Multiscale simulations in organic electronics: Applications to polymer wrapping of single-walled carbon nanotubes, bulk charge mobilities and organic-organic interfaces

The thesis deals with the simulation of organic molecular systems on multi scales. It covers the development of a coarse-grained model for polymer wrapping of single-walled carbon nanotubes (SWCNTs) which provides good predictions of the polymer\u27s selectivity towards different types of SWCNTs. Furthermore, the bulk charge mobility is analyzed for different amorphous and crystalline materials from first principle

FIAS Scientific Report 2011

In the year 2010 the Frankfurt Institute for Advanced Studies has successfully continued to follow its agenda to pursue theoretical research in the natural sciences. As stipulated in its charter, FIAS closely collaborates with extramural research institutions, like the Max Planck Institute for Brain Research in Frankfurt and the GSI Helmholtz Center for Heavy Ion Research, Darmstadt and with research groups at the science departments of Goethe University. The institute also engages in the training of young researchers and the education of doctoral students. This Annual Report documents how these goals have been pursued in the year 2010. Notable events in the scientific life of the Institute will be presented, e.g., teaching activities in the framework of the Frankfurt International Graduate School for Science (FIGSS), colloquium schedules, conferences organized by FIAS, and a full bibliography of publications by authors affiliated with FIAS. The main part of the Report consists of short one-page summaries describing the scientific progress reached in individual research projects in the year 2010..

The Emergence of Gravitational Wave Science: 100 Years of Development of Mathematical Theory, Detectors, Numerical Algorithms, and Data Analysis Tools

On September 14, 2015, the newly upgraded Laser Interferometer Gravitational-wave Observatory (LIGO) recorded a loud gravitational-wave (GW) signal, emitted a billion light-years away by a coalescing binary of two stellar-mass black holes. The detection was announced in February 2016, in time for the hundredth anniversary of Einstein's prediction of GWs within the theory of general relativity (GR). The signal represents the first direct detection of GWs, the first observation of a black-hole binary, and the first test of GR in its strong-field, high-velocity, nonlinear regime. In the remainder of its first observing run, LIGO observed two more signals from black-hole binaries, one moderately loud, another at the boundary of statistical significance. The detections mark the end of a decades-long quest, and the beginning of GW astronomy: finally, we are able to probe the unseen, electromagnetically dark Universe by listening to it. In this article, we present a short historical overview of GW science: this young discipline combines GR, arguably the crowning achievement of classical physics, with record-setting, ultra-low-noise laser interferometry, and with some of the most powerful developments in the theory of differential geometry, partial differential equations, high-performance computation, numerical analysis, signal processing, statistical inference, and data science. Our emphasis is on the synergy between these disciplines, and how mathematics, broadly understood, has historically played, and continues to play, a crucial role in the development of GW science. We focus on black holes, which are very pure mathematical solutions of Einstein's gravitational-field equations that are nevertheless realized in Nature, and that provided the first observed signals.Comment: 41 pages, 5 figures. To appear in Bulletin of the American Mathematical Societ

Quantifying and Predicting the Influence of Execution Platform on Software Component Performance

The performance of software components depends on several factors, including the execution platform on which the software components run. To simplify cross-platform performance prediction in relocation and sizing scenarios, a novel approach is introduced in this thesis which separates the application performance profile from the platform performance profile. The approach is evaluated using transparent instrumentation of Java applications and with automated benchmarks for Java Virtual Machines

Dielectric and Spin Susceptibilities using Density Functional Theory

The response of a system to some external perturbation is almost ubiquitous in Physics. The application of perturbation theory through an electronic structure method such as Density Functional Theory has had significant contributions over the last few decades. Its implementation, aptly named Density Functional Perturbation Theory has seen use in a number of ab initio calculations on a variety of physical properties of materials which depend on their lattice-dynamical behaviour. Specific heats, thermal expansion, infrared, Raman and optical spectra are to name just a few. Understanding the complex phenomena has significantly corroborated the current understanding of the quantum picture of solids. The Sternheimer scheme falls under the umbrella of methods to compute response functions in Time-Dependent Density Functional Theory. Initially developed to study the electronic polarisability, it is now commonly utilised in the field of lattice dynamics to study phonons and related crystal properties. The Sternheimer equation has also been used to model spin wave excitations by computation of the magnetic susceptibility. The poles of the susceptibility are known to correspond to magnon excitations and these computations have been corroborated by experimental inelastic neutron scattering data. These excitations are of a transverse nature, in that they involve fluctuations of the magnetisation perpendicular to a chosen z axis. The lesser-known longitudinal excitations involve fluctuations of the magnetisation along z, an investigation of collective modes present in transition metals may be carried out from self-consistent computations of the Sternheimer equation. The dielectric response is an important linear response function in solid-state physics. Its computation from first principles provides an invaluable tool in the characterisation of optical properties and can be compared to the experimental method of spectroscopic ellipsometry.The work in this thesis concerns the implementation of the Sternheimer method in computing the dynamical response from either an external plane wave or spin-polarised perturbation. These response functions are the dielectric and spin (magnetisation) susceptibilities respectively.The scheme to compute the frequency-dependent dielectric response is implemented in a plane-wave pseudopotential DFT package. Calculations are performed on the semiconducting systems of Silicon, Gallium Arsenide, Zinc Oxide and perovskite Methylammonium Lead Triiodide. The overall shape of the dielectric spectra is in good agreement with spectroscopic ellipsometry data, however, there is a shift which is attributed to the limitations of DFT.The scheme developed to compute longitudinal spin dynamics is applied to the transitionmetal systems of body-centred cubic Iron and face-centred cubic Nickel. In a similar manner to another first principles approach, a single dominant peak is shown to be present in the magnetisation channel with the charge dynamics being effectively null in comparison. However, the exact position of these peaks is not in agreement with the other approach, a discussion is made regarding difficulties pertaining to self-consistent optimisation

