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Data Center Building O

Dr. Jens Simon

Contact
Biography
Publications
Dr. Jens Simon

Paderborn Center for Parallel Computing (PC2)

Member - Research Assistant

Paderborn Center for Parallel Computing (PC2) > Vorstand

Member - Research Assistant

Phone:
+49 5251 60-1731
Fax:
+49 5251 60-1714
Office:
O2.161 (Map)
Web:
Visitor:
Pohlweg 51
33098 Paderborn
Postal Address:
Warburger Str. 100
33098 Paderborn

1992

Curriculum Vitae

Jens Simon graduated with a diploma in computer science 1992 and in 1999 he received his PhD - both from the Paderborn University. From 1992 til 1999, he worked at the Paderborn Center of Parallel Computing (PC²) at the University of Paderborn. From 1999 til 2001, he was the head of the Computer Science Research Group at the Konrad-Zuse-Zentrum für Informationstechnik Berlin (ZIB). Since 2001, Jens Simon is a senior research scientist and the head of IT at the PC².

He has presented several articles on national and international conferences and journals targetting optimal process mapping, benchmarking of parallel computers, performance optimization, and performance prediction.

Jens Simon worked as a referee for some international journals and conferences like ICS, SPAA, IRREGULAR, HPCN, PPL. He was a program committee member of the SCI-Europe, ParCo and a local chair of the Euro-Par in Paderborn. He was an invited speaker of some national and international workshops.

Coordinates

Universität Paderborn
Paderborn Center for Parallel Computing 
Warburgerstr. 100 
D-33098 Paderborn

office O2.161 (Building O, Pohlweg 51)
phone +49 5251 60 1731
secretary +49 5251 60 1735
fax +49 5251 60 1714
e-mail simon(at)uni-paderborn.de
Jens.Simon(at)acm.org

OpenStreetMap (N 51 42 29.07, E 8 46 06.67)

Teaching

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Publications


Open list in Research Information System

2012

Cost-aware and SLO Fulfilling Software as a Service

O. Niehörster, J. Simon, A. Brinkmann, A. Keller, J. Krüger, Journal of Grid Computing (2012), pp. 553-577

DOI
Abstract

Virtualization technology makes data centers more dynamic and easier to administrate. Today, cloud providers offer customers access to complex applications running on virtualized hardware. Nevertheless, big virtualized data centers become stochastic environments and the simplification on the user side leads to many challenges for the provider. He has to find cost-efficient configurations and has to deal with dynamic environments to ensure service level objectives (SLOs). We introduce a software solution that reduces the degree of human intervention to manage clouds. It is designed as a multi-agent system (MAS) and placed on top of the Infrastructure as a Service (IaaS) layer. Worker agents allocate resources, configure applications, check the feasibility of requests, and generate cost estimates. They are equipped with application specific knowledge allowing it to estimate the type and number of necessary resources. During runtime, a worker agent monitors the job and adapts its resources to ensure the specified quality of service—even in noisy clouds where the job instances are influenced by other jobs. They interact with a scheduler agent, which takes care of limited resources and does a cost-aware scheduling by assigning jobs to times with low costs. The whole architecture is self-optimizing and able to use public or private clouds. Building a private cloud needs to face the challenge to find a mapping of virtual machines (VMs) to hosts. We present a rule-based mapping algorithm for VMs. It offers an interface where policies can be defined and combined in a generic way. The algorithm performs the initial mapping at request time as well as a remapping during runtime. It deals with policy and infrastructure changes. An energy-aware scheduler and the availability of cheap resources provided by a spot market are analyzed. We evaluated our approach by building up an SaaS stack, which assigns resources in consideration of an energy function and that ensures SLOs of two different applications, a brokerage system and a high-performance computing software. Experiments were done on a real cloud system and by simulations.


2011

Autonomic Resource Management with Support Vector Machines

O. Niehörster, J. Simon, A. Brinkmann, A. Krieger, in: Proc. IEEE/ACM Int. Conf. on Grid Computing (GRID), IEEE Computer Society, 2011, pp. 157-164

DOI

Virtualized HPC: a contradiction in terms?

G. Birkenheuer, A. Brinkmann, J. Kaiser, A. Keller, M. Keller, C. Kleineweber, C. Konersmann, O. Niehörster, T. Schäfer, J. Simon, M. Wilhelm, Software: Practice and Experience (2011)

DOI
Abstract

System virtualization has become the enabling technology to manage the increasing number of different applications inside data centers. The abstraction from the underlying hardware and the provision of multiple virtual machines (VM) on a single physical server have led to a consolidation and more efficient usage of physical servers. The abstraction from the hardware also eases the provision of applications on different data centers, as applied in several cloud computing environments. In this case, the application need not adapt to the environment of the cloud computing provider, but can travel around with its own VM image, including its own operating system and libraries. System virtualization and cloud computing could also be very attractive in the context of high‐performance computing (HPC). Today, HPC centers have to cope with both, the management of the infrastructure and also the applications. Virtualization technology would enable these centers to focus on the infrastructure, while the users, collaborating inside their virtual organizations (VOs), would be able to provide the software. Nevertheless, there seems to be a contradiction between HPC and cloud computing, as there are very few successful approaches to virtualize HPC centers. This work discusses the underlying reasons, including the management and performance, and presents solutions to overcome the contradiction, including a set of new libraries. The viability of the presented approach is shown based on evaluating a selected parallel, scientific application in a virtualized HPC environment.


