Abstract

Researchers

Principle Investigator: Prof. Dr. Katharina Hölzle || Contact Author: Daniel-Leonhard Fox || Hasso Plattner Institute, Germany

Abstract

Finding the source of an outbreak allows efficient resource allocation. We build on previous work that uses graph neural networks to find patient zero on random graphs. Our goal is to design more suitable architectures and benchmark them on simulated outbreaks on very large graphs.

Researchers

Principle Investigator: Prof. Dr. Tobias Friedrich || Contact Author: Karen Seidel || Hasso Plattner Institute, Germany

Abstract

Many Internet protocols make use of legacy components such as outdated cryptography. In this project, students build a proof-of-concept attack how an adversary could attack this and decode TLS traffic in real-time, based on the now weak RSA Export ciphers. For this demo, it is necessary to factorize these old RSA primes.

Researchers

Principle Investigator: Christian Dörr || Contact Author: Christian Dörr || Hasso Plattner Institute, Germany

Abstract

Researchers

Principle Investigator: Prof. Dr. Andreas Polze || Contact Author: Joachim Kruth || University of Potsdam, Germany

Abstract

We design and develop EdgeIO, a hybrid resource orchestration and application deployment platform that seamlessly combines cloud and edge environments. The primary objective of EdgeIO is to impart flexibility -  in design, operation, moderation and modification, all the while fully exploiting the capabilities of edge & cloud computing.

Researchers

Principle Investigator: Prof. Dr.-Ing. Jörg Ott || Contact Author: Dr. Nitinder Mohan || Technical University Munich, Germany

Abstract

Partial database replication is a query-driven approach to minimize the overall memory consumption of a replication cluster while still enabling a balanced load distribution among nodes. In this Future SOC Lab project, we want to deploy partial data allocations for large database clusters and evaluate their end-to-end performance.

Researchers

Principle Investigator: Prof. Dr. h.c. Hasso Plattner || Contact Author: Stefan Halfpap || Hasso Plattner Institute, Germany

Abstract

Human behavior has shown to have a significant impact on future flood risk. The US National Flood Insurance Program has recently released data on flood insurance policies. This study contributes a data-driven approach to identify the main determinants and dynamics of flood insurance purchase throughout different states and social backgrounds.

Researchers

Principle Investigator: Prof. Dr. Andrea Cominola || Contact Author: Nadja Veigel || Technical University Berlin, Germany

Abstract

Our project contributes to the field of behaviour-based authentication. In the last years we collected a great amount of walking sequences of several people. As this dataset is too large to be processed on a normal machine, we hope to evaluate and improve our authentication model by the support of additional resources.

Researchers

Principle Investigator: Prof. Dr. Christoph Meinel || Contact Author: Vera Weidmann || neXenio GmbH, Germany

Abstract

We want to evaluate how page replication as another management mechanism is worth the effort. The experiments are based on a patched linux kernel running on multi-socket NUMA systems. The outcome should be to identify possible workloads and data structures that likely benefit from the replication of pages.

Researchers

Principle Investigator: Prof. Dr. Andreas Polze || Contact Author: Felix Eberhardt || Hasso Plattner Institute, Germany

Abstract

Cardiovascular diseases are the leading cause of death globally. Telemedicine interventions were shown to reduce the percentage of days lost due to unplanned cardiovascular hospital admissions and all-cause mortality. This project will train an AI-System that could help to scale such telemedical interventions by preprocessing and prioritizing.

Researchers

Principle Investigator: Prof. Dr. Andreas Polze || Contact Author: Jossekin Beilharz || Hasso Plattner Institute, Germany

Abstract

Microservices and DevOps are gaining considerable attraction. We would use the requested HPI Future SOC Lab resources to investigate the experimental evaluation of our activities on "DevOps-oriented Load and Resilience Testing for Microservices" and "Automated Cross-Component Issue Classification for Microservices".

Researchers

Principle Investigator: Dr.-Ing. Andre van Hoorn || Contact Author: Dr.-Ing. Andre van Hoorn || University of Stuttgart, Germany

Abstract

We are planning to extend our work on PINPOINT (published at the Runtime and Operating Systems for Supercomputers workshop at Super Computing 2020) for energy-efficient and economic processing on heterogeneous compute infrastructures in the HPI Future SOC Lab in cooperation with the OSM Group (HPI).

Researchers

Principle Investigator: Prof. Dr.-Ing. habil Wolfgang Schröder-Preikschat || Contact Author: Dr.-Ing. Timo Hönig || Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany

Abstract

The project objectives are focused on research and development of methods, technologies, tools and software systems for efficient storage, processing, analysis, mining and visualization of Big mobility, transport and health-related data collected using mobile crowd sensing and Internet of Things paradigms in Smart Cities.

Researchers

Principle Investigator: Prof. Dragan Stojanovic || Contact Author: Prof. Dragan Stojanovic || University of Nis, Serbia

Abstract

A vocal biomarker is a predictive function that reflects the state of the patient from voice in a cost-effective, instantaneous and non-intrusive way, from neurology to endocrinology. A vocal biomarker will implement a humanly interpretable convolutional neuronal network and enhanced via the integration of the stored patient and genomic data.

