HGS MathComp Curriculum & Events

Many of the most relevant observables of matter depend explicitly on atomistic and electronic details, rendering a first principles approach to computational materials design mandatory. Alas, even when using high-performance computers, brute force high-throughput screening of material candidates is beyond any capacity for all but the simplest systems and properties due to the combinatorial nature of chemical compound space, i.e. all the compositional, constitutional, and conformational isomers. Consequently, efficient exploration algorithms exploit implicit redundancies and correlations. I will discuss recently developed statistical learning based approaches for interpolating quantum mechanical observables throughout chemical compound space. Numerical results indicate remarkable performance in terms of efficiency, accuracy, scalability and transferability.

IWR Colloquium & HGS MathComp Von Neumann Lecture

A traditional goal of algorithmic optimality, squeezing out flops, has been superseded because of evolution in architecture. Flops no longer serve as a reasonable proxy for all aspects of complexity. Instead, algorithms must now squeeze memory, data transfers, and synchronizations, while extra flops on locally cached data represent only small costs in time and energy. Hierarchically low-rank matrices realize a rarely achieved combination of optimal storage complexity and high-computational intensity in approximating a wide class of formally dense linear operators that arise in applications for which exascale computers are being constructed. They may be regarded as algebraic generalizations of the fast multipole method. Methods based on these hierarchical data structures and their simpler cousins, tile low-rank matrices, are well proportioned for early exascale computer architectures, which are provisioned for high processing power relative to memory capacity and memory bandwidth. Hierarchically low-rank matrices are ushering in a renaissance of computational linear algebra. A challenge is that emerging hardware architecture possesses hierarchies of its own that do not generally align with those of a given algorithm-application pair. We describe modules of a software toolkit, hierarchical computations on manycore architectures (HiCMA), that illustrate these features and are intended as building blocks of applications, such as matrix-free higher-order methods in optimization and large-scale spatial statistics. Some modules of this open-source project have been adopted in the software libraries of major vendors.

Biography:

David Keyes directs the Extreme Computing Research Center at the King Abdullah University of Science and Technology (KAUST), where he was the founding Dean of the Division of Mathematical and Computer Sciences and Engineering in 2009 and currently serves in the Office of the President as Senior Associate for strategic priorities and institutional partnerships.

He works at the interface between parallel computing and partial differential equations and statistics, with a current focus on scalable algorithms exploiting data sparsity.

Before joining KAUST he led multi-institutional scalable solver software projects in the SciDAC and ASCI programs of the US DOE, ran university collaboration programs at US Department of Energy and NASA academic collaboration institutes, and taught at Columbia, Old Dominion, and Yale Universities.

He is a Fellow of SIAM, AMS, and AAAS, and has been awarded the ACM Gordon Bell Prize, the IEEE Sidney Fernbach Award, and the SIAM Prize for Distinguished Service to the Profession.

He earned a BSE in Aerospace and Mechanical Sciences from Princeton in 1978 and a PhD in Applied Mathematics from Harvard in 1984.

In the year 2000, the Clay Mathematics Institute selected seven of the most important open problems in modern mathematics and offered a prize of $1 million for a solution to any of them. Nineteen years on, only one millennium prize problem has been solved. In this talk, Prof. David Silvester will discuss the Navier-Stokes existence and smoothness problem, one of the six remaining unsolved problems.

The Navier-Stokes equations are central to fluid dynamics and its applications to engineering and physics, describing viscous turbulent flow, e.g. of air around an aeroplane wing, weather patterns and blood flow through arteries. Despite the wide-ranging applicability of the Navier-Stokes equations, it is still not known whether they always admit smooth solutions, which contain no unphysical "blow-ups", or singularities.

! Postponed until Autumn 2020 !

IIT Guwahati and Interdisciplinary Center for Scientific Computing (IWR) of Heidelberg University jointly organise the 2nd RTG Big Data Research Summer School 2020. The event will take place from March 23–27, 2020 at one of the most prestigious institutes in in India — IIT Guwahati. The summer school is aimed at advanced master students and PhD students with a background in scientific computing and mathematics.

Renowned experts will hold lectures and seminars on up to date topics and state of the art methods in big data computing and mathematics. The speakers will be researchers predominately from India and Heidelberg University, Germany. Participating students will actively discuss with the experts, solve problems during workshop sessions and some will have the opportunity to present their own research. This provides unique opportunities to the students to hone their skills.

riting performance-critical software productively is still a
challenging task because performance usually conflicts genericity.
Genericity makes programmers productive as it allows them to separate
their software into components that can be exchanged and reused
independently from each other. To achieve performance however, it is
mandatory to instantiate the code with algorithmic variants and
parameters that stem from the application domain, and tailor the code
towards the target architecture. This requires pervasive changes to
the code that destroy genericity.

