WSSP

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

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

33rd Workshop on Sustained Simulation
2022-05-23 - 2022-05-24 | HLRS, Nobelstraße 19, Stuttgart, Baden-Württemberg, 70569, Germany
Agenda
All times are given in Central European Summer Time (CEST). An additional live stream will be available. Please contact Mr. Johannes Gebert (gebert@hlrs.de) if you would like to participate.

Monday, May 23rd, 2022

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

10:15 – 10:45
Reaggregation of Disaggregation:
A Smart Approach to the Optimized Architecture and Platform Design
Hiroaki Kobayashi, Tohoku University

10:45 – 11:15
Combinatorial Clustering for a Material Informatics Application using Aurora Vector Annealing
Kazuhiko Komatsu, Tohoku University
Abstract

Due to the recent advancement of data science, such as machine learning and big-data analysis, the approach using data science techniques has attracted attention even to develop new materials, called material informatics. In material informatics, clustering is one of the essential data processing techniques to understand thermophysical properties. To improve clustering accuracy, this presentation gives an Ising-based clustering method using aurora annealing machine for a material informatics application.

11:15 – 11:45
HPC Refactoring Catalog : Updates
Ryusuke Egawa, Tokyo Denki University
Abstract

Aiming to support smooth code migration and optimization among HPC systems, HPC Refactoring, a database of system-aware code optimization patterns, was designed in 2015. This talk introduces an overview and updates/future plans for improving the HPC refactoring catalog.

11:45 – 13:15
Lunch

13:15 – 13:45
Concept of a File Tracing Mechanism for Research Data Management in High Performance Computing System
Yuta Namiki, Takeo Hosomi, AKihiro Yamashita, Susumu Date, Joint Research Laboratory for Integrated Infrastructure of High Performance Computing and Data Analysis, Cybermedia Center, Osaka University
Abstract

Research data management has come to take a role of great importance for reproducible and reusable research. In the recent academic research scene, researchers and scientists leverage HPC systems as a base for processing and analyzing a large amount of data through numerical analysis and computer simulations. Despite that, however, the data produced and analyzed on HPC systems are not managed due to the lack of a functionality that allows us to understand how data is produced and processed in the system. From the perspective, by focusing on the lineage of data, which shows the origins and history of data for assuring that the data is produced on HPC systems. we have prototyped a mechanism that generates the lineage by tracing file access operations of user programs in the kernel. In this presentation, we report the interim result we have achieved so far with future issues.

13:45 – 14:15
Mitigation of Aeroacoustic Noise based on Simulations on HPC Systems
Matthias Meinke, Ansgar Niemoeller, Miro Gondrum, Moritz Waldmann, and Wolfgang Schroeder, AIA, RWTH Aachen
Abstract

The numerical simulation of aeroacoustic sound is important for an improved understanding of noise generation mechanisms and the design of noise mitigation strategies. In this paper, the performance of two direct coupled two-step CFD/CAA methods implemented on HPC hardware are discussed. For the flow field either a finite-volume method for the solution of the Navier-Stokes equations or a lattice Boltzmann method is coupled to a discontinuous Galerkin method for the solution of the acoustic pertubation equations. The coupling takes advantage of a joint Cartesian mesh allowing for the exchange of the acoustic sources without MPI communication. An immersed boundary treatment of the acoustic scatttering from solid bodies by a novel solid wall formulation is implemented and validated in the DG method. Results for the case of a spinning vortex pair and the low Reynolds number unsteady flow around a circular cylinder show that a solution with comparable accuracy is obtained for the two direct hybrid methods when using identical mesh resolution. Finally, results of a large scale application, i.e., the noise prediction for a nose landing gear are presented.

14:15 – 14:45
Management of data flows between Cloud, HPC and IoT/Edge
Kamil Tokamov, HLRS, University of Stuttgart
Abstract

The components of heterogeneous applications are deployed across various execution platforms and utilise the capabilities of the platforms. As such, one component can utilise HPC resources for better performance in batch computation, while another – Cloud resources, for better scalability and elasticity. Furthermore, this is also a possibility for processing on Edge devices. The usage of such a hybrid setup, where dependent components of the applications are deployed across various platforms, might require flexible and adaptive data transfers from one platform to another. This work presents a data management framework, based on the Apache NiFi dataflow management system and developed in the scope of the SODALITE EU project. This framework enables scalable data transfer between any of GridFTP (a file transfer protocol dominant in HPC), HTTP, S3-compatible and data streaming (such as MQTT) endpoints.

14:45 – 15:15
Break

15:15 – 15:45

Sabine Roller, DLR (Deutsches Zentrum fÃ¼r Luft- und Raumfahrt e.V.)
Abstract

The abstract will be provided soon.

15:45 – 16:15
Integration of parallel HDF5 I/O in a large scale computational fluid dynamics solver
Tobias Gibis, University of Stuttgart
Abstract

As the number of cores in massively parallel computer systems increases, I/O strategies must be adapted as to not present bottlenecks. The “read and write one file per core” strategy, while efficient for smaller earlier computational architectures, leads to an unmanageable amount of files and is poorly suited for Lustre filesystems. With the introduction of Hawk at HLRS, an urgent need had arisen to develop a new framework based on MPI-I/O in which all cores write simultaneously to a common file. To this end, a new I/O framework based on HDF5 was implemented in the IAG in-house CFD code NS3D. The associated talk will discuss selected design decisions and challenges encountered, escpecially regarding adequate I/O performance.

16:15 – 16:45
High Performance Object-Oriented Data Processing Workflows for Researchers and Scientists
Jason Appelbaum , University of Stuttgart
Abstract

As computing capacity increases, datasets generated by HPC applications grow in size as well. The researchers and scientists who use such datasets for their work require scalability and efficiency in their data-processing workflows, but still prioritize utility and practicality. Typically such researchers are self-taught, intermediate-level programmers working collaboratively with others, in which case object-oriented languages such as python offer a greatly reduced barrier to entry and improved code maintainability within their research groups. Research progress is accelerated by flexible, easy access to large datasets for comparison and testing. The merits of a high-performance yet flexible approach utilizing HDF5 and MPI, wrapped by h5py and mpi4py in python, will be discussed. Examples taking advantage of collective I/O and parallel processing for the analysis of direct numerical simulation datasets will be presented, along with performance metrics. Additionally, techniques for ‘big data’ visualization using Paraview, HDF5 and XDMF will be showcased.

