WSSP

26th Workshop on Sustained Simulation
2023-01-13 08:00 - 17:00 (Europe/London) | Baden-Württemberg
Agenda

Tuesday, 10 October 2017

9:00 – 9:15
Introduction
Michael Resch, HLRS, University of Stuttgart

9:15 – 9:45
Two-Year Experiences with Vector Supercomputer SX-ACE and Design Space Exploration of the Next Generation Vector System
Hiroaki Kobayashi, Cyberscience Center, Tohoku University
Abstract

In this talk, I will be presenting two-year experiences with our brand-new vector-parallel supercomputer SX-ACE. In particular, we will show you operation statistics, applications developed on SX-ACE, and some case study of program tuning to exploit its potential. In addition, I will describe the future plan for supercomputing resource installation and deployment at Tohoku University and make some discussion on the design space exploration of the future vector system.

9:45 – 10:15
SiVeGCS – The Future of German Supercomputing
Michael Resch, HLRS
Abstract

This talk will summarize the research and development activities of HLRS and will highlight future activities and directions

10:15 – 10:45
Break

10:45 – 11:15
JAMSTEC Next Scalar Supercomputer System
Ken’ichi Itakura, JAMSTEC
Abstract

11:15 – 11:45
OCTOPUS: a new supercomputing service of Osaka University
Susumu Date, Cybermedia Center, Osaka University
Abstract

11:45 – 12:15
The Brand-new Vector Supercomputer, Aurora
Shintaro Momose, NEC
Abstract

12:15 – 13:15
Lunch

13:15 – 13:45
A Multiple-layer Bypass Mechanism for Energy Efficient Computing
Ryusuke Egawa, Masayuki Sato, Ryoma Saito, Hiroaki Kobayashi, Cyberscience Center, Tohoku University
Abstract

13:45 – 14:15
Coupling Strategies for Multiphysics Simulations on Hierarchical Cartesian Meshes
Matthias Meinke, Michael Schlottke, Ansgar Niemöller, Institute of Aerodynamics, RWTH Aachen University
Abstract

14:15 – 14:45
Locally Linearized Euler Equations in Discontinuous Galerkin with Legendre Polynomials
H. Klimach, M. Gaida, S. Roller, Simulationstechnik & Wissenschaftliches Rechnen, Universität Siegen
Abstract

14:45 – 15:15
Unveiling Insight on Fluid Systems in a Diverse Environment using CFD
Manuel Hasert, Festo AG & Co. KG
Abstract

15:15 – 15:45
break

15:45 – 16:15
High-fidelity Simulation of Helicopter Phenomena HPC aspects in advanced engineering applications
Manuel Keßler, Institute for Aero and Gasdynamics University of Stuttgart
Abstract

16:15 – 16:45
Highly portable CFD solutions for heterogeneous computing on unstructured meshes
A.V. Gorobets, S.A.Soukov, Keldysh Institute of Applied Mathematics of RAS, Moscow, Russia
P.B. Bogdanov, Scientific Research Institute of System Development of RAS, Moscow, Russia
X. Alvarez, F.X.Trias, Heat and Mass Transfer Technological Center of UPC, Barcelona, Spain
Abstract

16:45 – 17:15
Numerical modelling of phase change processes in clouds – challenges and approaches
Martin Reitzle, Bernhard Weigand, Institute of Aerospace Thermodynamics, University of Stuttgart
Abstract

17:15 – 17:45
A dynamic load-balancing strategy for large scale CFD-applications
Philipp Offenhäuser, HLRS
Abstract

19:00 – 21:00
Dinner in Goldener Adler

Wednesday, 11 October 2017

9:00 – 9:30
API Extension and Resource Manager Integration for Malleable MPI Applications
Isaias Alberto Compres Urena, Institute of Informatics, Technical University of Munich
Abstract

9:30 – 10:00
Performance and Quality Analysis of Interpolation Methods for Coupling
N. Ebrahimi-Pour, S. Roller, Simulationstechnik & Wissenschaftliches Rechnen, Universität Siegen
Abstract

10:00 – 10:30
Towards Realizing a Dynamic and MPI Application-aware Interconnect with SDN
Keichi Takahashi, Cybermedia Center, Osaka University
Abstract

10:30 – 11:00
Break

11:00 – 11:30
FEniCS HPC: An automated predictive high-performance framework for multiphysics simulations
Niclas Jansson, Department of High Performance Computing and Visualization, School of Computer Science and Communication, KTH Royal Institute of Technology
Abstract

11:30 – 12:00
Automated derivation and parallel execution of finite difference models on CPUs, GPUs and Intel Xeon Phi processors using code generation techniques
Christian T. Jacobs, Satya P. Jammy, David J. Lusher, Neil D. Sandham, Engineering and the Environment at the University of Southampton
Abstract

12:00 – 12:30
Performance tuning of Ateles using Xevolver
Kazuhiko Komatsu, Cyberscience Center, Tohoku University
Abstract

12:30 – 13:30
Lunch

13:30 – 14:00
vTorque – Introducing virtualization capabilities to Torque
Nico Struckmann, HLRS
Abstract

