate floods and and explore to earthquakes, vehicles and aircraft, develop to and the universe, formation of new the Earth simulations helped the by understand to LRZsystems of supercomputers. For example, therequire performance fields more but increasingly also that research in research, volumes not that it clear only constantly swelling data are the work glance, 2020.Even 2018to at first from makes SuperMUC and its successor SuperMUC-NGsystems HPC projects computed 115research on the LRZdescribes from volume withexcellent the report Packed new results science, computing needs. urgent future address to and capacity expand the center’s inthe field activities of Global HLRS’s Science port Systems alsosup will The new resources resources. on hospitals’ stresses changing to —inresponse —or belifted necessary and where lockdowns interventions such as could become and anticipate better government when officials experts could help health on the newlyrun donated infrastructure, soon which will report,” “weather The daily the future. up weeks eight to into Germany units across intensive care schung) implement to amodel demand for for predicting Population fürBevölkerungsfor (Bundesinstitut Research for Institute Federal and the German HLRS tion between support to The acollabora new beused nodes will Fund. Computing Performance High of the AMDCOVID-19 part was andaccelerators, processors AMDInstinct™ EPYC™ The donation, pandemic. AMD containing SARS-CoV-2 the related to for research bededicated will that Stuttgart Computing Center the to High-Performance systems server donated 10 AMDhas Computing manufacturer hardware DONATION TO SUPPORT COVID-RELATED SUPERMUC RESULTS BOOK PUBLISHED RESEARCH AND URGENT COMPUTING ARRIVES AT HLRS - - - - losophy &Technology of Science of Computer Simulation. of Phi Department leader of the HLRS Kaminski, Andreas and Resch Michael Director alongSão Paulo, with HLRS Group of on Computational at the Humanities University de and Oliveira José Teixeira Study Coelho Netto of the IEA Barbosa Maciel Lucia are the partnership Leading tion inart. and of the visualiza use deception and art, intechnology ofproblems and adaptation the history of disinformation, of and the information the trustworthiness chine learning, computer use that simulation and ma e-cultures emerging on topics of related theto study focus will and the IEA of HLRS collaboration, areas Among the specific expertise. promote to ofof knowledge researchers the sharing and inthe exchange andtinuing engage education programs, hold develop joint conferences, joint international con plan develop to The organizations joint programs, research itspolitical implications,society, and e-cultures. emerging of transformation the related to digital institutes of the two on build theThe agreement complementary will strengths HLRS AND INSTITUTE OF ADVANCED SIGN COLLABORATION AGREEMENT STUDIES,BRAZIL, (IEA)