In this talk, I advocate programming high-performance code using
partial evaluation and present AnyDSL, a clean-slate programming
system with a simple, annotation-based, online partial evaluator. I
will show that AnyDSL can be used to productively implement
high-performance codes from various different domains in a generic way
map them to different target architectures (CPUs with SIMD units,
GPUs). Thereby, the code generated using AnyDSL achieves a performance
that is in the range of multi man-year, industry-grade,
manually-optimized expert codes and highy-optimized code generated
from domains specific languages.

The inherent capacity of somatic cells to switch their phenotypic status in response to damage stimuli in vivo might have a pivotal role in ageing and cancer. However, how the entry-exit mechanisms of phenotype reprogramming are established remains poorly understood. In an attempt to elucidate such mechanisms, we herein introduce a stochastic model of combined epigenetic regulation (ER)-gene regulatory network (GRN) to study the plastic phenotypic behaviours driven by ER heterogeneity. To deal with such complex system, we additionally formulate a multiscale asymptotic method for stochastic model reduction, from which we derive an efficient hybrid simulation scheme. Our analysis of the coupled system reveals a regime of tristability in which pluripotent stem-like and differentiated steady-states coexist with a third indecisive state, with ER driving transitions between these states. Crucially, ER heterogeneity of differentiation genes is for the most part responsible for conferring abnormal robustness to pluripotent stem-like states. We formulate epigenetic heterogeneity-based strategies capable of unlocking and facilitating the transit from differentiation-refractory (stem-like) to differentiation-primed epistates. The application of the hybrid numerical method validates the likelihood of such switching involving solely kinetic changes in epigenetic factors. Our results suggest that epigenetic heterogeneity regulates the mechanisms and kinetics of phenotypic robustness of cell fate reprogramming. The occurrence of tunable switches capable of modifying the nature of cell fate reprogramming might pave the way for new therapeutic strategies to regulate reparative reprogramming in ageing and cancer

14:00-15:00 Talk
15:00-15:30 Discussion with the speaker after the talk, coffee will be provided

The Prelude: Pioneering the Development of Conservation Technology in Cambodia

The Sequel: Pioneering the Use of Digital Technology in Banteay Chhmar with the IWR, Heidelberg University

John Sanday who is a Conservation Architect, has spent the last 45 years working in Asia. For at least 15 of these years he has worked in Cambodia. Arriving for the first time in Siem Reap in 1989, John and his team pioneered one of the first projects in Angkor - the Preah Khan Conservation Training Project which was supported by the World Monuments Fund. John’s early memories were of the Khmer Rouge skirmishes which were still taking place on the outskirts of the historic city of Angkor – it was a memorable start to several decades of work in one of the greatest monumental cities of its time, which was placed on the UNESCO World Heritage List in 1992.

In the first part of his talk, John will describe his early days of setting up the first major conservation-training programme in the 12th Century Buddhist monastic complex of Preah Khan. He will talk about some of the problems they had to face and the techniques developed in Preah Khan and three other sites in Angkor. There will be illustrations showing Angkor as John found it in the 1990’s and it will set the background for him to side track to another major Khmer site in the far North of Cambodia.

John will dedicate the second half of his talk to one of the lesser known but highly significant Khmer sites known as Banteay Chhmar, which is closely linked to Angkor. This 12th Century Buddhist, monastic complex stylistically emulates the temples in Angkor and belongs to the Bayon period. Banteay Chhmar became John´s link with IWR and its team. John and Hans Georg Bock had been fantasizing for many years on trying to link heritage conservation with applied mathematics. Here in Banteay Chhmar, they initiated an extraordinary project and a way of using ‘state of the art’ technology to digitally reconstruct iconic face tower as well as sections of the enclosure wall with its exquisite bas-relief carvings. Precise dimensions of hundreds of stone blocks were recorded digitally to recreate the tower, which had to be dismantled and rebuilt, as well as the fallen stones of the bas relief as the first step to their reconstruction.

Khmer architect Dr. Pheakdey Nguonphan (Royal University of Phnom Penh) and Dr. Anja Schäfer (IWR) developed the digital technology and formed a multi-disciplinary research team including stone masons from Preah Khan. John will describe the system, that was developed to solve “John’s Puzzle” and illustrate how the stones began to recognize their original positions in the structures, without having to move the stones manually.

There will be time for questions and discussion at the end.

