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Proceedings 22 IEEE International Parallel and Distributed Processing Proceedings 22nd IEEE International Parallel and Distributed Processing Symposium IPDPS 2008 Advance Program Abstracts Abstracts for both contributed papers and all workshops have been compiled to allow authors to check accuracy and so that visitors to this Website may preview the papers to be presented at the conference. Full proceedings of the conference will be published on a cdrom to be dis- tributed to registrants at the conference. Summary of Contents IEEE International Parallel and Distributed Processing Symposium 1 Session 1: Algorithms - Scheduling 2 Session 2: Applications - General Applications 5 Session 3: Architecture - Input/Output 8 Session 4: Software - Redundancy and Faults 11 Session 5: Algorithms - Numerical Algorithms 14 Session 6: Applications - P2P Systems Architecture 17 Session 7: Architecture - Multi-core 21 Session 8: Software - Implementing Message Passing 24 Session 9: Algorithms - P2P and Overlay Networks 27 Session 10: Applications - Grids 30 Session 11: Architecture - Supercomputing/SIMD 34 Plenary Session: Best Papers 37 Session 12: Algorithms - Communication Algorithms 41 Session 13: Applications - P2P Structure 44 Session 14: Architecture - Power/SMT/ILP 47 Session 15: Software - Tuning and Performance 50 Session 16: Algorithms - Theory 53 Session 17: Applications - P2P Reliability and Trust 56 Session 18: Architecture - Networks 59 Session 19: Software - Language Features and Implementation 63 Session 20: Algorithms - Fault Tolerance 66 Session 21: Applications - Sensors 69 Session 22: Applications - Web Applications 72 Session 23: Software - Resource Management and Scheduling 75 Session 24: Algorithms - Sensor Networks 78 i Session 25: Applications - Additional Applications 81 Session 26: Applications - Applications and the Cell Processor 84 Heterogeneity in Computing Workshop 87 Workshop on Parallel and Distributed Real-Time Systems 94 Reconfigurable Architectures Workshop 101 Workshop on High-Level Parallel Programming Models & Supportive Environments 122 Workshop on Java and Components for Parallelism, Distribution and Concurrency 130 Workshop on Nature Inspired Distributed Computing 136 Workshop on High Performance Computational Biology 146 Advances in Parallel and Distributed Computing Models 152 Communication Architecture for Clusters 162 NSF Next Generation Software Program 168 High-Performance, Power-Aware Computing 198 High Performance Grid Computing 204 Workshop on System Management Techniques, Processes, and Services 211 Workshop on Parallel and Distributed Scientific and Engineering Computing 218 Performance Modeling, Evaluation, and Optimisation of Ubiquitous Computing and Networked Systems 232 Dependable Parallel, Distributed and Network-Centric Systems 242 International Workshop on Security in Systems and Networks 250 International Workshop on Hot Topics in Peer-to-Peer Systems 256 Workshop on Large-Scale, Volatile Desktop Grids 263 Workshop on Multi-Threaded Architectures and Applications 271 Workshop on Parallel and Distributed Computing in Finance 277 Workshop on Large-Scale Parallel Processing 284 ii IEEE International Parallel & Distributed Processing Symposium IPDPS 2008 1 SESSION 1 Algorithms - Scheduling 2 Efficient Resource Management Using Advance Reservations for Heterogeneous Grids Claris Castillo, George N. Rouskas and Khaled Harfoush Department of Computer Science North Carolina State University Raleigh, NC 27695 Email: {ccastil,rouskas,kaharfou}@ncsu.edu Support for advance reservations of resources plays a key role in Grid resource management as it enables the system to meet user expectations with respect to time requirements and temporal dependence of applications, increases predictability of the system and enables co-allocation of resources. Despite these attractive features, adoption of advance reservations is limited mainly due to the fact that related algorithms are typically complex and fail to scale to large and loaded systems. In this work we consider two aspects of advance reservations. First, we investigate the impact of heterogeneity on Grid resource management when advance reservations are supported. Second, we employ techniques from computational geometry to develop an efficient heterogeneity-aware scheduling algorithm. Our main finding is that Grids may benefit from high levels of resource heterogeneity, independently of the total system capacity. Our results show that our algorithm performs well across several user and system performance and overcome the lack of scalability and adaptability of existing mechanisms. Online Scheduling in Grids Uwe Schwiegelshohn Andrei Tchernykh Technische Universitat¨ Dortmund CICESE Research Center Robotics Research Institute 22860 Ensenada, Baja California, Mexico 