NEWS BRIEFS NEWS

- - - -

33 INSIDE · NO 19-1 · SPRING 2021 © European Space Agency

34 INSIDE · NO 19-1 · SPRING 2021 BRIEFS NEWS lish environmental akey technology. AIas and estab to users for future portable environmental data AIapplications on make to high-performance prerequisites the technical create will The Earth-AI-Platform concept. and withastrong network training an Earth-AI-Platform combines that the developmenta sophisticated strategy of by for using environmental systems data on HPC learning the machine application of large-scale facilitate aimsto ect proj Under leadership, the KI:STE JSC environmental data. intelligence led real-world the to first applications using developments rithmic of artificial the well capabilities as as Recent advancementsenvironmental inalgo challenges. solve to processes global whoscientists decode natural unique pose Earth to challenges datasets These derstood. not un encodesets that processes yet spatio-temporal fully heterogeneous consists data ofEnvironmental large, data AI STRATEGY FOR EARTH SYSTEM DATA PROJECT KI:STE - - - - - world and of the life. origin of the deepen to our understanding way in anexemplary theory,shows how and simulation experiment, interact developed hissimulations. since Theever further film computed already has on allLRZsupercomputers and has supercomputers, Professor of Springel tensivethe user GCS along-time in for As at the Astrophysics MPI in Garching. gether withProf. Dr. Volker minute (from 33:50), Springel to appearance, at abrief LRZalsomakes SuperMUC-NG the supercomputer documentary, role. Inthe arte decisive theoretical models simulations and numerical alsoplayed a new collaborations, experimental international extensive shot In addition out to jets. gigantic them into far space as and and fields magnetic turbulence mixed these gases the resulting and eventually at close the to of speed light, orbiting aroundblack of holes them gas the heated masses presents that the theory arte station the TV European from Adocumentary on it. and allcreatures make up the Earth out elements into space allthe heavy and disperses that at theplodes end asupernova itcreates of itsexistence, as ex star We When amassive allmade up are of stardust. budget of approximately2023 and atotal 7million Euro. 2021Juneto January 101017207 with a duration form under project is funded the agreementThe ID grant DICE authorization and authentication framework. frastructure cross-in afederated and B2ACCESS, preservation, term replication and for long- data aservice B2SAFE, storage, cloud and B2DROP, offers and trusted asecure structures withother and resources and platforms infra services onthe DICE integrating focused the leads activities JSC capacity. of storage petabytes withmore 50 than services management data of-the-art 14state- offering are countries 11European viders from way. persistent inaconsistent, 18pro and data process blocks access, and find, building store, to services generic providing for EOSC, infrastructure management and data The storage network aEuropean offers repositories. data and infrastructures, research computing centers, and data together anetwork of brings project that (DICE) for EOSC” Capacities Infrastructure inthe “Data isparticipating JSC of thiseffort, part As Portal. Cloud (EOSC) Science Open on the European offerings service aimed at increasing ects 2021,the Commission European launched projIn January LIFE FROM OUTER SPACE - FASCINATING DICE - DATA INFRASTRUCTURE VIDEO ONVIDEO CHANNEL ARTE TV CAPACITIES FOR EOSC

------Stuttgart on February 9,2021. on February Stuttgart online the Literaturhaus from broadcast The event was creativity. human and machine-based between differences andon on how the withAI, humans and perceive interact Wolfangeltion Eva by moderated journalist focused that joinedResch Kehlmann for anearly hour-long conversa Michael Director HLRS Following the reading, stories. and tell create to achievements:kind’s greatest the ability onewhich replicate to he of explored human AI’sability Kehlmann (Tyll, the World) Measuring in anessay read bestselling novelist Daniel “Zukunftsrede,” Stuttgart first Inthe how lives, close have we comedaily thisfuture? to present and inour becoming increasingly new capabilities a time and rapidly when AIare gaining machine learning considered be uniquely to and At quintessentially human. intelligence traditionally over activities take (AI)to cial of people the potential for have warned For years, artifi FIRSTSTUTTGART “ZUKUNFTSREDE” EXPLORES THE BORDERS BETWEEN HUMANS AND COMPUTERS

- - - ians-Universität (LMU), Director of and MCML LRZ. (LMU),Director ians-Universität at Ludwig-Maximil Mining and Systems Data of Database Chair offer,” explains Professor can Seidl, Thomas centers AI leading only that Germany’s astandard and guarantees technology represents state-of-the-art installed hardware additional “The 40AI it to petaflops. brings The system put been just into operation Ithas at LRZ. units (GPUs). of processing 64graphics withatotal NVIDIA nodes from on 8DGX-A100 AI)isbased for High-performance Cluster (shortened MCML’s for: UNIversal MUNICH.ai called the cluster Forthispurpose, onpower AI. for research basic nology and more jointly computing availabile making together now are knowledge(MCML) bringing and tech is why LRZand the Munich for Centre MachineLearning intelligence (AI)needs computingArtificial power. That Stuttgart. at the Literaturhaus onstage Resch WolfangelModerator Eva Michael withauthor Director and Daniel Kehlmann HLRS COMPUTING POWER FOR ARTIFICIAL INTELLIGENCE NEWS BRIEFS NEWS © Sebastian Wenzel Sebastian © - -

