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Books and Chapters

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A. Agne, M. Platzner, C. Plessl, M. Happe, E. Lübbers, in: FPGAs for Software Programmers, Springer International Publishing, 2016, pp. 227-244


Self-aware Compute Nodes

A. Agne, M. Happe, A. Lösch, C. Plessl, M. Platzner, in: Self-aware Computing Systems, Springer International Publishing, 2016, pp. 145-165


Many modern compute nodes are heterogeneous multi-cores that integrate several CPU cores with fixed function or reconfigurable hardware cores. Such systems need to adapt task scheduling and mapping to optimise for performance and energy under varying workloads and, increasingly important, for thermal and fault management and are thus relevant targets for self-aware computing. In this chapter, we take up the generic reference architecture for designing self-aware and self-expressive computing systems and refine it for heterogeneous multi-cores. We present ReconOS, an architecture, programming model and execution environment for heterogeneous multi-cores, and show how the components of the reference architecture can be implemented on top of ReconOS. In particular, the unique feature of dynamic partial reconfiguration supports self-expression through starting and terminating reconfigurable hardware cores. We detail a case study that runs two applications on an architecture with one CPU and 12 reconfigurable hardware cores and present self-expression strategies for adapting under performance, temperature and even conflicting constraints. The case study demonstrates that the reference architecture as a model for self-aware computing is highly useful as it allows us to structure and simplify the design process, which will be essential for designing complex future compute nodes. Furthermore, ReconOS is used as a base technology for flexible protocol stacks in Chapter 10, an approach for self-aware computing at the networking level.


Verschiebungen an der Grenze zwischen Hardware und Software

M. Platzner, C. Plessl, in: Logiken strukturbildender Prozesse: Automatismen, Wilhelm Fink, 2014, pp. 123-144


Im Bereich der Computersysteme ist die Festlegung der Grenze zwischen Hardware und Software eine zentrale Problemstellung. Diese Grenze hat in den letzten Jahrzehnten nicht nur die Entwicklung von Computersystemen bestimmt, sondern auch die Strukturierung der Ausbildung in den Computerwissenschaften beeinflusst und sogar zur Entstehung von neuen Forschungsrichtungen gef{\"u}hrt. In diesem Beitrag besch{\"a}ftigen wir uns mit Verschiebungen an der Grenze zwischen Hardware und Software und diskutieren insgesamt drei qualitativ unterschiedliche Formen solcher Verschiebungen. Wir beginnen mit der Entwicklung von Computersystemen im letzten Jahrhundert und der Entstehung dieser Grenze, die Hardware und Software erst als eigenst{\"a}ndige Produkte differenziert. Dann widmen wir uns der Frage, welche Funktionen in einem Computersystem besser in Hardware und welche besser in Software realisiert werden sollten, eine Fragestellung die zu Beginn der 90er-Jahre zur Bildung einer eigenen Forschungsrichtung, dem sogenannten Hardware/Software Co-design, gef{\"u}hrt hat. Im Hardware/Software Co-design findet eine Verschiebung von Funktionen an der Grenze zwischen Hardware und Software w{\"a}hrend der Entwicklung eines Produktes statt, um Produkteigenschaften zu optimieren. Im fertig entwickelten und eingesetzten Produkt hingegen k{\"o}nnen wir dann eine feste Grenze zwischen Hardware und Software beobachten. Im dritten Teil dieses Beitrags stellen wir mit selbst-adaptiven Systemen eine hochaktuelle Forschungsrichtung vor. In unserem Kontext bedeutet Selbstadaption, dass ein System Verschiebungen von Funktionen an der Grenze zwischen Hardware und Software autonom w{\"a}hrend der Betriebszeit vornimmt. Solche Systeme beruhen auf rekonfigurierbarer Hardware, einer relativ neuen Technologie mit der die Hardware eines Computers w{\"a}hrend der Laufzeit ver{\"a}ndert werden kann. Diese Technologie f{\"u}hrt zu einer durchl{\"a}ssigen Grenze zwischen Hardware und Software bzw. l{\"o}st sie die herk{\"o}mmliche Vorstellung einer festen Hardware und einer flexiblen Software damit auf.



Hardware Virtualization on Dynamically Reconfigurable Embedded Processors

C. Plessl, M. Platzner, in: Reconfigurable Embedded Control Systems: Applications for Flexibility and Agility, IGI Global, 2011



Open Source Middleware for Networked Embedded Systems towards Future Internet of Things

N. R. Prasad, M. Eisenhauer, M. Ahlsén, A. Badii, A. Brinkmann, K. Marius Hansen, P. Rosengren, in: Vision and Challenges for Realising the Internet of Things, European Commission, 2010, pp. 153-163

Proc. Int. Conf. on Engineering of Reconfigurable Systems and Algorithms (ERSA)

T.P. Plaks, D. Andrews, R. DeMara, H. Lam, J. Lee, C. Plessl, G. Stitt, CSREA Press, 2010


Computational Steering verteilter, interaktiver Materialflusssimulationen

C. Laroque, S. Lietsch, H. Zabel, in: Augmented & Virtual Reality in der Produktentstehung, Heinz Nixdorf Institut, 2008, pp. 221-239