14:00 -14:30
Optimised scheduling mechanisms for Virtual Machine deployment in Cloud infrastructures
Michael Gienger, HLRS
Abstract

14:30 – 15:00
To be defined
Christopher L. Barrett, Biocomplexity Institute, Virginia Tech
Abstract

15:00 – 15:30
Break

15:30 – 16:00
Software for agent based social simulation in the distributed HPC environments
Sergiy Gogolenko, HLRS
Abstract

16:00 – 16:30
A parallel solver for a linear system with a symmetric sparse matrix by one-dissection ordering
Mitsuo Yokokawa, Tomoki Nakano, Kobe University
Takeshi Fukaya, Hokkaido University
Yusaku Yamamoto, The University of Electro-Communications
Abstract

16:30 – 17:00
Vistle, a scalable visualization system for immersive virtual environments
Martin Aumüller, Uwe Wössner, HLRS
Abstract

17:00 – 17:30
Farewell

35th Workshop on Sustained Simulation Performance
2023-04-13 - 2023-04-14 | HLRS, Nobelstraße 19, Stuttgart, Baden-Württemberg, 70569, Germany
Agenda
All times are given in Central European Summer Time (CEST).
The registration is closed.

Thursday, April 13, 2022

10:00 – 10:15
Welcome & Introduction
Michael Resch, HLRS, University of Stuttgart

10:15 – 10:45
Lessons Learned from A Quantum-Annealing Assisted HPC R&D Project
Hiroaki Kobayashi, Tohoku University

10:45 – 11:15
NEC’s Quantum Computing Strategy, Technology, and Use Cases
Shintaro Momose, NEC Corporation

This presentation consists of two parts, discussing SX-Aurora TSUBASA vector supercomputer and introducing simulated annealer working on SX-Aurora TSUBASA called Aurora Vector Annealing. The first half of the presentation shows the vector architecture of SX-Aurora TSUBASA, especially its latest vector processors having the highest-level memory bandwidth. Sustained performance and power efficiency are also discussed, as well as NEC’s future plans and roadmap. The second half of the presentation shows NEC’s quantum computing strategies and their products to provide higher sustained performance in the annealing/optimization fields. NEC developed the Aurora Vector Annealing as a simulated annealer and has a strong business relationship with D-Wave providing a quantum annealer. NEC aims at solving various social issues by using the quantum/simulated annealing technologies and by developing a hybrid platform with supercomputer and quantum/simulated annealer to provide much higher sustained performance.

11:15 – 11:45
Towards Science DMZ based on Accelerated ONION using DTN
Susumu Date, Osaka University
The speaker introduces what is happening in Osaka University towards the promotion and advancement of Data-driven Scientific Research. In this talk, the experience of using DTN is first introduced and then a future direction of compute infrastructure composed of supercomputers( SQUID and OCTOPUS ) and data infrastructure is explained based on the experience.

11:45 – 13:15
Lunch

13:15 – 13:45
SPH-EXA: A Framework for Scalable, Flexible, and Extensible Astrophysical and Cosmological Simulations – Slides
Florina M. Ciorba, Department of Mathematics and Computer Science, University of Basel

SPH-EXA is a highly scalable and extensible simulation framework for astrophysical and cosmological simulations. It is codesigned by computational (astrophysicists and cosmologists) and computer scientists (high-performance computing) to achieve scientific advances in astrophysics, cosmology, and high-performance computing, for highly scalable simulations using Smoothed Particle Hydrodynamics. SPH-EXA includes highly optimized and parallelized hydrodynamics and gravity solvers. It supports new particle types and particle data fields that can be combined with custom-made, simulation-derived observable properties and in-situ data analysis. It requires minimal software dependencies, provides scalable parallelization and communication support, and portability with optimizations for recent CPUs and GPUs. This design relieves potential users from architectural specifics and performance concerns for performing and scaling up simulations with SPH-EXA. This talk will describe the SPH-EXA framework, its approach to domain decomposition, parallelization, gravity and hydrodynamics solvers, and their flexible use as pluggable components. A scalable initial conditions generator, test cases and simulations will also be presented. SPH-EXA is extensible with additional physical effects through the use of propagators, whereby the pluggable framework components are easily customized or implemented from scratch using the provided building blocks in an abstract, efficient, and scalable way.

13:45 – 14:15
Prediction and Mitigation of Aeroacoustic Noise on HPC Systems
Matthias Meinke, Ansgar Niemöller, Miro Gondrum, Zhe Yang, Wolfgang Schröder, Institute of Aerodynamics, RWTH Aachen University, Germany

14:15 – 14:45
Real-time flood inudndation simulation on SX-Aurora TSUBASA
Hiroyuki Takizawa, Yoichi Shimomura, Akihiro Musa, Yoshihiko Sato, Atuhiko Konja, Guoqing Cui, Rei Aoyagi, and Keichi Takahashi, Tohoku University
A real-time flood inundation simulation based on the Rainfall-Runoff Inundation (RRI) model is memory-intensive, and SX-Aurora TSUBASA is hence promising to efficiently execute the simulation in time due to high sustained memory bandwidth provided by vector processors. This talk will report that the real-time simulation has successfully been migrated and optimized for SX-Aurora TSUBASA. Assuming a shared computing system such as Supercomputer AOBA installed at Tohoku University, a resource demand estimation method is developed to minimize the amount of shared computing resources used for prediction in order to reduce the impact on other users sharing the system. The evaluation results show that SX-Aurora TSUBASA with only 32 cores can meet the real-time simulation requirement of simulating 7-hour flood inundation for the Tohoku region of Japan within 20 minutes, and also the resource demand estimation method can adaptively adjust the computing resource amount used for the real-time simulation.