35 INSIDE · NO 19-1 · SPRING 2021 36 INSIDE · NO 19-1 · SPRING 2021 GCS INSIDE ways to improve to ways performance.” look to closely for staffs andharder centres’ for both users you it into evenIt makes account have take to and analyze. Today, on vectorization. trate you that have so many things namely, do to had when programming: to itcame concen more importantly, what “Perhaps quiteclear we said. itwas Brehm program,” to easy and itwas tive itsperformance, to Y-MP“The ahuge bandwidth, machine memory had rela his time at LRZ. amongfavorite the many devices he worked withduring Y-MP the Cray cites Brehm still supercomputer his as fact, onlywane acouple that Despite into of hiscareer. years processors of vector thebalance—Brehm usage watched aconsiderable had microprocessors, computetoday’s unlike knowledge that, processors—processors of vector withextensive out henologies. came of While hisstudies ofthe lines front of new and use tech making challenging group in2000.Indoing work, Brehm on thisessential sat volved inapplication becoming head of the support, APP in increasingly Brehm became his time at LRZ, During machines.” and inthe parallelism of maketo good vectorization use and thinkabout how algorithms, rethink some new things, inthedisruption field, sothe must invest community in a computing, and itisagain ators perhaps alsoquantum now “But withacceler that Isee working,” Brehm said. on the order of more amillion-fold than since Istarted have amajor inperformance—something seen “I increase proud of histime at LRZ. about the passionate but world remains of computing and LRZ at thetechnologies. Brehm end from retired of 2020, adapt multiple to generations computing of disruptive growing to withhiscolleagues applications inturn, and, computing edge of cutting technologies for their respective make the help set to best-possible hisskill users using use working 35years spend the next for the organization, proved decision That consequential—Brehmquite would technology. the HPC emerging work to aiming hisdegree, finishing with after organization (LRZ) and Centre ing wound up getting a position inthe Supercomput at the Leibniz time withstaff collaborating spent some had He computing hiseducation. vector during I HPC, RECENTLY RETIRED APPLICATION SUPPORT STAFF SPOTLIGHT: REFLECTINGON 35 YEARS OF minted PhD graduate who done had intominted graduate PhD research anewly Brehm was Dr. Matthias n the80s, late HPC DEVELOPMENTS PAST AND PRESENT GROUP LEADER REFLECTSON Dr. MatthiasBrehm, LRZ ------challenge existing users to adapt, invite new users into the invite new users adapt, to users existing challenge new generation of will technology true—each remains tres cen about HPC truth question the basic same have changed, Brehm pointed out while the that technologiesagain. in on technologies emerging interest and focus an increased corresponded with restrictions, and thermal due energy to The slowdown of conventional microprocessor technology, domains or institutions.” different does from a good job together of users bringing and thisiswhere have give to GCS incentivesways users, to you though, Inaddition, al ofalso the users. broad mass major point—we do not concentrate only on the top, but do to withone of and has that abig inEurope, part leading is “This he said. programs,” and training of lectures range we have abroad GCS, “In at the centres. three available and hardware of expertise the been diversity has program theBrehm, key component training successful of GCS’s For resources. HPC of good GCS use withmaking issues play to ues role the single researchers’ largest inaddressing contin decade over education the and last training support, Thankfully, Brehm emphasis feels on confident GCS’s that competitors.” over the years scientific of several get anadvantage they can do so, successfully outcome. researchers But if an uncertain spend to time and on efforts reluctant are isn’t clear, users environment something andgramming if understand, to TakenI/O. together, ahuge and complex itbecame pro then you and have caches, parallelization parallel different in withthe issues data latency larger have hierarchies, over time faded withmicroprocessors—youbut thishas and understand, to clear easy itwas processors, vector With where help that ses improve to identify code performance. who inthese kinds sointerested were researchers of analy there weren’t many increase, performance a significant generation each of microprocessor offered such“Because Brehm said. aboutI don’t the performance,’” care really about my work, say, but care scientific researchers ‘I “Many overcometo obstacles. some of the performance public domain and and vendor applications libraries helped those simulations. Additionally, run to they using were going onof “under what was the hood” of the machines thougheven aware less many becoming were increasingly intheir simulations increases get to major gan performance microprocessors sorapidly many waxed that be scientists the waned, Brehm processors pointed vector out as that

