OPTIMAL STRATEGIES IN DIVING FOR DIVES OF THE REVERSE GROUP VIA EVOLUTIONARY ALGORITHMS

The aim of this study was to optimize platform diving techniques of the reverse group using a computer simulation program along with an evolutionary algorithm. We used a planar four-segment model of a diver to study the aerial phase for the reverse 3½ somersault tuck. We fixed the initial angular momentum and five characteristic poses: takeoff, adoption of spinning position, leaving the spinning position, end of come-out, and entry. Starting with real performances of male elite divers executing 306C and 307C performances we found optimal performances for the 307C. The evolutionary algorithm ends up in several different optimal technique variants. The corresponding joint angle patterns are computed and compared. Decreasing knee and hip angles in spinning position by about 20° resulted in a gain of one complete rotation

ERIS live: A NUMA-aware in-memory storage engine for tera-scale multiprocessor systems

The ever-growing demand for more computing power forces hardware vendors to put an increasing number of multiprocessors into a single server system, which usually exhibits a non-uniform memory access (NUMA). In-memory database systems running on NUMA platforms face several issues such as the increased latency and the decreased bandwidth when accessing remote main memory. To cope with these NUMA-related issues, a DBMS has to allow flexible data partitioning and data placement at runtime. In this demonstration, we present ERIS, our NUMA-aware in-memory storage engine. ERIS uses an adaptive partitioning approach that exploits the topology of the underlying NUMA platform and significantly reduces NUMA-related issues. We demonstrate throughput numbers and hardware performance counter evaluations of ERIS and a NUMA-unaware index for different workloads and configurations. All experiments are conducted on a standard server system as well as on a system consisting of 64 multiprocessors, 512 cores, and 8 TBs main memory

Evaluation of the dynamic construct competition miner for an eHealth system

Business processes of some domains are highly dynamic and increasingly complex due to their dependencies on a multitude of services provided by various providers. The quality of services directly impacts the business process’s efficiency. A first prerequisite for any optimization initiative requires a better understanding of the deployed business processes. However, the business processes are either not documented at all or are only poorly documented. Since the actual behaviour of the business processes and underlying services can change over time it is required to detect the dynamically changing behaviour in order to carry out correct analyses. This paper presents and evaluates the integration of the Dynamic Construct Competition Miner (DCCM) as process monitor in the TIMBUS architecture. The DCCM discovers business processes and recognizes changes directly from an event stream at run-time. The evaluation is carried out in the context of an industrial use-case from the eHealth domain. We will describe the key aspects of the use-case and the DCCM as well as present the relevant evaluation results

Performance Analysis of Complex Engineering Frameworks

Many engineering applications require complex frameworks to simulate the intricate and extensive sub-problems involved. However, performance analysis tools can struggle when the complexity of the application frameworks increases. In this paper, we share our efforts and experiences in analyzing the performance of CODA, a CFD solver for aircraft aerodynamics developed by DLR, ONERA, and Airbus, which is part of a larger framework for multi-disciplinary analysis in aircraft design. CODA is one of the key next-generation engineering applications represented in the European Centre of Excellence for Engineering Applications (EXCELLERAT). The solver features innovative algorithms and advanced software technology concepts dedicated to HPC. It is implemented in Python and C++ and uses multi-level parallelization via MPI or GASPI and OpenMP. We present, from an engineering perspective, the state of the art in performance analysis tools, discuss the demands and challenges, and present first results of the performance analysis of a CODA performance test case

Knowledge Graphs Evolution and Preservation -- A Technical Report from ISWS 2019

One of the grand challenges discussed during the Dagstuhl Seminar "Knowledge Graphs: New Directions for Knowledge Representation on the Semantic Web" and described in its report is that of a: "Public FAIR Knowledge Graph of Everything: We increasingly see the creation of knowledge graphs that capture information about the entirety of a class of entities. [...] This grand challenge extends this further by asking if we can create a knowledge graph of "everything" ranging from common sense concepts to location based entities. This knowledge graph should be "open to the public" in a FAIR manner democratizing this mass amount of knowledge." Although linked open data (LOD) is one knowledge graph, it is the closest realisation (and probably the only one) to a public FAIR Knowledge Graph (KG) of everything. Surely, LOD provides a unique testbed for experimenting and evaluating research hypotheses on open and FAIR KG. One of the most neglected FAIR issues about KGs is their ongoing evolution and long term preservation. We want to investigate this problem, that is to understand what preserving and supporting the evolution of KGs means and how these problems can be addressed. Clearly, the problem can be approached from different perspectives and may require the development of different approaches, including new theories, ontologies, metrics, strategies, procedures, etc. This document reports a collaborative effort performed by 9 teams of students, each guided by a senior researcher as their mentor, attending the International Semantic Web Research School (ISWS 2019). Each team provides a different perspective to the problem of knowledge graph evolution substantiated by a set of research questions as the main subject of their investigation. In addition, they provide their working definition for KG preservation and evolution

Performance Analysis of Complex Engineering Frameworks

Many engineering applications require complex frameworks to simulate the intricate and extensive sub-problems involved. However, performance analysis tools can struggle when the complexity of the application frameworks increases. In this paper, we share our efforts and experiences in analyzing the performance of CODA, a CFD solver for aircraft aerodynamics developed by DLR, ONERA, and Airbus, which is part of a larger framework for multi-disciplinary analysis in aircraft design. CODA is one of the key next-generation engineering applications represented in the European Centre of Excellence for Engineering Applications (EXCELLERAT). The solver features innovative algorithms and advanced software technology concepts dedicated to HPC. It is implemented in Python and C++ and uses multi-level parallelization via MPI or GASPI and OpenMP. We present, from an engineering perspective, the state of the art in performance analysis tools, discuss the demands and challenges, and present first results of the performance analysis of a CODA performance test case