Proc. Int. Workshop on Storage Network Architecture and Parallel I/Os (SNAPI)

A. Brinkmann, R. Chamberlain, IEEE Computer Society, 2008

Proceedings of the 1. GI/ITG KuVS Fachgespräch Virtualisierung

A. Brinkmann, H. Karl, Paderborn Center for Parallel Computing, Paderborn University, 2008


Provision of Fault Tolerance with Grid-enabled and SLA-aware Resource Management Systems

F. Heine, M. Hovestadt, O. Kao, A. Keller, in: Parallel Computing: Current and Future Issues of High End Computing, 2006, pp. 113-120

The Virtual Resource Manager: Local Autonomy versus QoS Guarantees for Grid Applications

L. Burchard, F. Heine, H. Heiss, M. Hovestadt, O. Kao, A. Keller, B. Linnert, J. Schneider, in: Future Generation Grids, 2006, pp. 83-98


In this paper, we describe the architecture of the virtual resource manager VRM, a management system designed to reside on top of local resource management systems for cluster computers and other kinds of resources. The most important feature of the VRM is its capability to handle quality-of-service (QoS) guarantees and service-level agreements (SLAs). The particular emphasis of the paper is on the various opportunities to deal with local autonomy for resource management systems not supporting SLAs. As local administrators may not want to hand over complete control to the Grid management, it is necessary to define strategies that deal with this issue. Local autonomy should be retained as much as possible while providing reliability and QoS guarantees for Grid applications, e.g., specified as SLAs.


SLA-aware Job Migration in Grid Environments

F. Heine, M. Hovestadt, O. Kao, A. Keller, in: Grid Computing: New Frontiers of High Performance Computing, 2005, pp. 185-201


Grid Computing promises an efficient sharing of world-wide distributed resources, ranging from hardware, software, expert knowledge to special I/O devices. However, although the main Grid mechanisms are already developed or are currently addressed by tremendous research effort, the Grid environment still suffers from a low acceptance in different user communities. Beside difficulties regarding an intuitive and comfortable resource access, various problems related to the reliability and the Quality-of-Service while using the Grid exist. Users should be able to rely, that their jobs will have certain priority at the remote Grid site and that they will be finished upon the agreed time regardless of any provider problems. Therefore, QoS issues have to be considered in the Grid middleware but also in the local resource management systems at the Grid sites. However, most of the currently used resource management systems are not suitable for SLAs, as they do not support resource reservation and do not offer mechanisms for job checkpointing/migration respectively. The latter are mandatory for Grid providers as rescue anchor in case of system failures or system overload. This paper focuses on SLA-aware job migration and presents a work, which is being performed in the EU supported project HPC4U.


Large-Scale SCI Clusters in Practice: Architecture and Performance in SCI

J. Simon, A. Reinefeld, O. Heinz, in: SCI: Scalable Coherent Interface. Architecture and Software for High-Performance Compute Clusters, Springer, 1999, pp. 367-381


Multi-User System Management on SCI Cluster

M. Brune, A. Keller, A. Reinefeld, in: SCI - Scalable Coherent Interface: Architecture and Software for High Performance Compute Clusters, 1999, pp. 443-460


The growing maturity of hardware and software components has tempted researchers to build very large SCI clusters with several hundred processors that are operated as high-performance compute servers in multi-user mode. In this chapter, we present a resource management software for the user access and system administration of high-performance compute clusters named Computing Center Software (CCS). It is in day-to-day use since 1992 on various parallel systems and has recently been adapted to the management of SCI clusters. CCS provides pluggable schedulers, optimal space partitioning for multiple users, reliable user access, and powerful tools for specifying resources and services by means of a specification language and a graphical user interface. After a brief introduction in the remainder of this section, we describe the CCS system architecture and the characteristics of its resource description facilities.

Specifying Resources and Services in Metacomputing Systems

M. Brune, J. Gehring, A. Keller, A. Reinefeld, in: High-Performance Cluster Computing: Architecture and Systems, 1999, pp. 186-200


With a steadily increasing number of services, metacomputing is now gaining importance in science and industry. Virtual organizations, autonomous agents, mobile computing services, and high-performance client–server applications are among the many examples of metacomputing services. For all of them, resource description plays a major role in organizing access, use, and administration of the computing components and software services. We present a generic Resource and Service Description (RSD) for specifying the hardware and software components of (meta-) computing environments. Its graphical interface allows metacomputer users to specify their resource requests. Its textual counterpart gives service providers the necessary flexibility to specify topology and properties of the available system and software resources. Finally, its internal object-oriented representation is used to link different resource management systems and service tools. With these three representations, our generic RSD approach is a key component for building metacomputer environments.


Parallel CG Poisson Solver for PowerPC 601

S. Blazy, U. Dralle, J. Simon, in: PowerXplorer User Report - Applications and Projects on the Parsytec PowerXplorer Parallel Computer, Heinrich-Heine-Universität, 1995


Problem Independent Distributed Simulated Annealing and its Applications

R. Diekmann, J. Simon, in: Applied Simulated Annealing, Springer, 1993, pp. 17-44


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