------over 35 years of service at LRZ and thirteen of those at LRZand years thirteen ofover service 35years But Brehm that looks those the are traits back on fondly their accelerate andto research. scientists engineers for partners diversified they mustfor become users; agile, centres of tomorrow only cannot provide computer alarge the HPC analytics, on data nologies, focus or the increased workflows, the computing promiseHPC of quantum tech intelligence in of artificial Whether usage itisthe increasing shifts. of promisingin these disruptive paradigm they developingensure are young become to talent experts centres to communities on HPC search and call they support, and the re staff centres’ HPC happening between dialogues - - road to exascale.” road exascale.” to mentioningisn’t even on the wealso,of are that course, and withone thatrience another. period, Itisanexciting work about and sharing expe eager are inPRACE partners centres and the European Also,the GCS three important. involved and isgood that and support and inuser training, “Today, hewell said. together” more we have people far and the that centres keep keepto working progressing, so hope just we continue “I forprogressing 35 years. the next the tools inplace has continue to confident GCS that Brehm feelsachieve intheir breakthroughs research, users or watching coffee breaks, during chat to colleagues hour-long meeting bike commutes back andLRZ, to forth of on taking his years When he reflects of GCS. a part being © LRZ INSIDE GCS INSIDE eg -

37 INSIDE · NO 19-1 · SPRING 2021 TRAININGS TRAININGS

TRAINING CALENDAR HPC COURSES AND TUTORIALS

Editor’s Note Due to the COVID-19 pandemic, the GCS centres provided many of their courses in the last year as online courses. Starting in autumn 2021, some of the courses may go back to the classrooms. These decisions are not yet finalized, so we have decided not to publish the training calendar as usual, as dates, locations, and plans may continue to change. For the most up-to-date information about GCS training courses, please visit: https://www.gauss-centre.eu/trainingsworkshops

For a complete and updated list of all GCS courses, please visit: https://www.gauss-centre.eu/training

The German HPC calendar (organized by the Gauss Allianz in cooperation with all German HPC centres) provides an extensive list of training all taking place German HPC centres. More information can be found at: https://hpc-calendar.gauss-allianz.de/

Further training courses and events can be found on GCS member sites: https://www.hlrs.de/training/ https://www.lrz.de/services/compute/courses/ https://www.fz-juelich.de/ias/jsc/events 19-1 · SPRING 2021 19-1 · SPRING 2021 INSIDE · NO INSIDE · NO