! Meet & Greet: 13:40, Mathematikon, Common Room, 5th Floor !

Talk - "Mathematics of Life" Special Interest Group

Climate change, increasing human mobility and trade, pathogen evolution and resistance, urbanization, and ecological range shifts - all these global factors destabilize the current pattern of infectious diseases, notably those transmitted by vectors. There is general agreement that this will lead to the emergence and re-emergence of a wide range of infectious diseases. In Europe, water and vector-borne diseases such as Vibriosis, Dengue, Chikungunya, West Nile Virus, Lyme disease and Tick-borne encephalitis are proliferating and emerging among previously immunologically naive populations. This may result in severe disease outbreaks, morbidity, mortality, long-term disability and increasing burdens of disease. In Low-and-Middle-Income Countries (LMICs), Ebola has not yet been contained, malaria, Dengue and cholera are still associated with massive disease burdens, and arboviruses are likewise on the rise. Globally, resistance to antibiotics and insecticides is a growing concern. New genotypes and new pathogens are threatening to unleash pandemics with potential to have major societal impact, if not effectively monitored and controlled. The recent Corona virus situation is a good example of how sensitive the global population is to local emergence of viruses with epidemic potential. Achieving the sustainable development goals 2030 requires new methods for monitoring, surveillance and analysis, all of which are key for the deployment of more efficient, timely and strategic prevention.

To address these unprecedented global challenges, the public health professions are called on to develop new approaches and innovative techniques and solutions. We are now entering a world, where increasing availability of high quality, high-dimensional data and advanced computation techniques allow for previously unimaginable levels of precision and granularity with respect to monitoring and forecasting of disease outbreaks, their associated burdens and intervention demands. Digitalization, machine learning and artificial intelligence are still in its infancy in terms of public health applications, but hold great promise for revolutionizing public health decision-making, and for sustaining and safeguarding the global population.

This talk provides a few examples on how data from many different disciplines and domains, including climate, human mobility and social media, can be integrated in machine learning, and help timely risk assessment, better forecasts and support the development of more effective prevention strategies. In the talk I will discuss the methods, findings and give examples of tangible decision tools in the making in collaboration with public health policy makers.

“Mathematics of Life” is a special interest group organized by doctoral students of the HGS MathComp.

!!! Veranstaltung ist auf unbestimmte Zeit verschoben !!!

Die Aufnahme, Speicherung und Weitergabe großer Mengen von Daten ist eine Aufgabe, der sich menschliche Gesellschaften bereits seit Jahrtausenden zu stellen haben. Einen der größten Meilensteine bildet dabei die Erfindung der Schrift, zuerst nachweisbar im Mesopotamien des 4. vorchristlichen Jahrtausends. Zeugnisse dieses Quantensprungs finden sich unter anderem in der Heidelberger Uruk-Warka-Sammlung, die spektakuläre Funde aus dem Sitz des mythischen Königs Gilgamesch bewahrt. Diese Objekte zeugen jedoch nicht nur von den Leistungen antiker Archivare, sie stellen auch eine Herausforderung für ihre modernen Nachfolger dar. Mit welchen Methoden lassen sich archäologische Daten heute sammeln, bewahren und austauschen?

Antworten darauf liefert das Heidelberger "Forensic Computational Geometry Labratory" (FCGL), an dem Methoden zur Digitalisierung archäologischer Artefakte entwickelt werden. Mittels eines Laserscanners werden die Objekte aufgenommen und über das Programm Gigamesh in digitale 3D-Modelle umgesetzt. Unter anderem kommt dieses Verfahren im Projekt "Scanning for Syria" zum Einsatz, in dessen Zentrum die Sicherung von durch den syrischen Bürgerkrieg bedrohten Kulturgütern steht. Das HAIlight im März bietet Ihnen die Gelegenheit, den Forschern am FCGL bei ihrer Arbeit mit Objekten der Uruk-Warka-Sammlung über die Schulter zu schauen.

Das HAIlight findet am Freitag, den 27.03.2020 um 18:00 Uhr statt und dauert ca. eineinhalb bis zwei Stunden. Die Plätze für die Teilnahme sind begrenzt und werden nach Ablauf der Rückmeldefrist verlost. Details zu Treffpunkt und Veranstaltungsort erhalten Sie in der Teilnahmebestätigung.