18:30
Dinner (Registration closed)

Tuesday, May 24th, 2022

09:00 – 09:45
Keynote
Jack Dongarra , University of Tennessee

09:45 – 10:15
A ML-Based Approach to Automatic Selection of Compiler and its Option Flags
Hiroyuki Takizawa, Tohoku University
Abstract

Today, one HPC platform could have multiple compilers, each of which provides a lot of option flags. Those compilers have different optimization capabilities, and target at even different processors on a heterogeneous computing system such as NEC SX-Aurora TSUBASA. Thus, it could be challenging to select an appropriate build configuration such as the best available compiler and its option flags for each application code. In this talk, I will introduce our ongoting work to use machine learning for predicting an appropriate build configuration from performance counter values.

10:15 – 11:00
Break

11:00 – 11:30
Speeding up k-nearest neighbors search with space-filling curve.
Masashi Kotera, Sourav Saha, Takuya Araki, NEC Corporation
Abstract

k-nearest neighbors search (k-NN) is a useful algorithm that can be used for classification and regression, but naive k-NN is slow because it requires scanning all the training data at prediction time. There is a method of solving this problem for low dimensional data, such as dividing the search space Like kd-tree. However, algorithms using tree structures are difficult to vectorize because they require recursion. In this talk, we talk about implementing the speed-up method for k-NN using z-curve, a kind of space-filling curve; the calculation of z-curve is easy to vectorize, and z-curve enables efficient range search that can be used to implement k-NN.

11:30 – 12:00
Heterogeneous Computing with SX-Aurora TSUBASA Vector Engine
Ryota Ishihara, NEC Corporation
Abstract

SX-Aurora TSUBASA supports a variety of execution models in heterogeneous environments including various computational resources such as GPU and x86. User can select appropriate computational resources according to characteristics of each of applications in the executions. In this session, we will introduce the functions provided in each execution model and how to use them.

12:00 – 13:30
Lunch

13:30 – 14:00
Trends
Michael Resch, HLRS, University of Stuttgart

14:00 – 14:30
Searching a roadmap to solve partial differential equations with quantum machine learning
Markus Mieth, Pia Siegl, DLR (German Aerospace Center)
Abstract

Our research aims to evaluate the potential of quantum computing to solve partial differential equations (PDEs) in the context of aerospace engineering. Established algorithms and methods for PDEs often rely on discretization in time and space. For a reasonable accuracy they come with high computational costs in terms of time and memory space. Machine learning approaches are studied as an alternative. One promising concept is the physical informed neural network (PINN) [1]. Here, the PDE is directly included into the loss function such that no data or only a limited amount is needed for training. In our approach, we exchange the classical neural network of the PINN with a trainable quantum circuit, while the optimization still runs on a classical computer. While we can already approximate simple functions successfully with known strategies [2, 3], more complex PDEs are hard to solve. Our work focuses on the search of problem-oriented quantum circuits and data encoding strategies, which increase the expressibility of the quantum model and allow for the approximation of more complex functions.

14:30 – 15:00
Prediction of Bio-Hybrid Fuel Injection and Mixture Formation in an Internal Combustion Engine
Tim Wegmann, Matthias Meinke, Wolfgang Schroeder, AIA, RWTH Aachen
Abstract

For an efficient, stable and low emission combustion of novel e-fuels in piston engines, the fuel distribution at start of ignition plays a crucial rule. The injection system and fuel properties define the initial fuel vapor distribution. The subsequent fuel-air mixing depends on the convection, turbulence intensities, and the formation and break-up of large-scale flow structures, in particular the tumble vortex. Large-eddy simulations (LES) with high mesh resolution are necessary to accurately predict all involved scales for the mixing process. In this study, numerical analyses of the liquid fuel injection and the fuel-air mixing in a piston engine are performed. LES are conducted using a hierachical unstructured Cartesian mesh method with an efficient four-way coupling of the spray droplets with the gas phase. Due to the large number of spray droplets, a Lagrangian Particle Tracking (LPT) algorithm is used to accurately predict the liquid spray propagation and evaporation. The spray model is based on a KHRT-breakup formulation. The Navier-Stokes equations are solved for compressible flow using a finite-volume method, where boundary surfaces are represented by a conservative cut-cell method. The hierarchical Cartesian mesh ensures efficient use of high performance computing platforms through solution adaptive refinement and dynamic load balancing.

15:00 – 15:30
Break

15:30 – 16:00
Quantum machine learning for data analysis
Li Zhong, HLRS, University of Stuttgart
Abstract

Fault-tolerant quantum computers have been proven to be able to improve machine learning through speed-ups in computation orimproved model scalability. Therefore, research at the junction of the two fields has garnered an increasing amount of interest, which has led to the rapid development of quantum deep learning and quantum-inspired deep learning techniques. In thiswork, we will demonstrate how quantum computers and quantum algorithms can be leveraged for image processing through quantum-inspired deep neural networks.

16:00
Open End

31st Workshop on Sustained Simulation
2021-03-16 - 2021-03-19 | HLRS, Nobelstraße 19, Stuttgart, Baden-Württemberg, 70569, Germany
Agenda
Due to the corona pandemic, the workshop was hold online. All times are given in Central European Time (CET)

Tuesday, March 16th, 2021

9:15 – 9:30
Welcome & Introduction
Michael Resch, HLRS, University of Stuttgart

9:30 – 10:00
The New Era of Hybrid-Computing on and with SX-Aurora TSUBASA: Vector-Scalar to Vector-Digital Annealing, to Vector-Quantum Annealing
Hiroaki Kobayashi, Cyberscience Center, Tohoku University
Abstract

I will be giving my talk about recent-achievements on our on-going project entitle “R&D of A Quantum-Annealing-Assisted Next Generation HPC Infrastructure and its Applications.” My talk will start with some performance evaluation results of SX-Aurora TSUBASA as a vector computing platform, and then go into its hybrid computing using VH-VE together. Finally, I will discuss two types of hybrid: computing mechanism and hardware platform levels, which are annealing on SX-Aurora TSUBASA itself and its on SX-Aurora TSUBASA and Quantum-Annealer.