14:45 – 15:15
Break

15:15 – 15:45
Competence Centres and Centres of Excellence within the European Strategy – Slides
Bastian Koller, HLRS, University of Stuttgart

15:45 – 16:15
Power capping in high performance computing – experiences and prospects
Pawel Czarnul, Adam Krzywaniak and Jerzy Proficz, Gdańsk University of TechnologyIn this work we investigate usage, limitations and prospects of power capping in high performance computing (HPC). Specifically, we discuss APIs for modern CPUs, GPUs and present, as an illustration, new unpublished data showing performance and energy characteristics for selected parallel OpenMP applications under power caps executed on a dual socket Intel Skylake-X system. These APIs can be used within algorithms: deriving configurations for which selected performance-energy goals (such as EDP, EDS) are optimized for non-trivial i.e. non-default power caps; and also allowing minimization of execution times under power caps. We discuss various factors of interest in the future in power capping aware HPC such as other metrics not considered so far, applicability and accuracy of measurement methods: using filters, hardware vs software methods, conditions and use cases for particular methods. We describe future works and areas including scenarios that can benefit from power capping in HPC.

16:15 – 16:45
Containerization for DLR HPC applications
Sabine Roller, Deutsches Zentrum für Luft- und Raumfahrt, Institut für Softwaremethoden zur Produkt-Virtualisierung

18:30
Dinner

Friday, April 14, 2023

09:00 – 09:45
Keynote – Sustaining Simulation Performance in the US Exascale Computing Project – Slides
Hartwig Anzt , University of Tennessee, Knoxville
The US Exascale Computing Project (ECP) has the goal to deliver a capable exascale computing ecosystem to provide breakthrough modeling and simulation solutions to address the most critical challenges in scientific discovery, energy assurance, economic competitiveness, and national security. This requires providing scientific computing applications with a software stack that allows them to perform on the leadership supercomputers. In this talk, we discuss the impact of the ECP hardware landscape on software design and how the Ginkgo math library responds to the ECP application requirements and helps to achieve the simulation performance goals.

09:45 – 10:15
HPC and AI at HLRS – Slides
Michael Resch, HLRS, University of Stuttgart

HLRS was created to support users with High-Performance Computing. Over the last years, however, Artificial Intelligence has become an important topic. In this talk we look into the changes that AI drives in computer simulation. We will explore the needs of AI users. Furthermore, we will have a first look at the needs of traditional computer simulation and t the potential of AI for such simulations.

10:15 – 11:00
Break

11:00 – 11:30
Towards Building a Digital Twin of Job Scheduling
Tatsuyoshi Ohmura, NEC Corporation

A job scheduler, which is the core component of the HPC system, has several parameters. Tuning these parameters can improve the efficiency of system operation, but this requires knowledge and experience and places a burden on
the system operator. To reduce this burden, we are studying the digital twin of the job scheduler. To realize the digital twin, we have developed a job scheduler simulator. We demonstrate examples of the use of the simulator.

11:30 – 12:00
Scalable Cluster Administration with LXC³ – Slides
Erich Focht, NEC Corporation
The LXC^3 Cluster Command and Control tools have evolved at NEC Germany since two decades, going through various changes to adapt to continuously changing requirements. The talk discusses the design choices of LXC^3-neo which runs as a pool of micro-services orchestrated by docker swarm, its scalability and limitations seen at customer sites. The most recent developments move the cluster management stack even closer to methods used in cloud systems management, simplifying node image handling and management network setup.

12:00 – 13:30
Lunch

13:30 – 14:00
A feasibility study of quantum annealing for the next-generation computing infrastructure – Slides
Kazuhiko Komatsu, Tohoku University
This presentation introduces a new project, feasibility study of quantum computing for the next-generation computing infrastructure, and shows an early evaluation of annealing machines.