The Rühle Saal at HLRS in Stuttgart © HLRS 39 38 40 INSIDE · NO 19-1 · SPRING 2021 DESCRIPTIONS CENTRE fields of modeling and computer science. pro for access gain and industry. Users organizations, research academia, projects coming for from formance research supercomputing to access of the resources highest per Provision of supercomputer resources services. supercomputing, data and federated extreme-scale exploiting collaborative through formed infrastructures, isper research Our and society. science facing challenges exploreand to engineers some of the most complex grand module of Modular Cluster Supercomputer JSC’s “JUWELS”. The T jects across the science and engineering spectrum inthe spectrum and the engineering across science ­jects zentrum Jülich iscommitted enabling to scientistszentrum he Jülich Supercomputing at Forschungs (JSC) Centre JÜLICH SUPERCOMPUTING CENTRE FORSCHUNGSZENTRUM JÜLICH : JSC provides JSC - - ­ ° ° ° of are: JSC tasks Core effective usage of the supercomputer usage effective resources. ­ andand para algorithms methods on mathematical e.g. teams, and cross-sectional community-oriented ing simulation laboratories and data includ Implementation of support infrastructures strategic close c­ in students and education doctoral forHigher master companies. HPC together withleading groupssearch and by in technology, doing co-design e.g. fields by re selected sciences of physics and other natural Supercomputer-oriented and develop research operation with neighbouring universities. operation withneighbouring www.fz-juelich.de/jsc [email protected] 02 61- 61-64 +49 -24 Phone Germany 52425 Jülich Wilhelm-Johnen-Straße Prof. Dr. Dr. Lippert Thomas Jülich Forschungszentrum Jülich Supercomputing Centre (JSC) Contact llel performance tools, enabling the tools, llel performance © Forschungszentrum Jülich © Forschungszentrum ­ment in - - v Compute servers currentlyCompute servers operated by JSC A detailed description can be found on JSC‘s web pages: https://www.fz-juelich.de/ias/jsc/systems befound web pages: can on JSC‘s description A detailed System Modular Supercomputer Modular Modular Supercomputer Modular Modular Supercomputer Modular Fujitsu Cluster Fujitsu “DEEP-EST” Atos Cluster “JUWELS” (Prototype) “QPACE 3” “QPACE “JURECA” “JUSUF” 48 TByte memory TByte 48 (KNL) Phi Xeon Intel cores 43,008 nodes, 672 629 TByte memory TByte 629 GPUs A100 NVIDIA 3,744 Rome EPYC AMD cores 44,928 nodes 936 racks, 39 Booster (Atos): memory TByte 275 GPUs V100 NVIDIA 224 Skylake Intel cores 122,768 nodes 2,567 10 cells, (Atos): Cluster 157 TByte memory 157 TByte (KNL) Phi Xeon Intel cores 111,520 nodes1,640 Booster (Intel/Dell): memory TByte 443 GPUs A100 NVIDIA 768 Rome EPYC AMD cores 98,304 nodes, 768 (Atos): Cluster Data-Centric 32 TByte NVM TByte 32 + memory 7.1 TByte FPGAs Stratix10 16 Intel GPUs V100 16 NVIDIA 8260 Platinum Xeon Intel cores 768 16 nodes, Module: Analytics Data memory 6 TByte GPUs V100 NVIDIA 75 4215 Silver Xeon Intel cores 600 nodes, 75 Booster: NVM TByte 25.6 + memory TByte 9.6 6146 Gold Xeon Intel cores 1,200 nodes, 50 Cluster: 52 TByte memory TByte 52 GPUs V100 61 NVIDIA Rome EPYC AMD cores 26,240 nodes, 205 Size (TFlop/s) ­Performance Peak X X 12,266 75,020 18,515 4,996 1,789 1,372 549 170 45 Computing Capability Computing Capability and Capacity codes) (data analytics Computing Capability and Capacity parts) code (high-scalable Computing Capability and Capacity parts) code scalable (low-/medium- Computing Capacity Computing Capacity Computing Capability Purpose and Research Institutes Universities German and PRACE) (through European Industry Research Institutes and Universities, German and Cluster) Data-Centric the on (only European Programme Access Early through users interested and series EU-project “SEA” and “DEEP” the of Partners Project Brain Human and PRACE through Institutes Universities and Rewsearch German and European Lattice QCD Applications QCD Lattice SFB TR55, User CENTRE DESCRIPTIONS CENTRE ­Community

41 INSIDE · NO 19-1 · SPRING 2021 CENTRE DESCRIPTIONS CENTRE 42 INSIDE · NO 19-1 · SPRING 2021 for HPC code portability and scalability support the LRZ’ and scalability code portability for HPC on the national Top-notch and level. European specialists supercomputing top-tier livering and services resources de and HPDA facility HPC the LRZisaleadership-class nearMunich, inGarching campus on the research Located and HPDA inHPC Leadership humanities. and digital sciences life to and engineering astrophysics of disciplines–from and inabroad spectrum renowned to postdocs to students scientists— nity–from itsclients to throughout commu the scientific frastructure in computing providing to anoptimal IT centre dedicated the forefront of itsfield aworld-class performance high as SupercomputingSuperMUC Centre. NG at the Leibniz F Centre (Leibniz-Rechenzentrum, LRZ) has been at been LRZ)has (Leibniz-Rechenzentrum, Centre Supercomputing theor Leibniz nearly sixdecades, SUPERCOMPUTING CENTRE LEIBNIZ - - - ties as well as research organizations throughout Bavaria. organizations research well as ties as provider for service allMunich universi the LRZisthe IT In addition its role to national supercomputing as centre, science backbone for Bavarian IT theing LRZoffer. iscomplement intelligence and big data artificial learning, machine Arobust education for program HPC, systems. HPC computingtum AI on and integrating large-scale on technologies emerging Computing quan like focusing inthe field the forward of way The Future LRZisleading Computing at LRZ Future way.energy-efficient operations inthe most and run to ensure base broad user