10:00 – 10:30
HPC in the Next Decade
Michael Resch, HLRS, University of Stuttgart
Abstract

The coming ten years of HPC will be dominated by three main developments. First, the end of Moore’s law is already now showing its impact. Second a new application − Artificial Intelligence − is forcing computing centers to adapt their strategies. Finally, Quantum Computing is knocking on the door of HPC without providing and hints about the direction in which QC is headed. HLRS has to adapt to these challenges and in the talk we will present challenges and opportunities as well as strategies to cope with both.

10:30 – 11:00
Software Methods for Product Virtualization
Sabine Roller, DLR (Deutsches Zentrum für Luft- und Raumfahrt e.V.)
Abstract

The abstract will be provided soon.

11:00 – 11:15
Break

11:15 – 11:45
SX-Aurora TSUBASA VE Design
Hiroki Asano, NEC Tokyo
Abstract

VE (Vector Engine) of SX-Aurora TSUBASA leverages innovative vector processors which have high single-core performance and memory bandwidth.
NEC has been developing VE series and launched the latest model VE20 in 2020.
At this moment, our challenge is to achieve better performance for the future VE products through several studies.
In this session, we will introduce one of the studies regarding the memory subsystem.

11:45 – 12:15
Fostering HPC Competences in Europe to Support Academia and Industry
Bastian Koller, HLRS
Abstract

This talk will give an update on the EuroHPC Projects EuroCC and CASTIEL, which are implementing 33 National Competence Centres in Europe. Also, it will update on the FF4EuroHPC Projects with insights on the first closed open call for industrial experimentation.

12:15
Open Meeting

Wednesday, March 17th, 2021

8:30 – 8:35
Introduction of Chair

8:35 – 9:05
Exploiting Hybrid Parallelism in LBM Implementation Musubi on Hawk
Harald Klimach, Kannan Masilamani, Sabine Roller, University of Siegen
Abstract

In this contribution we look into the efficiency and scalability of our Lattice Boltzmann implementation Musubi when using OpenMP threads within an MPI parallel computation on Hawk. The Lattice Boltzmann methods enables explicit computation of incompressible flows and the mesh discretization can be automatically generated, even for complex geometries. The basic Lattice Boltzmann kernel is fairly simple and involves only few floating point operations for each lattice node. A simple loop over all lattice nodes each partition of the MPI parallel setup lends a straight forward loop parallelization with OpenMP. With increased core counts per compute node, the use of threads on the shared memory nodes is gaining importance, as it avoids overly small partitions with many outbound communications to neighboring partitions. We briefly discuss the hybrid parallelization of Musubi and investigate how the usage of OpenMP threads affects the performance when running simulations on the Hawk supercomputer at HLRS.

9:05 – 9:35
Hybrid Computation on Building Responses for Earthquakes on a VH and VEs of SX-Aurora TSUBASA
Mitsuo Yokokawa, Kobe University
Abstract

We have earthquakes frequently, and therefore buildings need to be earthquake resistant. A code for building responses in time for earthquakes was parallelized by using a hybrid execution model on a VH and VEs of the SX-Aurora TSUBASA. Computation performance will be presented.

09:35 – 10:05
Forecasting Intensive Care Unit Demand during the COVID-19 Pandemic: A Spatial Age-structured Microsimulation Model
Ralf Schneider, HLRS, Sebastian Klüsener, Matthias Rosenbaum-Feldbrügge
Abstract

Background: The COVID-19 pandemic poses the risk of overburdening health care systems, and in particular intensive care units (ICUs). Non-pharmaceutical interventions (NPIs), ranging from wearing masks to (partial) lockdowns have been implemented as mitigation measures around the globe. However, especially severe NPIs are used with great caution due to their negative effects on the economy, social life and mental well-being. Thus, understanding the impact of the pandemic on ICU demand under alternative scenarios reflecting different levels of NPIs is vital for political decision-making on NPIs. The aim is to support political decision-making by forecasting COVID-19-related ICU demand under alternative scenarios of COVID-19 progression reflecting different levels of NPIs.
Methods: In this talk we will present our implementation of a spatial age-structured microsimulation model of the COVID-19 pandemic by extending the Susceptible-Exposed-Infectious-Recovered (SEIR) framework. The model accounts for regional variation in population age structure and in spatial diffusion pathways. In a first step, we calibrate the model by applying a genetic optimization algorithm against hospital data on ICU patients with COVID-19. In a second step, we forecast COVID-19-related ICU demand under alternative scenarios of COVID 19 progression reflecting different levels of NPIs. The third step is the automation of the procedure for the provision of weekly forecasts. The automated estimation of the model’s parameters is done by means of Random-Forest regression.
Results: In the results section we will show the application of the model to Germany and demonstrate state-level forecasts over a 2-month period, which can be updated daily based on latest data on the progression of the pandemic.To illustrate the merits of our model, we present here “forecasts” of ICU demand for different stages of the pandemic during 2020 and 2021. Our forecasts for a quiet summer phase with low infection rates identified quite some variation in potential for relaxing NPIs across the federal states. By contrast, our forecasts during a phase of quickly rising infection numbers in autumn (second wave) suggested that all federal states should implement additional NPIs. However, the identified needs for additional NPIs varied again across federal states. In addition, our model suggests that during large infection waves ICU demand would quickly exceed supply, if there were no NPIs in place to contain the virus.