14:00 – 14:30
Energy Efficiency and Renewable Energy for Distributed High-Performance Computing
Christoph Niethammer, HLRS, University of Stuttgart

14:30 – 15:00
A new framework for calibrating COVID-19 SEIR models with spatial-/time-varying coefficients using genetic and sliding window algorithms – Slides
Huan Zhou, HLRS, University of Stuttgart

A susceptible-exposed-infected-removed (SEIR) model assumes spatial-/time-varying coefficients to model the effect of non-pharmaceutical interventions (NPIs) on the regional and temporal distribution of COVID-19 disease epidemics. A significant challenge in using such models is their fast and accurate calibration to observed data from geo-referenced hospitalized data, i.e., efficient estimation of the spatial-/time-varying parameters. In this work, a new calibration framework is proposed towards optimizing the spatial-/time-varying parameters of SEIR model. We also devise a method for combing the overlapping sliding window technique (OSW) with a genetic algorithm (GA) calibration routine to automatically search the segmented parameter space. Parallelized GA is used to reduce the computational burden. Our framework abstracts the implementation complexity of the method away from the user. It provides high-level APIs for setting up a customized calibration system and consuming the optimized values of parameters. We evaluated the application of our method on the calibration of a spatial age-structured microsimulation model (CoSMic) using a single objective function that comprises observed COVID-19-related ICU demand. The results reflect the effectiveness of the proposed method towards estimating the parameters in a changing environment.

15:00
Open End

37th Workshop on Sustained Simulation Performance
2024-06-17 - 2024-06-18 | HLRS, Nobelstraße 19, Stuttgart, Baden-Württemberg, 70569, Germany
Agenda
All times are given in Central European Summer Time (CEST).

Monday, June 17th , 2024

10:00 – 10:15
Welcome & Introduction
Michael Resch, High-Performance Computing Center Stuttgart, University of Stuttgart

10:15 – 10:45
Operational experience of the latest-generation SX-Aurora TSUBASA system, AOBA-S
Hiroyuki Takizawa, Cyberscience Center, Tohoku University
Tohoku University Cyberscience Center started operation of the world’s largest SX-Aurora TSUBASA system named AOBA-S in August 2023. This talk reports the experience of operating the AOBA-S system while showing some performance evaluation results and discussions. Several important applications have already been optimized for AOBA-S, and the performance evaluation results clearly suggest the potential of the latest-generation vector engines adopted in AOBA-S. This talk also introduces our research projects that have recently started in collaboration with AOBA users.

10:45 – 11:15
Performance of a direct numerical simulation code for isothermal compressible turbulence on the SX-Aurora TSUBASA
Mitsuo Yokokawa, Kobe University
A direct numerical simulation code for compressible turbulent flows under isothermal conditions in a box with periodic boundary conditions was developed. A finite difference method is used for a discretization of the governing equations. In paticular, an eighth-order compact difference scheme was used for the covective terms and the Mattor’s method, which is a parallel solver for a linear system with tridiagonal matrix, was used to compute the first-order derivative of the covective terms. Performance of the DNS code was measured on the SX-Aurora TSUBASA.

11:15 – 11:45
Aim and Strategy of mdx2, IaaS-typed Computing Infrastructure
Susumu Date, Osaka University
The Cybermedia Center at Osaka University has installed an IaaS-typed Computing Infrastructure in March 2024 and will soon start the IaaS service. In this talk, the speaker will start with the background and show the aim and strategy of this system installation from now on as well as overview the structure of the system.

11:45 – 12:15
Improving Efficiency of Monte Carlo Method via Code Intrinsic framework
Qifeng Pan, High-Performance Computing Center Stuttgart, University of Stuttgart
The Monte Carlo (MC) method is widely used in many engineering fields, especially in uncertainty quantification, due to its robustness and simplicity. However, the existing execution pattern of MC suffers from low efficiency and scaling problems in high-performance computing (HPC). In this talk, the speaker will introduce the code intrinsic framework designed to tackle the efficiency problem of MC in HPC. The basic idea of the code intrinsic framework is to reduce the redundant calculations of MC and increase the code vectorization rate. Numerical results show that performance improvements can be achieved on various platforms, including the Intel and SX-Aurora TSUBASA machines.

12:15 – 13:15
Lunch Break

13:15 – 13:45
DEPO Meets Mechanics: A Case Study on Dynamic Power Capping for Energy Efficiency
Johannes Gebert, Jonathan Schäfer, High-Performance Computing Center Stuttgart, University of Stuttgart
Moore’s law is slowing down despite HPC centers’ increasing energy consumption. For cost and climate reasons, developing techniques for reducing energy usage while at least maintaining performance is sensible. DEPO, a software-agnostic, node-level, and dynamic power-capping approach by Krzywaniak, Czarnul, and Proficz (2022) promises to achieve these goals. We present their approach to real-world challenges based on an FEA. The Direct Tensor Computation (DTC) of Ralf Schneider and Johannes Gebert is run with DEPO to demonstrate the tools’ applicability. We explore different points in the input configuration space of the application and investigate the impact on energy consumption under power capping. Furthermore, we present and discuss different ways to continue and expand this research.

13:45 – 14:15
Connecting Software Methods and Data Driven Methods
Sabine Roller, German Aerospace Center, TU Dresden

14:15 – 14:45
Evaluating a Real-Time Lossy Array Compression Algorithm for Computer Simulations
Darjan Krijan, High-Performance Computing Center Stuttgart, University of Stuttgart
Computer Simulations that were previously regarded as CPU-bound become gradually memory-bound as the growth in memory bandwidth cannot keep up with the much higher advancements in raw computational power. This imbalance is quantified with a relative factor of approximately5.1 per decade since the 1990s, where a rise in memory bandwidth is met with a 5.1-times increase in relative computing power. In practical terms, comparing a NEC SX-4 from 1994 that operated at a balanced computational intensity of 0.125 FLOP/Byte with an Intel Ponte Vecchio accelerator from 2023 that operates at 15.9 FLOP/Byte shows a factor of 127 in the described imbalance. Mixed precision approaches that were traditionally used to speed up the throughput of calculations inside the CPU core on a cache/register level now provide speedup due to less demanded memory bandwidth. Approaches to compress arrays in a lossless or lossy manner to reduce memory bandwidth were implemented in LLNL’s zfp library, although it is not able to process the data in real-time. A similar approach targeting a real-time lossy array compression (RTLAC) algorithm is currently being evaluated for use in highly memory-bound computer simulations at HLRS.

14:45 – 15:15
Coffee Break

15:15 – 15:45
Direct Numerical Simulation of Turbulent Boundary Layers – On the Road to High Reynolds Numbers
Christoph Wenzel, Institute of Aerodynamics and Gas Dynamics, University of Stuttgart

15:45 – 16:15
Datenmanagement for HPC Workloads at Scale: Case Studies on Data Structure and Compression.
Gregror Weiß, High-Performance Computing Center Stuttgart, University of Stuttgart

16:15 – 16:45
Cloud resolving global weather simulation with the Model for Prediction Across Scales (MPAS) – A case study
Thomas Schwitalla, University of Hohenheim

16:45 – 17:15
The Quest for Sustained Performance on Heterogeneous Exascale Architectures with the Climate Model ICON
Panagiottis Adamidis, Deutsches Klimarechenzentrum Hamburg

18:30
Dinner

Tuesday, June 18, 2024

09:00 – 09:30
Challenges for HLRS ahead
Michael Resch, High-Performance Computing Center Stuttgart, University of Stuttgart
This talk summarizes the challenges that lay ahead for HLRS in the coming decade. It looks into the challenges that we face when changing technology from CPU to GPU. It will also address the issue of AI as a new user community in HPC.

09:30 – 10:00
Analyses of Turbomachinery and Heat Transfer Cases using HPC Systems
Matthias Meinke, Institute of Aerodynamics, RWTH Aachen University
This presentation will highlight computational methodologies and results from two industrial applications related to the field of turbomachinery and steel casting. Details of the computational methods featuring, adaptive mesh refinement, dynamic load balancing and multigrid methods will be presented together with the required HPC resources.

10:00 – 10:30
Algorithmic Differentiation of Geometric Modelling Libraries Aimed at Gradient-Based Shape Optimization
Mladen Banovic, German Aerospace Center, TU Dresden

10:30 – 11:00
Coffee Break

11:00 – 11:30
ML for Computational Science: Machine Learning Models to Accelerate Simulation Science on HPC
Makoto Takamoto, NEC Germany

11:30 – 12:00
A Constraint Partition Method for Combinatorial Optimization Problems
Kazuhiko Komatsu, Cyberscience Center, Tohoku University
In recent years, Ising machines have attracted much attention due to their potential in solving combinatorial optimization problems that are challenging for conventional computers. For optimization problems formulated into quadratic unconstrained binary optimization (QUBO) problems with constraints, known as constraint problems, an objective function and constraint function, along with penalty coefficients, are combined into a single Hamiltonian of a QUBO problem. However, when solving constraint problems, solution accuracy typically degrades by excessively large penalty coefficients avoiding constraint violations. As a result, minimizing the objective function becomes challenging. To solve this issue, the presentation introduces a method that partitions constraint functions and reduces penalty coefficient values. Performance evaluation using the traveling salesperson problem (TSP) with one-hot constraints illustrates that the proposed method enhances solution accuracy compared to conventional approaches.

12:00 – 12:30
An analyse of Kernels Performances when porting a CFD code to Nvidia GPUs using different Programming Models
Paul Saumet, High-Performance Computing Center Stuttgart, University of Stuttgart

12:30 – 13:30
Lunch

13:30 – 14:00
AI for HPC: Optimising Operations
Rishabh Saxena, High-Performance Computing Center Stuttgart, University of Stuttgart
In the last few years, Artificial Intelligence and Machine Learning have been dominant topics in the general field of computer science, and the scientific community as well. Since one of the core principles of machine learning-based algorithms requires a huge amount of data being processed on a large scale, it is expectant that high performance hardware would be needed for such computations. In this context, HPC can provide a suitable platform for various aspects of the ML pipeline, from data pre-processing to the deployment of models in production environment. In this talk, we will look at how HLRS is working towards optimizing its systems for AI and ML workloads, what are the aspects of ML pipelines that are relevant for HPC, how traditional HPC workloads, like simulations, can be integrated into ML pipelines, and what is the outlook for AI on HPC in the near future at HLRS.