2010

Enforcing SLAs in Scientific Clouds

O. Niehörster, A. Brinkmann, G. Fels, J. Krüger, J. Simon, in: Proc. Int. Conf. on Cluster Computing (CLUSTER), IEEE, 2010, pp. 178-187

DOI

2008

Virtual Supercomputer for HPC and HTC

G. Birkenheuer, A. Brinkmann, H. Dömer, S. Effert, C. Konersmann, O. Niehörster, J. Simon, in: Proc. Gemeinsamer Workshop der GI/ITG Fachgruppen "Betriebssysteme" und "KuVS": Virtualized IT infrastructures and their management, Leibniz-Rechenzentrum, 2008, pp. 37-49


2002

Performance Evaluation, Analysis and Optimization

B. P. Miller, J. Labarta, F. Schintke, J. Simon, in: Proc. European Conf. on Parallel Processing (Euro-Par), Springer, 2002, pp. 131

DOI

2001

A Cache Simulator for Shared Memory Systems

F. Schintke, J. Simon, A. Reinefeld, in: Proc. Int. Conf. on Computational Science (ICCS), Springer, 2001, pp. 569-578

DOI

2000


1999

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

DOI

1998

The Latency-of-Data-Access model for Analyzing Parallel Computation

J. Simon, J. Wierum, Information Processing Letters - Special Issue on Models of Computation (1998), pp. 255-261

DOI

1997

Embedding SCI into PVM

M. Fischer, J. Simon, in: Proc. European Parallel Virtual Machine / Message Passing Interface Users’ Group Meeting (EuroPVM/MPI), Springer, 1997, pp. 175-184

DOI

Experiences with a SCI Multiprocessor Workstation Cluster

O. Heinz, J. Simon, in: Proc. Int. Conf. on Architecture of Computing Systems (ARCS), VDE Verlag, 1997


SCI multiprocessor PC cluster in a WindowsNT environment

J. Simon, O. Heinz, in: Proc. Workshops im Rahmen der 14. ITG/GI-Fachtagung Architektur von Rechensystemen, 1997, pp. 189-199


The MOL Project: An Open, Extensible Metacomputer

A. Reinefeld, R. Baraglia, T. Decker, J. Gehring, D. Laforenza, F. Ramme, T. Römke, J. Simon, in: Proc. Heterogenous Computing Workshop (HCW), IEEE Computer Society, 1997, pp. 17-31

DOI

Workload Analysis of Computation Intensive Tasks: Case Study on SPEC CPU95 Benchmarks

J. Simon, R. Weicker, M. Vieth, in: Proc. European Conf. on Parallel Processing (Euro-Par), Springer, 1997, pp. 971-984

DOI

1996

Accurate Performance Prediction for Massively Parallel Systems and its Applications

J. Simon, J. Wierum, in: Proc. European Conf. on Parallel Processing (Euro-Par), Springer, 1996, pp. 675-688

DOI

On Accurate Performance Prediction for Massively Parallel Systems and its Applications

J. Simon, J. Wierum, Paderborn Center for Parallel Computing, 1996


Performance Prediction of Benchmark Programs for Massively Parallel Architectures

J. Simon, J. Wierum, in: Proc. Annual Int. Conf. on High-Performance Computers (HPCS), 1996


Sequential Performance versus Scalability: Optimizing Parallel LU-Decomposition

J. Simon, J. Wierum, in: Proc. Int. Conf. on High-Performance Computing and Networking (HPCN-Europe), Springer, 1996, pp. 627-632

DOI

1995

An Efficient Mapping Library for Parix

T. Römke, M. Röttger, U. Schroeder, J. Simon, in: Proc. ZEUS Workshop on Par. Programming and Computation, IOS Press, 1995


Implementation of a Parallel and Distributed Mapping Kernel for PARIX

M. Röttger, U. Schroeder, J. Simon, in: Proc. Int. Conf. on High-Performance Computing and Networking, Springer, 1995, pp. 781-786

DOI

On Efficient Embeddings of Grids into Grids in PARIX

T. Römke, M. Röttger, U. Schroeder, J. Simon, in: Proc. European Conf. on Parallel Processing (Euro-Par), Springer, 1995, pp. 179-192

DOI

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


SparcStation SCI-Interface

J. Gehring, J. Simon, Paderborn Center for Parallel Computing, 1995


1994

Leistung eines Parallelrechners auf Basis des PowerPC-Prozessors

J. Simon, in: Parallele Datenverarbeitung aktuell: TAT '94, IOS Press, 1994, pp. 38-45


1993

Benutzung virtueller Topologien unter PARIX

J. Simon, Paderborn Center for Parallel Computing, 1993


Problem Independent Distributed Simulated Annealing and its Applications

R. Diekmann, R. Lüling, J. Simon, Paderborn Center for Parallel Computing, 1993


Problem Independent Distributed Simulated Annealing and its Applications

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

DOI

Virtual Topology Library for PARIX

M. Röttger, J. Simon, U. Schroeder, Paderborn Center for Parallel Computing, 1993


1992

A General Purpose Distributed Implementation of Simulated Annealing

R. Diekmann, R. Lüling, J. Simon, in: Proc. 13th IMACS World Congress on Computation and Applied Mathematics, 1992


A General Purpose Distributed Implementation of Simulated Annealing

R. Diekmann, R. Lüling, J. Simon, in: Proc. IEEE Symp. on Parallel and Distributed Processing (SPDP), IEEE, 1992, pp. 94-101

DOI

Implementierung von Simulated Annealing auf Transputer-Systemen

R. Diekmann, R. Lüling, B. Monien, J. Simon, in: Parallele Datenverarbeitung mit dem Transputer, Springer, 1992, pp. 361-368

DOI

Leistungssteigerung paralleler Systeme durch virtuelle Topologien

R. Diekmann, J. Simon, in: Abstraktband des 4. bundesweiten Transputer-Anwender-Treffens (TAT 92), 1992


Open list in Research Information System

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