44221 Dortmund, Germany [email protected] [email protected] Ramin Yahyapour Technische Universitat¨ Dortmund IT and Media Center 44221 Dortmund, Germany [email protected] This paper addresses nonclairvoyant and nonpreemptive online job scheduling in Grids. In the applied basic model, the Grid system consists of a large number of identical processors that are divided into several machines. Jobs are independent, they have a fixed degree of parallelism, and they are submitted over time. Further, a job can only be executed on the processors belonging to the same machine. It is our goal to minimize the total makespan. We show that the performance of Garey and Graham’s list scheduling algorithm is significantly worse in Grids than in multiprocessors. Then we present a Grid scheduling algorithm that guarantees a competitive factor of 5. This algorithm can be implemented using a “job stealing” approach and may be well suited to serve as a starting point for Grid scheduling algorithms in real systems. 3 Scheduling with Storage Constraints Erik Saule, Pierre-Franc¸ois Dutot and Gregory´ Mounie´ LIG - MOAIS Team Grenoble Universites,´ France {firstname.lastname}@imag.fr Cumulative memory occupation is a quite intuitive but not so studied constraint in scheduling. The interest in such a constraint is present in multi-System-on-Chip, embedded systems for storing instruction code, or in scientific computation for storing results. Memory occupation seen as a constraint is impossible to solve with approximation algorithms. We believe that transforming the constraint into a second objective to optimize helps to deal with such constraints. The problem addressed in this paper is to schedule tasks on identical processors in order to minimize both maximum completion time and maximum cumulative memory occupation. For independent tasks, a family of algorithms with good approximation ratios based on a PTAS is given. Several approximation ratios are proved to be impossible to achieve with any schedule. The precedence constrained case is then studied and a family of performance guaranteed algorithms based on List Scheduling is proposed. Finally, optimizing the mean completion time as a third objective is also studied and a tri-objective algorithm is given. Portioned Static-Priority Scheduling on Multiprocessors Shinpei Kato and Nobuyuki Yamasaki School of Science for Open and Environmental Systems Keio University, Japan {shinpei,yamasaki}@ny.ics.keio.ac.jp This paper proposes an efficient real-time scheduling algorithm for multiprocessor platforms. The algorithm is a derivative of the Rate Monotonic (RM) algorithm, with its basis on the portioned scheduling technique. The theoretical design of the algorithm is well implementable for practical use. The schedulability of the algorithm is also analyzed to guarantee the worst-case performance. The simulation results show that the algorithm achieves higher system utilizations, in which all tasks meet deadlines, with a small number of preemptions compared to traditional algorithms. 4 SESSION 2 Applications - General Applications 5 A Parallel Software Toolkit for Statistical 3-D Virus Reconstructions from Cryo Electron Microscopy Images Using Computer Clusters with Multi-core Shared-Memory Nodes Yili Zheng and Peter C. Doerschuk School of Electrical and Computer Engineering, Purdue University West Lafayette, IN 47907-1285 USA Department of Biomedical Engineering and School of Electrical and Computer Engineering, Cornell University Ithaca, NY 14853-5401 USA A statistical approach for computing 3-D reconstructions of virus particles from cryo electron microscope images and minimal prior information has been developed which can solve a range of specific problems. The statistical approach causes high computation and storage complexity in the software implementation. A parallel software toolkit is described which allows the construction of software targeted at commodity PC clusters which is modular, reusable, and user-transparent while at the same time delivering nearly linear speedup on practical problems. Modeling and Predicting Application Performance on Parallel Computers Using HPC Challenge Benchmarks Wayne Pfeiffer and Nicholas J. Wright San Diego Supercomputer Center, La Jolla CA 92093-0505, USA {pfeiffer, nwright}@sdsc.edu A method is presented for modeling application performance on parallel computers in terms of the performance of micro- kernels from the HPC Challenge benchmarks. Specifically, the application run time is expressed as a linear combination of inverse speeds and latencies from microkernels or system characteristics. The model parameters are obtained by an automated series of least squares fits using backward elimination to ensure statistical significance. If necessary, outliers are deleted to ensure that the
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