14:00 – 14:30
Modelling of a Offshore Wind Park with OpenFOAM
Flavio Galeazzo, High-Performance Computing Center Stuttgart, University of Stuttgart

14:30 – 15:00
HANAMI: Advancing Supercomputing Collaboration Between Europe and Japan
Sophia Honisch, High-Performance Computing Center Stuttgart, University of Stuttgart
The HANAMI project, a strategic alliance between Europe and Japan, aims to innovate high-performance computing (HPC) applications for next-generation supercomputers across various scientific domains. This collaboration focuses on enhancing simulation capabilities in environmental sciences, biomedicine, and materials science. Aligned with the EuroHPC Joint Undertaking, HANAMI will port existing code, evaluate application performance on new architectures, and facilitate access to advanced supercomputing resources like Fugaku and EuroHPC systems.

15:00 – 15:45

Farewell

39th Workshop on Sustained Simulation Performance
2025-05-27 - 2025-05-28 | HLRS, Nobelstraße 19, Stuttgart, Baden-Württemberg, 70569, Germany
Agenda
All times are given in Central European Summer Time (CEST).

Tuesday, May 27th, 2025

09:15 – 09:30
Welcome & Introduction
Michael Resch, High-Performance Computing Center Stuttgart, University of Stuttgart

09:30 – 10:00
Research and user support activities at Tohoku University Cyberscience Center
Hiroyuki Takizawa,Cyberscience Center, Tohoku University
Tohoku University Cyberscience Center has been operating vector supercomputers and assisting users in fully utilizing their potential. This presentation will report on our recent efforts to help users optimize their code for our computing system, AOBA, which is powered by the latest generation of NEC SX-Aurora TSUBASA, the most powerful vector supercomputer. At both the system operation and research levels, we are continuously exploring effective methods to make the most of vector computing technologies. Performance evaluation results demonstrate that the SX-Aurora TSUBASA achieves high sustained performance for memory-intensive applications without requiring special programming models or languages.

10:00 – 10:30
The Future of HLRS
Michael Resch, High-Performance Computing Center Stuttgart, University of Stuttgart
In this talk we will look at the new developments in HPC and what impact they will have on HLRS. We will explore the role of AI for an HPC center and see how this will change services and operation of HLRS.

10:30 – 11:00
Musing on performance sustainability in the age of AI, superchips, APUs, increasing TCOs and NetZero impact
Sadaf Alam, Bristol Center of Supercomputing, University of Bristol
Supercomputing ecosystems have experienced considerable shifts since the early 2020 across applications and technology domains. HPC and supercomputing resources are increasingly being allocated to AI—a domain where the frequency of hardware changes and especially software stacks updates are considerably different compared to classic modelling and simulation HPC applications. Recently, the fastest reported HPL system on November 2024 Top500 list is based on an APU, or accelerated processor unit. This talks overviews Isambard-AI, a UK national AI RR or research resource comprising Nvidia Arm-GPU superchip called GH200, its software stack for AI and HPC, and its sustainability credentials using the Modular Data Centre (MDC) solution to manage Total Cost of Ownership (TCO) and NetZero impact.

11:00 – 11:30
Coffee Break

11:30 – 12:00
Future Computing at HLRS
Johannes Gebert, High-Performance Computing Center Stuttgart, University of Stuttgart
Increasing the computational capabilities enables larger and more detailed simulations, even after decades of development. While the high-performance computer’s (HPC) performance increases, the physical, hence technological limits are on the horizon. Specialized processors may focus on certain mathematical operations in widespread software stacks, but they also promise to accelerate the performance of potentially heterogeneous systems. Hardware improvements need software environments to allow for reasonably quick ports of existing software stacks to these new, accelerating devices.
At HLRS, we contribute to the HPC community by investigating computing devices’ capabilities, testing the software stack, and sharing our experiences and improvements on hardware architectures.
In this talk, we will give an overview of the future computing program at HLRS, goals, and strategy. We will outline current projects and present initial results.

12:00 – 12:30
Introduction and challenge of new supercomputing system towards the Open Science era
Susumu Date, University of Osaka
Osaka University has been working on the procurement of a supercomputing system after OCTOPUS. We will plan to complete the installation of it and start the operation in September 2025. In this talk the speaker introduce and explain the specification of the new supercomputing system as well as a challenge which we have faced for realizing supercomputing system in the Open Science era.

12:30 – 13:30
Lunch Break

13:30 – 14:00
First Results of GPU Porting Activities for Aeroacoustic Prediction
Methods
Matthias Meinke, Institute of Aerodynamics, RWTH Aachen University
tbd

14:00 – 14:30
From PDE to x in NeoFOAM: An overview of the NeoFOAM project
Gregor Olenik, TU München
NeoFOAM is a platform portable implementation of OpenFOAMs core algorithms and data structures. It aims to bring modern software development methods to existing simulation workflows, leveraging C++20 compliant code, being extensively unit-tested, hardware vendor agnostic, and extensible via plugins. This talk discusses the architecture and design choices behind NeoFOAM using neoIcoFoam as an illustrative example.

14:30 – 15:00
Accelerating the FlowSimulator: Speeding up the HPC codes used at DLR
Immo Huismann, DLR Dresden
This contribution summarizes activities performed at German Aerospace Center (DLR) to speed up the used high-performance computing (HPC) codes.
It starts out from the overarching goals that are to be solved via HPC, showcases the current distribution of HPC usage at DLR and, thereafter, demonstrates multiple case studies for analysing and accelerating the specific codes.
The list of case studies for performance analysis includes, but is not limited to, one of the CFD software “CFD by ONERA, DLR and Airbus” (CODA) and one of an industrial-grade aeroelastic toolchain.
Runtimes, profiles, and traces are shown, and current actions to address the underlying bottlenecks discussed.

15:00 – 15:30
Coffee Break

15:30 – 16:00
Sustainable research software for accessible high-performance computing
Michael Schlottke-Lakemper, High-Performance Scientific Computing, University of Augsburg
Modern supercomputers are becoming increasingly heterogeneous, incorporating hardware components from multiple vendors. At the same time, high-performance computing software development has grown more collaborative, often uniting research groups and institutions across different regions. Coupled with the constant addition of new features and performance optimizations, this raises critical questions about sustainability: How can we handle hardware complexity, coordinate diverse development teams, and maintain evolving research software within an academic environment while still writing energy-efficient, high-performance code?In this talk, we present some of our strategies for tackling these challenges through the Trixi Framework. We introduce Trixi.jl, a high-order numerical simulation environment for conservation laws built in Julia, along with its spin-off packages (TrixiShallowWater.jl, TrixiAtmo.jl) and its sister project, TrixiParticles.jl. We then discuss how we handle software architectures, automation, code reuse, and organizational practices to balance extensibility with accessible high performance on heterogeneous systems. Finally, we point out remaining open questions and outline plans for future development.

16:00 – 16:30
Investigating the Cerebras CS2 Chip: Mathematical and Software Engineering Goals, Methods and Initial Results
Jonathan Schäfer, High-Performance Computing Center Stuttgart, University of Stuttgart
In a world of ever-increasing computational demand and Moore’s law slowing down for conventional chips, interest in alternative hardware for specialized mathematical operations rises. An instance of an interesting new hardware concept is the Cerebras CS2 chip with around 850000 cores, which is therefore called a “supercomputer on a chip”. As part of the new Future Computing Group led by Johannes Gebert and in collaboration with the Computational Mathematics Group led by Prof. Hartwig Anzt at the Technical University of Munich, HLRS investigates the new chip from various angles, namely from a mathematical, hardware-oriented, software engineering, and user experience point of view. We present a roadmap for research as well as initial findings.

16:30 – 17:00
Reproducible and Performance-Optimized Environments for Large-Scale Machine Learning Applications
Felix Ruhnke, High-Performance Computing Center Stuttgart, University of Stuttgart
With the increasing size of machine learning models for solving complex problems, the demand for computational resources is rising significantly. This leads to a stronger convergence between the disciplines of machine learning and High-Performance Computing. The growing performance capabilities of modern machine learning models open up new application areas, including safety-critical domains such as medical technology. At the same time, the scientific community is increasingly drawing attention to a reproducibility crisis in the field of machine learning. The intersection of these three developments underscores the necessity of thoroughly investigating reproducible and performance-optimized environments for large-scale machine learning applications. In this work, various implementations of the Message Passing Interface in containerized environments were developed to examine the impact of different communication modes on the numerical reproducibility of results. For this purpose, benchmark tests were conducted to optimize polynomials of varying degrees on a single node with a varying number of Graphics Processing Units. The gradient aggregation algorithms Average and Adaptive Summation were employed. The results showed that variations in communication models using the Average algorithm had no impact on numerical reproducibility. In contrast, tests using the Adaptive Summation algorithm with varying communication modes resulted in non-reproducible outcomes.Furthermore, it was observed that, due to the non-associative nature of floating-point arithmetic operations and the varying execution order of computations during parallel training of machine learning models, deviations of over 7% in the number of iterations until convergence can occur. Additionally, the investigations revealed a highly sensitive convergence behavior of the models during training concerning configuration changes, emphasizing the need for careful selection of the computing environment and precise hyperparameter adjustment.

17:00 – 17:30
Development of dynamic resource assignment for effective system usage
Masatoshi Kawai , Tohoku University
Recently, energy efficiency as well as improving parallel performance of applications has become important for the operation and use of supercomputers. In this presentation, we will introduce a developing platform that provides dynamic resource assignments for improving parallel performance and energy consumption.

Wednesday, May 28, 2025

09:30 – 10:00
HammerHAI – The German AI Factory for Engineering, Global Challenges and Industry
Bastian Koller, High-Performance Computing Center Stuttgart, University of Stuttgart
This talk will provide insight into the German AI Factory HammerHAI, which resulted from a European Key Initiative and which started service operations in Q1/25

10:00 – 10:30
Leveraging Cloud-Native Supercomputing for AI Workflows
Dennis Hoppe, High-Performance Computing Center Stuttgart, University of Stuttgart
This talk explores the transformative potential of cloud-native supercomputing concepts and their impact on AI workflows. While powerful and GPU-rich, traditional High-Performance Computing systems present unique challenges when executing AI tasks. A clear paradigm shift is underway, moving from a system-centric to a user-centric approach, where usability, accessibility, and flexibility become key design criteria. Using the AI Factory HammerHAI as a concrete example, the presentation will demonstrate how HammerHAI aims to lower these barriers by integrating cloud-native concepts like containerisation and orchestration, thereby optimising supercomputing resources specifically for the practical needs of the AI community.