Für die Platzvergabe schicken Sie uns bitte bis spätestens Montag, 16.03.2020 unter Angabe Ihres Namens eine E-Mail an hailight@alumni.uni-heidelberg.de. Begleitpersonen können dann teilnehmen, wenn nach Berücksichtigung aller interessierten HAI-Mitglieder noch freie Plätze zur Verfügung stehen. Geben Sie daher bitte auch an, ob es sich bei Ihrer Begleitung um ein Mitglied handelt. Vielen Dank für Ihr Verständnis.

This workshop aims at discussing and devising new and unifying concepts to calculate and understand molecular stresses in complex materials. Such molecular stresses can stem from quantum chemical calculations, atomistic or coarse-grained Molecular Dynamics simulations. They could be inherent to the system, i.e. reflect intrinsic tension or pre-stress, or build up upon applying external mechanical perturbations.

In an informal workshop we will bring together experts from the relevant scientific areas, computational physics, materials science, and biological matter, and will leave room for a few contributed talks from participants as well as many discussions among speakers and participants. There is the possibility to participate in a small practical workshop on force distribution analysis (FDA).

The workshop is completely free of charge.

Please register here

Day 1 (Motivation) 09:00 - 12:00
I. Review of FEM error estimation and adaptivity for elliptic PDEs
II. Adaptive timestepping for parabolic PDES

Day 2 (Spatial adaptivity) 09:00 - 12:00
I. Error reduction estimates; marking strategies; proof of convergence
II. Goal-oriented adaptivity; dual problems; numerical experiments

Day 3 (Parametric enhancement) 09:00 - 12:00
I. Stochastic Galerkin approximation; solver ingredients
II. Combining spatial and parametric adaptivity; numerical experiments

Day 4 (Extensions) 09:00 - 10:00
I. Solutions to exercises; open issues; lessons learned

Tutorial Classes
Students will need to have access to a computer or laptop
with MATLAB or Octave installed. The exercises will be based on
the T-IFISS software package which can be downloaded from
http://www.manchester.ac.uk/ifiss/tifiss.html

Scrum is an agile framework within which people can address complex adaptive problems, while productively and creatively delivering products. Kanban uses a visual system for managing work as it moves through a process, allowing team members to see the state of every piece of work at any time.

Both of them are agile approaches to project management. Agile project management is one answer to the growing speed in which projects need to be delivered and the realization that many projects are not delivered as originally planned. This is especially true for projects with volatile or unclear requirements at project start.

Concepts like continuous improvement, fast feedback cycles, limiting work in progress and transparency can bring value to teams as well as to individuals.

During this workshop you will learn:

- What is Agile? Get an overview of agile principles, values, techniques and methods
- How to use Kanban for your personal use? Boost your productivity and get things done!
- How can Kanban be introduced to a team? Streamline work between team members and create transparency on status
- How can Scrum be adapted in an academic environment? Use a process framework to improve collaboration and knowledge-sharing between lab members and cut down your fixed meeting times

Program:

9:00-12:00

- Agile introduction - origins, mindset & term definition
- Introduction to Scrum Framework
- Introduction to Kanban
- Applying theory into practice (Part 1)
- Personal Kanban - how to gain focus and transparency in your daily work

13:00-15:15

- Applying theory to practice (Part 2)
- Kanban for teams - lightweight way to introduce an agile method to a team
- LabScrum - a process framework to manage work in academic scientific research

Please register here

- Interdisziplinäre Verbindung von Mediävistik und Informatik
- Computergestützte Analyse von Burgen, Urkunden und Landkarten
- Dokumentation basierend auf 3D-Modellen, QGIS und Neo4j
- Neue Methoden für die digitale Bauforschung
- Informationsgewinnung mit Personennetzwerken

Registrierung notwendig!

Industry’s demand for using big data analysis tools is growing evermore. Public clouds developed in recent years have provided various data analysis tools for analysts, data scientists, researchers, and academics without the burden of permanently allocating and continuously maintaining high performance computing facilities. Google Cloud Platform (GCP) is one of the public cloud providers with a variety of state-of-the-art products addressing wide range of challenges in data engineering and data analytics.
The internet age and growth of social networks was a game changer for human sciences. If previously researchers and analysts had to carefully design data collection processes, now people are sharing their thoughts and concerns on a daily (or hourly) basis. In this workshop we are going to introduce GCP pipelines from streaming Twitter API’s data into a data warehouse. Afterwards, we will perform sentiment analysis and network analysis to find the patterns in user’s behavior. Finally, using visualization tools in python, we will prepare effective communication of the results.

Target Group:

- Students majoring in economics,
information systems and natural sciences.

Hardware/ Software Requirements (Student):

- Laptop

- Anaconda

installation instructions:
https://docs.anaconda.com/anaconda/install

- A google account

Please register here