Researchers

Principle Investigator: Head of Platform, PhD Juan Jose Lozano || Contact Author: Dr. Julia Sidorova || Biomedical Research Networking Center in Hepatic and Digestive Diseases (CIBEREHD), Spain

Abstract

Economic and business forecasting in turbulent times is hard, as data are nonstationary. Yet, the brain has mechanisms to deal with such challenges and neuroscience has uncovered some of them. Here we predict economic indicators by stochastically optimizing a neural circuit model for emotion dynamics, using only a handful of observations.

Researchers

Principle Investigator: Prof. Dr. George Mengov || Contact Author: Prof. Dr. George Mengov || Sofia University St. Kliment Ohridski, Bulgaria

Abstract

Contact tracing is a key element in countering an epidemic. We propose a probabilistic network model that by exploiting interactions between individuals infers their probability of being infected. This will enhance the information available and will enable the design of more focused restriction and control policies and evaluate their effects.

Researchers

Principle Investigator: Elisabetta Fersini || Contact Author: Elisabetta Fersini || University of Milan-Bicocca, Italy

Abstract

The WEEVIL7 project is designed as the extension of the previous one (WEEVIL6), which was developed using the RX600S5-1 server from the HPI Future SOC Lab.  This project is a continuation of previous one, that is, this submission is a renewal for accessing HPI Future SOC Lab infrastructure.

Researchers

Principle Investigator: Prof. Dr. Carlos Juiz || Contact Author: Belen Bermejo || Universitat de les Illes Balears, Spain

Abstract

We want to examine a large artificial neural network in simulation of a system processing visual signals. Our first model was built of 4880 Hodgkin-Huxley neural cells. We now want to build a much larger 1 million-neuron system using a computational cluster and SAP HANA analytics platform for an in-memory processing of its readout signal.

Researchers

Principle Investigator: Dr. habil. (prof. PJAIT/UMCS) Grzegorz Marcin Wójcik || Contact Author: Karol Chlasta || Polish-Japanese Institute of Information Technology in Warsaw, Poland

Abstract

Our preliminary work apply Raman spectroscopy and DL for a fast diagnosis of SARS-COV-2 from human salivary samples. In the next steps, we plan to collect and analyze data from portable spectrometers (low resolution spectra) for  PoC applications, and, in parallel, we will study and longitudinally monitor vaccinated individuals through our system.

Researchers

Principle Investigator: Full Professor Vincenzina Messina || Contact Author: Dario Bertazioli || Università degli Studi di Milano-Bicocca, Italy

Abstract

The quantitative Structure-Activity Relationship (QSAR) paradigm, commonly used in drug design, will be used to stablish a mathematical model with the aim to predict the corrosion inhibition efficiency of 500 commercial drugs on steel surfaces. The HPC resources will be used to calculate quantum chemical descriptors within DFTB.

Researchers

Principle Investigator: Research Professor (Dr.) Alan Joel Miralrio Pineda || Contact Author: Research Professor (Dr.) Alan Joel Miralrio Pineda || Instituto Tecnológico y de Estudios Superiores de Monterrey (ITESM), Mexico

Abstract

The goal of this project is to develop a non-intrusive automatic data collection mechanism to collect images of coral reefs in the Vamizi Island, in the north of Mozambique. Object detection algorithms will be used in real-time to automatically photograph, detect and classify fish and other marine species that will pass by the cameras.

Researchers

Principle Investigator: Erwan Sola || Contact Author: Luís Pina || Universidade Lúrio, Mozambique

Abstract

The existing work on intrusion detection system using data mining and machine learning is based on static batch classifiers to detect intrusions irrespective of the regular data stream's time-varying characteristics. This research proposes an adaptive approach for online intrusion detection using stream-orient learning for adapting to concept drift.

Researchers

Principle Investigator: Dr. Kuljit Kaur Chahal || Contact Author: Sugandh Seth || Guru Nanak Dev University, India

Abstract

The Wildenstein Plattner Institute is undertaking a massive digitization project, with the goal to make millions of previously unpublished cultural heritage information available to the broader public. Because of the mass of information, it can only be processed using ML techniques like advanced OCR and image processing algorithms.

Researchers

Principle Investigator: Prof. Dr. Christoph Meinel || Contact Author: Christian Bartz || Wildenstein Plattner Institute Inc., United States

Abstract

The computer resources have helped us greatly to systematically investigate the influence of parameter settings on algorithm performance for problems with interconnected components. However, we have barely been able to scratch the surface to date, we are kindly asking for an extension of our access to your compute resources.

Researchers

Principle Investigator: Dr. Markus Wagner || Contact Author: Dr. Markus Wagner || University of Adelaide, Australia

Abstract

The proposal aims at deploying the experiments on a real cloud platform. The initial experiments were carried out by simulating cloud and edge platforms. We are also extending the work presented at DARLI-AP'2021 workshop by examining concurrent offloading demands.

Researchers

Principle Investigator: Prof. Zakaria Maamar || Contact Author: Prof. Zakaria Maamar || Zayed University, United Arab Emirates

Abstract

The aim of this study is to identify optimization algorithms in the Infrastructure as a Service (IaaS) layer of the computing environment. As at this layer there are several Virtual Machine (VM) parameters with their corresponding tasks to play. The fine tuning at this level is hence expected to yield optimal usage of resources.

Researchers

Principle Investigator: Dr. Saleema J S || Contact Author: Lakshmi Sankaran || Christ University, India