10:30 – 11:00
Coffee Break

11:00 – 11:30
New Brand “NEC BluStellar” Use Case – Research Information Infrastructure(RII)
Futoshi Tabata, NEC Japan
tbd

11:30 – 12:00
Introduction of Confidential Computing in HPC: Usage Model, Use Cases and Challenges
Kamil Tokmakov, NEC
HPC data centres accommodate users from various domains, each with varying security requirements. Sensitive data processing, such as for medical use cases or intellectual property protection, requires stricter security measures, including encryption across all data states: at-rest, in-motion and in-use. While parallel file systems found in HPC, such as GPFS and Lustre, already offer encryption of data at-rest and in-motion, encryption keys and sensitive data are not yet fully protected in memory. Confidential computing addresses such protection of data in-use by performing computations in the trusted execution environments, where data and code are secured at the hardware level. This talk introduces confidential computing in the context of HPC, covering its use cases and challenges.

12:00 – 12:30
NEC SX-Aurora TSUBASA – Our best friend for a long time
Christoph Wenzel, Institut für Aero- und Gasdynamik (IAG), University of Stuttgart
For a long time, the NEC SX-Aurora TSUBASA has been a valuable addition to the HPE Apollo (Hawk) system at HLRS. Even though its size was not sufficient for large-scale production runs for the fundamental research on turbulent boundary layers with direct numerical simulation (DNS), Aurora has still played a central role in our research pipeline. In this talk, our group’s experience working with the SX-Aurora platform will be presented, highlighting its integration into our workflows. Additionally, a performance study of our in-house DNS code NS3D on Aurora will be presented, providing insights into computational efficiency achieved on Aurora.

12:30 – 13:30
Lunch Break

13:30 – 14:00
Super-resolution Reconstruction of Three-dimensional Vorticity Fields by Latent Diffusion Models
Mitsuo Yokokawa, Tohoku University
tbd

14:00 – 14:30
Enabling AMD APU Support for CalculiX
CrunchiX: A Port to the Instinct MI300A
Benjamin Schnabel, High-Performance Computing Center Stuttgart, University of Stuttgart
CalculiX CrunchiX is an open-source finite-element analysis (FEA) application featuring both implicit and explicit solvers, written in C, C++ and Fortran 77 and maintained by Guido Dhondt since 1998. Its flexible architecture allows it to interface with a variety of sparse linear solvers-such as an iterative Cholesky solver, SPOOLES, or intel oneMKL PARDISO-to solve structural mechanics problems. Recently, heterogeneous computing with GPUs has emerged as a key strategy to accelerate the solution of linear systems of equations in scientific applications. While CalculiX already supports NVIDIA GPUs through the PaStiX solver and the CUDA library, there is currently no counterpart for AMD architectures. In this work, we describe the design, implementation, and optimization of a new backend for CalculiX that targets the AMD Instinct MI300A APUs.
Our implementation is deployed and benchmarked on HLRS’s newest flagship supercomputer HPE Cray EX4000 system (Hunter).

14:30 – 15:00
Power and Performance
Nico Formanek, High-Performance Computing Center Stuttgart, University of Stuttgart
The biggest driver of computing performance are hardware improvements. Even though the relative energy efficiency (e.g. FLOPS/watt) is improving at an almost exponential rate this does not translate in any reduction in absolute energy consumption. Rebound effects like this have been studied for centuries in economics starting from Jevons (1865) but there is still no consensus if economic growth can be decoupled from absolute energy consumption. Here I will argue that we face a similar problem in computing, i.e. that performance cannot be decoupled from absolute energy input. This in turn casts doubt on the feasibility of sustainability efforts like the GREENER (2023) principles. I will close by evaluating several accounts of why we still could want to improve performance even in the light of such hard tradeoffs.

15:00 – 15:30
Coffee Break

15:30 – 16:00
Towards scientific foundation models
Steffen Staab, University of Stuttgart
Foundation models are machine-learned models that are trained on broad data at scale and are adaptable to a wide range of downstream tasks. Foundation models have been used successfully for question answering and text generation (ChatGPT), image understanding (Clip, VIT), or image generation. Recently, the basic idea underlying foundation models been considered for learning scientific foundation models that capture expectations about partial differential equations. Existing scientific foundation models have still been very much limited wrt. the type of PDEs or differential operators . In this talk, I present some of our recent work on paving the way towards scientific foundation models that aims at making them more robust and better generalisable.

16:00 – 16:30
Quantum Computing Status -Technologies, Benchmarks and Use Cases in Academic and Industry Fields
Shintaro Momose, NEC Japan
tbd

16:30 – 16:45
Farewell
Michael Resch, High-Performance Computing Center Stuttgart, University of Stuttgart