© LRZ - - - Compute serverscurrentlyoperatedbyLRZ www.lrz.de [email protected] Contact A detailed description can befound https://doku.lrz.de/display/PUBLIC/Access+and+Overview+of+HPC+Systems can on LRZ’sweb description pages: A detailed System for SuperMUC-NG SuperMUC-NG for “SuperMUC-NG” Megware Slide SX Slide Megware Lenovo Nextscale Machine Lerning Lerning Machine DGX-1, DGX-1v DGX-1, Compute Cloud Cloud Compute “CooLMUC-2” “CoolMUC-3” “CoolMUC-3” ThinkSystem Intel/Lenovo Teramem IvyMUC Systems 80 00 +49 -8935831-80 Phone Germany nearMunich, 1,85748Garching Boltzmannstraße Prof. Dr. Dieter Kranzlmüller Supercomputing Centre (LRZ) Leibniz 64 Nvidia V100 Nvidia 64 (“Skylake”), Xeon Intel cores, 3,072 nodes, 64 8 x P100, 8xV100 8 xP100, Tesla, Nvidia 2 nodes, (“Broadwell”), 6 TByte RAM 6TByte (“Broadwell”), v4 E7-8890 Xeon Intel cores, 96 1 node, (“Ivy Bridge”) (“Ivy E5-2650 Xeon Intel 17.2 TByte, Omnipath 17.2 TByte, Landing, Knights cores, 9,472 nodes, 148 111 TByte, Omni-Path 100G Omni-Path 111 TByte, Skylake cores 8,192 nodes, 144 24.6 TByte, FDR 14 IB FDR TByte, 24.6 EP Haswell cores 10,752 nodes, 384 608 TByte, Omni-Path 100G Omni-Path TByte, 608 Skylake cores, 304,128 nodes, 6,336 Size (Mixed Precision) (Mixed (Mixed Precision) (Mixed (TFlop/s) ­Performance Peak X X 128, 8,000 26,300 1,130 600 447 459 13 13

Cloud Learning Machine Big Data Big Computing Capability Computing Capability Computing Capability computing Capability Computing Capability Purpose PRACE Research Institutes, and Universities German (Tier-2) Bavarian Universities (Tier-2) Bavarian Universities (Tier-2) Bavarian Universities (Tier-2) Bavarian Universities (Tier-2) Bavarian Universities PRACE (Tier-0 System) (Tier-0 PRACE research institutes, and universities German User ­Community CENTRE DESCRIPTIONS CENTRE