A bibliography on parallel and vector numerical algorithms

This is a bibliography of numerical methods. It also includes a number of other references on machine architecture, programming language, and other topics of interest to scientific computing. Certain conference proceedings and anthologies which have been published in book form are listed also

Power-Aware Job Dispatching in High Performance Computing Systems

This works deals with the power-aware job dispatching problem in supercomputers; broadly speaking the dispatching consists of assigning finite capacity resources to a set of activities, with a special concern toward power and energy efficient solutions. We introduce novel optimization approaches to address its multiple aspects. The proposed techniques have a broad application range but are aimed at applications in the field of High Performance Computing (HPC) systems. Devising a power-aware HPC job dispatcher is a complex, where contrasting goals must be satisfied. Furthermore, the online nature of the problem request that solutions must be computed in real time respecting stringent limits. This aspect historically discouraged the usage of exact methods and favouring instead the adoption of heuristic techniques. The application of optimization approaches to the dispatching task is still an unexplored area of research and can drastically improve the performance of HPC systems. In this work we tackle the job dispatching problem on a real HPC machine, the Eurora supercomputer hosted at the Cineca research center, Bologna. We propose a Constraint Programming (CP) model that outperforms the dispatching software currently in use. An essential element to take power-aware decisions during the job dispatching phase is the possibility to estimate jobs power consumptions before their execution. To this end, we applied Machine Learning techniques to create a prediction model that was trained and tested on the Euora supercomputer, showing a great prediction accuracy. Then we finally develop a power-aware solution, considering the same target machine, and we devise different approaches to solve the dispatching problem while curtailing the power consumption of the whole system under a given threshold. We proposed a heuristic technique and a CP/heuristic hybrid method, both able to solve practical size instances and outperform the current state-of-the-art techniques

Quantifying and Predicting the Influence of Execution Platform on Software Component Performance

The performance of software components depends on several factors, including the execution platform on which the software components run. To simplify cross-platform performance prediction in relocation and sizing scenarios, a novel approach is introduced in this thesis which separates the application performance profile from the platform performance profile. The approach is evaluated using transparent instrumentation of Java applications and with automated benchmarks for Java Virtual Machines

Energy-aware performance engineering in high performance computing

Advances in processor design have delivered performance improvements for decades. As physical limits are reached, however, refinements to the same basic technologies are beginning to yield diminishing returns. Unsustainable increases in energy consumption are forcing hardware manufacturers to prioritise energy efficiency in their designs. Research suggests that software modifications will be needed to exploit the resulting improvements in current and future hardware. New tools are required to capitalise on this new class of optimisation. This thesis investigates the field of energy-aware performance engineering. It begins by examining the current state of the art, which is characterised by ad-hoc techniques and a lack of standardised metrics. Work in this thesis addresses these deficiencies and lays stable foundations for others to build on. The first contribution made includes a set of criteria which define the properties that energy-aware optimisation metrics should exhibit. These criteria show that current metrics cannot meaningfully assess the utility of code or correctly guide its optimisation. New metrics are proposed to address these issues, and theoretical and empirical proofs of their advantages are given. This thesis then presents the Power Optimised Software Envelope (POSE) model, which allows developers to assess whether power optimisation is worth pursuing for their applications. POSE is used to study the optimisation characteristics of codes from the Mantevo mini-application suite running on a Haswell-based cluster. The results obtained show that of these codes TeaLeaf has the most scope for power optimisation while PathFinder has the least. Finally, POSE modelling techniques are extended to evaluate the system-wide scope for energy-aware performance optimisation. System Summary POSE allows developers to assess the scope a system has for energy-aware software optimisation independent of the code being run