10:05 – 10:20
Break

10:20 – 10:50
HPC Based Analyses of Biofuel Injection in IC Engines and Metall Machining Processes
Matthias Meinke, Tim Wegmann, Julian Vorspohl, Daniel Lauwers, and Wolfgang Schröder, RWTH Aachen
Abstract

Some recent engineering applications will be presented, in which the turbulent flow in technical devices with embedded droplets and particles is simulated with the HPC platform HAWK installed at HLRS. The investigation of the flow field in the internal combustion engine is performed, to analyze the mixing of air with various injected biofuels. The distribution of the evaporated fuel in the internal combustion engine has a large influence on the emissions of pollutants and the engine efficiency. Since biofuels possess quite different fluid properties, it is important to accurately predict the concentration of the evaporated fuels for an optimization of the engine performance. The second application is connected to electrical discharge and electro-chemical machining processes, which are used to manufacture work pieces such as turbine blades of high strength material. In these processes, fluid flow plays an important role for the transport of removed material and thus on the quality of the final product. The simulations conducted are based on a solver formulated for hierarchical Cartesian meshes, in which a Lagrangian particle solver is used to track the motion of droplets of the fuel spray or the transport of removed material. Several aspects of the numerical methods, its parallelization, dynamic load balancing and the implementation on high performance computing platforms will be presented in this contribution.

10:50 – 11:20
Particle-in-Cell Plasma Simulation of Filamentary Coherent Structures
Seiji Ishiguro and Hiroki Hasegawa, National Institute for Fusion Science, National Institute of Natural Sciences
Abstract

We have performed three dimensional particle-in-cell (PIC) plasma simulation to investigate the filamentary coherent structure so called blob/hole.
Impurity ion transport by this structure is revealed. The impurity ion profile in the blob/hole structure becomes a dipole structure and this propagates with the blob/hole.
The performance of three dimensional PIC code on the new super computer build by NEC SX-Aurora TSUBASA at National Institute for Fusion Science will also be presented.

11:20 – 11:50
Computational Simulation of Chiral Transition and Paramagnetic Current Induced by Paramagnetic Coupling in Chiral Superconductor
Hirono Kaneyasu, University of Hyogo
Abstract

Assuming the non-unitary chiral superconductivity as a bulk state of Sr₂RuO₄, we show the field-induced chiral stability generating the paramagnetic current in the eutectic Sr₂RuO₄-Ru by computational simulation of the Ginzburg-Landau equation. The paramagnetic coupling with the chiral magnetization causes the field-induced chiral transition and the paramagnetic current. The field-induced chiral stability consists of the field-dependence of zero-bias anomaly in the tunneling spectroscopy. This good agreement with the experimental result indicates that the non-unitary chiral spin-triplet state is one of candidates for the superconducting state of Sr₂RuO₄, in addition to the chiral spin-single state as other candidates. The high-performance computing by code optimized for SX-Aurora makes it possible to analyze field dependence and spatial variation of chiral state and supercurrent in more detail.

11:50 – 12:20
Direct Numerical Flow Simulation on Vector and Massively-parallel Supercomputers
Johannes Peter, University of Stuttgart
Abstract

Direct numerical simulations of turbulent flows require high computational power, only available on supercomputers such as those provided at the HLRS. At the Institute of Aerodynamics and Gas Dynamics an adapted in-house finite-difference code of high accuracy order is used for the analysis of canonical transitional and turbulent wall-bounded flows and (in-)stability investigations. The talk will present some recent results regarding supersonic mixing of two gases and show performance data for the massively-parallel ‘Hawk’ system and the ‘SX-Aurora’ vector system.

12:20
Open Meeting

Thursday, March 18th, 2021

8:30 – 8:35
Introduction of Chair

8:35 – 9:05
Introduction of Cloud Bursting and Seamless Use of SX-Aurora TSUBASA under Job Scheduler.
Tatsuyoshi Ohmura, NEC Tokyo
Abstract

With the development of AI/BDA, the number of users of HPC systems is increasing. While the computational power required by users is also increasing On-premise HPC systems are difficult to expand due to limitations in power, space, and budget. In this session, we will introduce cloud bursting, which is a Job Scheduler function to temporarily expand computational power by using cloud computing resources. In addition, we will introduce the function that enables the HPC system to be used transparently under Job Scheduler.

9:05 – 9:35
Porting and Optimizing Molecular Docking Simulations on SX-Aurora Vector Engine
Erich Focht (NEC Germany), Leonardo Solis-Vasquez (TU Darmstadt), Andreas Koch (TU Darmstadt)
Abstract

Molecular docking simulations are widely used in computational drug discovery to predict molecular interactions at close distances. Specifically, these simulations aim to predict the binding poses between a small molecule and a macromolecular target, both referred to as ligand and receptor, respectively. The purpose of drug discovery is to identify ligands that effectively inhibit the harmful function of a certain receptor. In that context, molecular docking simulations are critical, by using them, the time-consuming preliminary tasks consisting of identifying potential drug candidates can be significantly shortened. Subsequent wet lab experiments can be carried out using only a narrowed list of promising ligands, hence reducing the overall cost of experiments.
AutoDock is one of the most widely used software applications for molecular docking simulations. Its main engine is a Lamarckian Genetic Algorithm (LGA), which combines a genetic algorithm and a local-search method to explore several molecular poses. The prediction of the best pose is based on the score, which is a function that evaluates the free energy (kcal/mol) of a ligand-receptor system. AutoDock is characterized by nested loops with variable upper bounds and divergent control structures. Moreover, the time-intensive score evaluations are typically invoked a couple of million of times within each LGA run. Based on its computation intensity, AutoDock suffers from long execution runtimes, which are mainly attributed to its inability to leverage its embarrassing parallelism. In recent years, an OpenCL-based implementation of AutoDock has been developed to accelerate its executions on a variety of devices including multi-core CPUs, GPUs, and even FPGAs.
In this work, we present our experiences porting and optimizing the OpenCL-based AutoDock onto the SX-Aurora Vector Engine. The OpenCL code is composed of a host and device parts that are maintained in the NEC VEO version. As the API functions of OpenCL and VEOffload resemble each other, porting the host code was very smooth. While the device part was easily ported too, an extra effort was required to increase the performance on SX-Aurora. For this, we used hardware-specific techniques that involve: appropriate data types for wider vectors, leveraging the multiple cores on the SX-Aurora, pushing outer into inner loops in score calculations and local search and using multi-process VEO to overcome OpenMP limitations in NUMA mode. Our evaluations were done on VE10B and VE20B models and compared to modern multicore CPUs and GPUs.

09:35 – 10:05
Evaluating and Exploiting the Potential of the Second-generation SX-Aurora TSUBASA
Hiroyuki Takizawa, Tohoku University
Abstract

In October 2020, we have started the operation of Supercomputer AOBA, which employs the second-generation SX-Aurora TSUBASA as the main computing resource. In this talk, I would like to share the performance evaluation results to discuss the potential of the second-generation SX-Aurora TSUBASA through comparison with the previous generations. I will also introduce our recent research activities for making a good use of its performance while keeping the code portable.

10:05 – 10:20
Break

10:20 – 10:50
Acceleration of Structural Analysis Software FrontISTR on NEC SX-Aurora TSUBASA
Toshiaki Hishinuma, Research Institute for Computational Science Co. Ltd.
Abstract

Structural analysis using the finite element method (FEM) is widely used in the field of engineering.
Recently, NEC has introduced SX-Aurora TSUBASA, which has vector accelerator boards (Vector Engine, VE).
One VE has a high-speed memory with a bandwidth of about 1.2 TB/s and eight high-performance vector cores.
Each core has three Fused Multiply-Add (FMA) arithmetic units, each of which can perform 32 double-precision floating point element executions simultaneously.
The host CPU is called VH.
FrontISTR is one of the highly parallelized open-source FEM software programs for nonlinear structural analysis.
This software firstly generates a stiffness matrix using the FEM and then solves linear equations for the sparse matrix generated by FEM.
The stiffness matrix generation is not suitable for VE because it cannot process data continuously, and it involves many integer operations.
There is an API for transferring data between VH and VE called Another/Alternative/Awesome VE Offloading (AVEO), which can be used to execute compute-intensive portions of an entire program on VE.
We accelerate execution speed of the overall structural analysis program by running the linear equation solvers on VE using AVEO.
We chose the JAD format as the sparse matrix storage format and the conjugate gradient (CG) method as the linear solver.
In this study, we evaluate accelerated FrontISTR in terms of the following three parts.
(1) the generation time of stiffness matrices on VH, (2) the transfer time of sparse matrices and vectors from VH to VE using AVEO, and (3) the calculation time of linear equations by the CG method on VE.
We describe the effectiveness of accelerated structural analysis execution on NEC SX-Aurora TSUBASA.

10:50 – 11:20
VGL: a High-Performance Graph Processing Framework for the NEC SX-Aurora TSUBASA Vector Architecture
Ilya Afanasyev; Moscow State University
Abstract

Developing efficient graph algorithms implementations is an extremely important problem of modern computer science, since graphs are frequently used in various real-world applications. Graph algorithms typically belong to the data-intensive class, and thus using architectures with high-bandwidth memory potentially allows to solve many graph problems significantly faster compared to modern multicore CPUs. Among other supercomputer architectures, vector systems, such as the SX family of NEC vector supercomputers, are equipped with high-bandwidth memory. However, the highly irregular structure of many real-world graphs makes it extremely challenging to implement graph algorithms on vector systems, since these implementations are usually bulky and complicated, and a deep understanding of vector architectures hardware features is required. We present the world first attempt to develop an efficient and simultaneously simple graph processing framework for modern vector systems. Our vector graph library (VGL) framework targets NEC SX-Aurora TSUBASA as a primary vector architecture and provides relatively simple computational and data abstractions. These abstractions incorporate many vector-oriented optimization strategies into a high-level programming model, allowing quick implementation of new graph algorithms with a small amount of code and minimal knowledge about features of vector systems. The provided comparative performance analysis demonstrates that VGL-based implementations achieve significant acceleration over the existing high-performance frameworks and libraries: up to 14 times speedup over multicore CPUs (Ligra, Galois, GAPBS) and up to 3 times speedup compared to NVIDIA GPU (Gunrock, NVGRAPH) implementations.

11:20 – 11:50
Optimization of the stencil computation considering the architecture of SX-Aurora TSUBASA
Kazuhiko Komatsu, Tohoku University
Abstract

This presentation introduces optimizations of the stencil computation on SX-Aurora TSUBASA, which focuses on the differences of bandwidth characteristics of SX-Aurora TSUBASA.

11:50 – 12:20
Computational Simulation of External Aerodynamics: Evaluation of Performance and Scalability
Michael Wagner, DLR (Deutsches Zentrum für Luft- und Raumfahrt e.V.)
Abstract

This presentation will share our efforts and experiences in evaluating performance and scalability of CODA on current HPC architectures. CODA is a CFD solver for external aircraft aerodynamics developed by DLR, ONERA, and Airbus, and one of the key next-generation engineering applications represented in the European Centre of Excellence for Engineering Applications (EXCELLERAT).

12:20
Open Meeting

Friday, March 19th, 2021

8:30 – 8:35
Introduction of Chair

8:35 – 9:05
Packed Mode Vectorization in LLVM for SX-Aurora
Simon Moll (NEC Germany)
Abstract

The abstract will be provided soon.

9:05 – 9:35
An Energy-aware Cache Control Mechanism for Deep Cache Hierarchy
Ryusuke Egawa(Tokyo Denki University), Liu Jiaheng(Tohoku University)
Abstract

To overcome the memory wall problem, cache hierarchies of modern microprocessors have become deeper and larger as the number of cores increases. Besides, the power and energy consumption of the deep cache hierarchy become non-negligible. In this talk, we present a mechanism to improve cache energy efficiency by adapting a cache hierarchy to individual applications and its evaluation results.

09:35 – 10:05
Loose Coupling of Task-based Programming Models with MPI Through Continuations
Joseph Schuchart, HLRS
Abstract

Using MPI in combination with asynchronous task-based programming models can be a daunting task. Applications typically have to manage a dynamic set of active operations, fall-back to a fork-join model, or rely on some middleware to coordinate the interaction between MPI and the task scheduler. In this talk, I will propose an extension to MPI, called MPI Continuations, that provides a callback-based notification mechanism to simplify the usage of MPI inside asynchronous tasks.

10:05 – 10:20
Break

10:20 – 10:50
Five challenges of new supercomputing system SQUID in Osaka University
Susumu Date, Cybermedia Center, Osaka University
Abstract

The abstract will be provided soon.

10:50 – 11:20
Basics on Quantum Computation
Thomas Kloss, University Grenoble
Abstract

With the announcement of quantum supremacy in 2019, Google claimed to have solved the first real-world problem out of reach for classical computers. Since then at the latest, quantum computing has moved into the political and economic spotlight. In this talk I will present some very basic slides on quantum computers and what makes them different of classical computers. I will also show new work which puts Googles supremacy claim into question.

11:20 – 11:50
AI@HLRS: The Past, the Present, and the Future
Dennis Hoppe, HLRS
Abstract

The growth of artificial intelligence (AI) is accelerating. AI has left research and innovation labs, and nowadays plays a significant role in everyday lives. The impact on society is graspable: autonomous driving cars produced by Tesla, voice assistants such as Siri, and AI systems that beat renowned champions in board games like Go. All these advancements are facilitated by powerful computing infrastructures based on HPC and advanced AI-specific hardware, as well as highly-optimized AI codes. Since several years, HLRS is engaged in big data and AI-specific activities around HPC. In this talk, I will give a brief overview about our AI-focused research project CATALYST to engage with researchers and industry, present selected case studies, and outline our journey over the last years with respect to the convergence of AI and HPC from both a software and hardware point of view.

11:50 – 12:00
Break

12:00 – 13:00
NEC Vector Engine Performance with Legacy CFD Codes
Keith Obenschain, NRL (United States Naval Research Laboratory)
Abstract
Abstract

Many codes that were developed during the vector supercomputing era from the 1970’s to 1990’s are still in use with vector friendly constructs in their codebase. The recently released NEC Vector Engine provides an opportunity to exploit this vector heritage. The NEC Vector engine can potentially provide state of the art performance without a complete rewrite of the codebase. Given the time and cost required to port or rewrite codes, this is potentially an attractive solution. This presentation will assess how the NEC Vector engine performance compares with existing architectures using traditional benchmarks, a legacy CFD program FDL3DI and the effort required to take full advantage of the architecture.

13:00
Open Meeting

28th Workshop on Sustained Simulation
2018-10-09 - 2018-10-10 | HLRS, Nobelstraße 19, Stuttgart, Baden-Württemberg, 70569, Germany
Agenda

Tuesday, 9 October 2018

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

9:15 – 9:45
Experiences with SX-Aurora Tsubasa and its extension for the future
Hiroaki Kobayashi, Cyberscience Center, Tohoku University
Abstract

In my talk, I would like to share with you some experiences with NEC’s New Vector system named SX-Aurora TSUBASA. I will also present our on-going project, named Quantum Annealing-Assisted Next generation HPC infrastructure, with the extension of SX-Aurora TSUBASA for the future.

9:45 – 10:15
Update on the HLRS Strategy
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
Status of HPC in Siegen
Sabine Roller, Simulationstechnik & Wissenschaftliches Rechnen, Universität Siegen
Abstract

11:15 – 11:45
HPC, HPDA, Machine Learning, Deep Learning….a glance of the evolution of traditional HPC Centers
Bastian Koller, HLRS
Abstract

In this talk the current evolution of HPC as a single resource offering towards a set of solutions will be presented, analysed and some thoughts about the future use of such systems will be given

11:45 – 12:15
Data Reduction using Singular Value Decomposition (SVD) Algorithm
Jing Zhang, HLRS
Abstract

This talk will present the Singular Value Decomposition (SVD) algorithm and give the results for smaller data sets using SVD as a data reduction algorithm, which could perform feature extraction in “raw” data.

12:15 – 13:15
Lunch

13:15 – 13:45
Porting Climate Models to Aurora TSUBASA
Panos Adamidis, DKRZ
Abstract

The main interest of the climate models running at DKRZ focuses on two major directions. On one hand, high resolution grids are being used in order to resolve small-scale physical processes. In this way, parametrisation and the inherent uncertainty can be avoided , thus improving significantly climate change projections. On the other hand addressing questions related to climate variability also involves simulations running over long time periods e.g. modeling of complete glacial cycle on grids with coarser resolution.
Such simulations are computationally very intensive and high sustained performance is vital in order to be able to conduct real world experiments. Both, single node performance as well as good scaling capabilities of the soft- and hardware are important.
The NEC Aurora TSUBASA System promises high sustained performance by combining high floating point performance of vector processors with extremely high memory bandwidth. The presentation will show first results from our tests with earth system models on the NEC Aurora system at DKRZ.

13:45 – 14:15
Performance evaluation and analysis of SX-Aurora TSUBASA
Kazuhiko Komatsu, Cyberscience Center, Tohoku University
Abstract

A new vector supercomputer, SX-Aurora TSUBASA, has been released. It has a newly developed Vector Engine(VE) processor to achieve a high sustained performance by powerful vector processing and a high memory bandwidth. This presentation examines the basic potential of SX-Aurora TSUBASA through the performance evaluations.

14:15 – 14:45
Performance of a DNS code on SX-Aurora TSUBASA
Mitsuo Yokokawa, Kobe University
Abstract

Direct numerical simulations (DNSs) of turbulence at high Reynolds number are very important to understand behavior of turbulent flow and to establish tubulent models. We have carried out large-scale DNSs for more than a decade on the Earth Simulator and the K compute and would like to execute DNSs with larger grid points beyond the present grid points on future supercomputers. In this talk, the first evaluation results of a DNS code performance on SX-Aurora TSUBASA will be presented. In paticular, off-loaded I/O performace for checkpoints of instantanious velocity fields from a vector engin (VE) to a vector host (VH) as well as computing performace on VEs will be included.

14:45 – 15:15
Organizing MPI parallel Simulations
Harald Klimach, Uni Siegen
Abstract

MPI parallel simulations provide some challenges when dealing with user interaction. We present:
* a method to obtain configuration settings from Lua scripts in a scalable way,
* a strategy to manage logging output during the parallel execution with configurable level of detail,
* a concept to deal with errors detected by the application at runtime.
These components are put together into a Fortran library to build a basic infrastructure for parallel simulation applications. It relies on Fypp as a pre-processing tool, which allows the usage Python to generate Fortran code.

15:15 – 15:45
Break

15:45 – 16:15
Accelerating Heatstroke Risk Simulation on Modern Vector Systems
Ryusuke Egawa, Cyberscience Center, Tohoku University
Abstract

TBD

16:15 – 16:45
Vector Engine Processor and 2D vector function
Shintaro Momose, NEC Germany
Abstract

TBD

16:45 – 17:15
Aurora SW Update
Masashi Ikuta, NEC Tokyo
Abstract

TBD

17:15 – 17:45
Limits of sustained performance and remedies
Uwe Küster, NEC Germany
Abstract

With limited processor frequency any performance increase results from parallelism. But the startup to fill the operating units decreases the effective performance if the executed kernels are not large. We discuss this effect by measurements on Aurora. A remedy could be in implementing bricks of kernels in hardware.

19:00 –
Dinner in Goldener Adler

Wednesday, 10 October 2018

9:00 – 9:30
Deep Neural Networks for Data-Driven Turbulence Models
Andrea Beck, IAG Stuttgart
Abstract

In this talk, we present a novel data-based approach to turbulence modelling for Large Eddy Simulation by artificial neural networks. We define the exact closure terms including the discretization operators and generate training data from direct numerical simulations of decaying homogeneous isotropic turbulence. We design and train artificial neural networks based on local convolution filters to predict the underlying unknown non-linear mapping from the coarse grid quantities to the closure terms without a priori assumptions. All investigated networks are able to generalize from the data and learn approximations with a cross correlation of up to 47% and even 73% for the inner elements, leading to the conclusion that the current training success is data-bound. We further show that selecting both the coarse grid primitive variables as well as the coarse grid LES operator as input features significantly improves training results. Finally, we construct a stable and accurate LES model from the learned closure terms. Therefore, we translate the model predictions into a data-adaptive, pointwise eddy viscosity closure and show that the resulting LES scheme performs well compared to current state of the art approaches. This work represents the starting point for further research into data-driven, universal turbulence models.

9:30 – 10:00
An object oriented multiphysics simulation concept for HPC
Matthias Meinke, Lennart Schneiders, Michael Schlottke-Lakemper, Wolfgang Schroeder, Institute of Aerodynamics, RWTH Aachen Unviersity, Aachen, Germany
Abstract

A simulation framework for a generalized multiphysics simulation concept is introduced which is based on an implementation of various solvers formulated for Cartesian hierarchical meshes. The implementation features a generalized mesh object which communicates with various solvers based on finite-volume or discontinous Galerkin methods. SInce all solution methods share a common mesh, solution adaptive meshes with dynamic load balancing are straighforward to implement. Interleaved time stepping of the solvers for the different physics allow an efficient implemention on HPC systems. Examples are presented for the coupling of various solution methods for flow simulations, acoustic fields and level sets used for tracking moving surfaces.

10:00 – 10:30
Moving geometries in high-order discontinuous Galerkin discretization
Neda Ebrahimi Pour, Uni Siegen
Abstract

Representing geometries in high-order schemes is a crucial task with special requirements. An attractive solution to this problem is the employment of penalizing terms to represent the geometry within elements. This approach also allows for a convenient movement of obstacles through flows for example, as it avoids the need for expensive remeshing and interpolations. We present this concept in our high-order discontinuous Galerkin solver Ateles and show first results for compressible flows.

10:30 – 11:00
Break

11:00 – 11:30
Towards Performance and Power Model for Multi-Core Processors with DVFS
Dmitry Khabi, HLRS
Abstract

A significant part of homogeneous supercomputer consists of an extensive number of general-purpose processors (CPU),which are connected with each other over a high-performance network. The degree of parallelism of these high-performance computing (HPC)platforms is generally limited to the number of processor cores. The scalability and performance enhancement almost exclusively stems fromthe growing number of CPU cores, although that number no longer meets the constantly expanding HPC requirements.The growing number of CPU cores is to be seen not only as a simple increasing number of cores but also as the additionaloverhead in a distribution of the rest of the hardware resoursers, such as the network, last level cache, memory channels, power budget, etc.,between the growing number of the cores and hence also between the parallel processes and threads. Particulary in combination with the capabilitiesof the processor to change the operating voltage and frequency, so-called “Dynamic Voltage and Frequency Scaling (DVFS)”,the analysis of the scalability and energy efficienty of a multi-core processor even on the basis of the existing models,such as “Roofline Performance Model” or “Execution-Cache-Memory Model” (ECM), is additionally complicated.The performance and power dissipation of CPU and DRAM are in complex interaction with the number of the active cores and the CPU frequency.This talk presents an extension of ECM model (hereinafter referred as DTM – “Data Transfer Model”), which describes the performance taking intoconsideration the various frequencies of the hardware components. The evaluation of the model using the “STREAM” kernels (with temporally memory access)is performed on different hardware architectures.

11:30 – 12:00
A method to reduce load imbalances in simulations of phase change processes with FS3D
Johannes Müller, Martin Reitzle, Institute of Aerospace Thermodynamics (ITLR), University of Stuttgart, Philipp Offenhäuser, High-Performance Computing Center Stuttgart (HLRS)
Abstract

Numerical simulations of phase change processes require a precise reconstruction of the interface between two phases. Based on the Volume of Fluid (VoF) method for multiphase flows the height function technique is able to reconstruct the sharp interface accurately and enables simulations with complex interface deformations. But this calculations increase the computational load for cells containing the phase interface. An equidistant domain decomposition leads to an imbalanced workload distribution. In order to perform investigations with a high spatial and temporal resolution, it is necessary to use the available HPC resources efficiently. The challenge of parallelization is to distribute the workload homogeneously among the cores. For simulations of the solidification processes with the multiphase code Free Surface 3D (FS3D), a load balanced domain decomposition is presented. The first part is the decomposition of the structured computational domain by recursive bisection. The second part is the corresponding process communication, which enables a nearest neighbor communication through non-blocking MPI calls. The transport of the diagonal element is realized via a communication sequence and thus an exchange of small amounts of data is avoided. A measure for the load imbalance is presented based on test cases. Finally, advantages and limitations of load balancing are discussed based on the tracing of the calculations for one timestep.

12:00 – 12:30
Optimization and Parallelization of a Phase-Field Solver to Investigate Sintering Processes
J. Hötzer, H. Hierl, M. Seiz, M. Kellner, B. Nestler, IAM-CMS / KIT
Abstract

Simulations allow to improve the development of new high performance materials with tailored microstructures and defined properties. The process of sintering is of high interest in order to produce defined ceramic materials as needed for a broad range of applications e.g. healthcare, electronics, automotive and aerospace. The phase-field method allows to efficiently investigate the microstructure evolution in large scale 3D domains during the sintering process. A phase-field model based on the grand potential approach is implemented in the massively parallel phase-field solver framework PACE3D. It is optimized on various levels starting from the model and parameters down to the hardware. The solver allows to resolve and calculate an arbitrary number of individual particles in the green body by using a local reduction technique and a material class based parametrization concept. The evolution equations for the phase-fields and the concentration are explicitly vectorized using vector intrinsics. Performance results on a single core, single node and with up to 96100 processes on the German supercomputers Hazel Hen, SuperMuc and ForHLR II are shown and discussed. Besides an optimized voxel based format to store the simulation data for checkpointing with MPI-IO, an efficient and reduced mesh based output is used.

12:30 – 13:30
Lunch

13:30 – 14:00
The potential of MPI shared-memory model for supporting hybrid communication scheme
Huan Zhou, HLRS
Abstract

This talk first brings the MPI shared-memory model forward and then illustrates the usages of this model via two use cases. One is the hybrid RMA. It is fully employed in the DART-MPI. The other is the hybrid collectives (to be specific, allgather operation). These two use cases highlight the performance benefit brought by the appliance of MPI shared-memory model. However, extra synchronization operations should be added to guarantee a deterministic behaviour.

14:00 – 14:30
Fine-Grained Synchronization using Global Task Dependencies in DASH
J. Schuchart, J.Gracia, HLRS
Abstract

The current usage of MPI communication operations leads to a global synchronization across many processes and compute nodes. The problem becomes more severe when combining MPI with a thread-parallel programming model such as OpenMP: synchronization latencies are paid manyfold by all threads within an MPI processes. We present ongoing work to address this problem by implementing a task-based programming model which allows to express dependencies across MPI processes. This kind of fine-grained synchronization can replace global MPI synchronization in many cases and thus result in substantially improved communication efficiency.

14:30 – 15:00
Automatic Parameter Tuning for Efficient Checkpointing
Hiroyuki Takizawa, Muhammad Alfian Amrizal, Kazuhiko Komatsu, and Ryusuke Egawa, Graduate School of Information Sciences, Tohoku University
Abstract

One of the most intensive I/O operations of a scientific simulation is so-called checkpointing, which is to save the state of a running simulation into a checkpoint file so that the simulation can be resumed from the file upon a system failure. Generally, it is difficult to increase the I/O performance of a system at the same pace as its computational performance. Moreover, it is necessary for a future system to perform checkpointing more frequently because the system will consist of more hardware components and hence the probability of encountering a system failure during the simulation will significantly increase. As a result, the overhead for checkpointing will be relatively growing, and could dominate the total simulation time. In this talk, therefore, I will discuss the possibility and potential benefit of employing automatic parameter tuning for reducing the checkpointing overheads.

15:00 – 15:30
Break

15:30 – 16:00
NEC SX-Aurora TSUBASA and the LLVM ecosystem
Simon Moll, Compiler Design Lab, Saarland University
Abstract

The NEC SX-Aurora TSUBASA is a high-performance vector CPU for sustained simulation performance. The existing compiler toolchain for the SX-Aurora is comprehensive but also proprietary restricting its use in research and confining its development to internal teams at NEC. In recent years, the open source LLVM compiler infrastructure has seen significant support and contributions by major players such as NVIDIA, AMD, ARM, Intel, Apple and Google. These employ LLVM in their official toolchains, GPU driver stacks and mission-critical infrastructure. Likewise, many compiler research labs have adopted LLVM for its accessibility, robustness and permissive license. Recently, the LLVM community has been discussing an extension for scalable vector architectures (LLVM-SVE), which feature an active vector length just as the SX-Aurora does. In this talk, we will discuss the potential of LLVM for the NEC SX-Aurora. The Compiler Design Lab at Saarland University is working with NEC on an LLVM-SVE backend for the SX-Aurora.

16:00 – 16:30
Approach to provide supercomputer storage I/O information toward users
Tsuyoshi Nakagawa, JAMSTEC
Abstract

The role of supercomputer storage on JAMSTEC becomes increasingly important not only for simulation but also for data driven science. The information such as the storage I/O performance and the file system characteristics may improve the user’s availability and make new scientific knowledge and innovation. In this talk, we introduce our approach to provide I/O information toward users.

16:30 – 17:00
Job Scheduler Simulator Extension For Evaluating Queue Mapping to Computing Node
Susumu Date, Yuki Matsui, Yasuhiro Watashiba, Tatashi Yoshikawa, Shinji Shimojo, Cybermedia Center, Osaka University
Abstract

TBD

17:00 – 17:30
Farewell