43 INSIDE · NO 19-1 · SPRING 2021 CENTRE DESCRIPTIONS CENTRE 44 INSIDE · NO 19-1 · SPRING 2021 SICOS BW GmbH, which assists small and medium-sized and small medium-sized which assists BW GmbH, SICOS alsohelped found to technologies. HLRS HPC of-the-art state- to access has always industry that ensures HLRS und Wirtschaft), fürWissenschaft stleistungsrechner apublic-privateThrough joint hww(Höch called venture Supercomputing for industry and applied science. withanemphasis onciplines, computational engineering dis many across scientific and industry users academic to intelligence and artificial visualization, analytics, data HPC, for and services provides infrastructure HLRS Stuttgart, of and the University withboth GCS affiliated institution computingnational center. high-performance Aresearch Computing Center Stuttgart. Hawk at the High-Performance T (HLRS) was established in 1996 as the first German German the first in1996as established was (HLRS) Computing Stuttgart Center he High-Performance HIGH-PERFORMANCE COMPUTING CENTER STUTTGART - - the labels. Blue Angel and EMAS under for environmental center responsibility iscertified The competencies Europe. across HPC andbuild integrate to efforts coordinating isalsocurrently HLRS Undertaking, the solutions. Joint support With of the EuroHPC practical global where challenges supercomputing provide can computing. develop Projects new technologies and address of key the address problems to future partners facing workingprojects, closely and withacademic industrial indozens research of funded participate scientists HLRS of supercomputing the future Guiding users. HPC industrial the unique addresses that needs program of atraining emie, Additionally, cofounded the HLRS Supercomputing-Akad technologies and HPC resources. inaccessing enterprises © Ben Derzian for HLRS for HLRS © Ben Derzian - Compute serverscurrentlyoperatedbyHLRS Contact A detailed description can be found on HLRS’ web pages: https://www.hlrs.de/systems web befound pages: can on HLRS’ description A detailed www.hlrs.de [email protected] System AMD COVID-19 System COVID-19 AMD Hawk GPU Extension GPU Hawk (Vulcan, Vulcan 2) Vulcan (Vulcan, HPE Apollo 9000 9000 Apollo HPE NEC SX-Aurora SX-Aurora NEC Cray CS-Storm Cray NEC Cluster Cluster NEC TSUBASA “Hawk” 8 72 69 72 +49 -711-6858 Phone Germany 19,70569 Stuttgart, Nobelstraße Resch M. Michael Hon.-Prof. Dr. h.c. Dr.Prof. Dr.-Ing. h.c. High-Performance Computing Center Stuttgart (HLRS), University of Stuttgart University (HLRS), Computing Center Stuttgart High-Performance 1.44 PB memory PB 1.44 cores 720,896 5,632 nodes A100 GPUs A100 NVIDIA 192 24 nodes Size 119 TB memory 119 TB 18736 cores nodes 662 2,048 GB memory GB 2,048 GPUs 64 8 nodes memory GB 3072 cores 512 nodes 64 GPUs MI50 AMD 80 nodes 10 AI performance AI (TFlop/s) ­Performance Peak 120,000 TF TF 120,000 26,000 TF 499.2 TF 499.2 1,012 TF 1,012 3. F T 137.6 530 TF 530 Computing Capability Purpose gence applications gence Intelli-Artificial Machine Learning, Computing Capacity Computing Vector Deep Learning Machine Learning Research COVID-19 User and industry and organizations research (PRACE) European and German and industry and organizations research (PRACE) European and German and industry and research institutions, universities, German and industry and research institutions, universities, German and industry and research institutions, universities, German COVID-19 research on focused researchers European and German ­Community CENTRE DESCRIPTIONS CENTRE

45 INSIDE · NO 19-1 · SPRING 2021 INNOVATIVES SUPERCOMPUTING IN DEUTSCHLAND N O 19-1 · SPRING 2021

InSiDE magazine (German: Innovatives Supercomputing in Deutschland) is the bi- www.gauss-centre.eu annual publication of the Gauss Centre for Supercomputing, showcasing recent highlights and scientific accomplishments from users at Germany’s three national supercomputing centres. GCS was founded in 2007 as a partnership between the High-Performance Com- puting Center Stuttgart, Jülich Supercomputing Centre, and the Leibniz Supercomputing Centre. It is jointly funded by the German Ministry of Education and Science (Bundes­ ministerium für Bildung und Forschung – BMBF) and the corresponding ministries of the three states of Baden-Württemberg, North Rhine-Westphalia, and Bavaria.

Cover image: Turbulence shaping the interstellar medium. The image shows a slice through the turbulent gas in the world’s highest-resolution simulation of turbulence published in Nature Astronomy. For more information, visit page 13. © Christoph Federrath

Funding for GCS HPC resources is provided by: