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International Symposium on High Performance computing, ISHPC 1997

作者： Akiyama, Yutaka Misoo, Kiyotaka Omura, Yoshiharu Matsumoto, Hiroshi Saito, Minoru Noguchi, Tamotsu Onizuka, Kentaro Ando, Makoto Parallel Application TRC Laboratory Tsukuba Research Center Real World Computing Partnership Tsukuba Mitsui Building 16F 1-6-1 Takezono Tsukuba305 Japan Information and Mathematical Science Laboratory Inc 2-43-1 Ikebukuro Toshima-ku171 Japan Radio Atmospheric Science Center Kyoto University GokashoUji611 Japan

ISBN: (纸本)3540637664

This paper describes parallelization of the space plasma particle simulation program "KEMPO1" and shows its performance on five different platforms. One of our goals is to solve the Electrostatic Solitary Wave (ESW) problem by intensive computer simulations, which previously took about 1 month for a single experiment (107 particles, 104 time steps). The parallelized version performs the same calculation in 3 hours and a bigger one (2.7 × 108 particles, 1.6 × 104 time steps) in about 8 hours on our 256-processor Hitachi SR2201 parallel computer. It has made systematic real-world space plasma particle simulations feasible. © Springer-Verlag Berlin Heidelberg 1997.

关键词： Solitons

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KC-GenRe: A Knowledge-constrained Generative Re-ranking Method Based on Large Language Models for Knowledge Graph Completion

arXiv

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arXiv 2024年

作者： Wang, Yilin Hu, Minghao Huang, Zhen Li, Dongsheng Yang, Dong Lu, Xicheng Defense Innovation Institute Academy of Military Sciences China Information Research Center of Military Science China National Key Laboratory of Parallel and Distributed Computing China

The goal of knowledge graph completion (KGC) is to predict missing facts among entities. Previous methods for KGC re-ranking are mostly built on non-generative language models to obtain the probability of each candidate. Recently, generative large language models (LLMs) have shown outstanding performance on several tasks such as information extraction and dialog systems. Leveraging them for KGC re-ranking is beneficial for leveraging the extensive pre-trained knowledge and powerful generative capabilities. However, it may encounter new problems when accomplishing the task, namely mismatch, misordering and omission. To this end, we introduce KC-GenRe, a knowledge-constrained generative re-ranking method based on LLMs for KGC. To overcome the mismatch issue, we formulate the KGC re-ranking task as a candidate identifier sorting generation problem implemented by generative LLMs. To tackle the misordering issue, we develop a knowledge-guided interactive training method that enhances the identification and ranking of candidates. To address the omission issue, we design a knowledge-augmented constrained inference method that enables contextual prompting and controlled generation, so as to obtain valid rankings. Experimental results show that KG-GenRe achieves state-of-the-art performance on four datasets, with gains of up to 6.7% and 7.7% in the MRR and Hits@1 metric compared to previous methods, and 9.0% and 11.1% compared to that without re-ranking. Extensive analysis demonstrates the effectiveness of components in KG-GenRe. Copyright © 2024, The Authors. All rights reserved.

关键词： Knowledge graph

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An evolutionary approach for scheduling in parallel processor systems

An evolutionary approach for scheduling in parallel processo...

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International Symposium on parallel Architectures, Algorithms and Networks (ISPAN)

作者： A.Y. Zomaya C. Ward B. Macey Parallel Computing Research Laboratory Department of Electrical and Electronic Engineering University of Western Australia Nedlands WA Australia University of Western Australia Perth WA AU

Task scheduling is essential for the proper functioning of parallel processor systems. Scheduling of tasks onto networks of parallel processors is an interesting problem that is well-defined and documented in the literature. However, most of the available techniques are based on heuristics that solve certain instances of the scheduling problem very efficiently and in reasonable amounts of time. This paper investigates an alternative paradigm, based on genetic algorithms, that can be used to efficiently solve the scheduling problem without the need to apply any restricted assumptions that are problem-specific, such as is the case when using heuristics. The conditions under which a genetic algorithm performs best will also be highlighted. This will be accompanied by a number of examples and case studies.

关键词： Processor scheduling Job shop scheduling Routing parallel processing Genetic algorithms Delay estimation Laboratories Manufacturing processes Process control Operations research

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Synchronizing the timestamps of concurrent events in traces of hybrid MPI/OpenMP applications

Synchronizing the timestamps of concurrent events in traces ...

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作者： Becker, Daniel Geimer, Markus Rabenseifner, Rolf Wolf, Felix German Research School for Simulation Sciences Laboratory for Parallel Programming 52062 Aachen Germany RWTH Aachen University Department of Computer Science 52056 Aachen Germany Forschungszentrum Jülich Jülich Supercomputing Centre 52428 Jülich Germany University of Stuttgart High Performance Computing-Center 70550 Stuttgart Germany

ISBN: (纸本)9780769542201

Event traces are helpful in understanding the performance behavior of parallel applications since they allow the indepth analysis of communication and synchronization patterns. However, the absence of synchronized clocks on most cluster systems may render the analysis ineffective because inaccurate relative event timings may misrepresent the logical event order and lead to errors when quantifying the impact of certain behaviors or confuse the users of time-line visualization tools by showing messages flowing backward in time. In our earlier work, we have developed a scalable algorithm that eliminates inconsistent inter-process timings postmortem in traces of pure MPI applications. Since hybrid programming, the combination of MPI and OpenMP in a single application, is becoming more popular on clusters in response to rising numbers of cores per chip and widening shared-memory nodes, we present an extended version of the algorithm that in addition to message-passing event semantics also preserves and restores shared-memory event semantics. © 2010 IEEE.

关键词： Message passing

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Sequential and parallel Meta-Heuristics for Solving the Single Row Routing Problem

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Cluster computing 2004年第2期7卷 123-139页

作者： Zomaya, Albert Y. Patterson, Daniel Olariu, Stephan School of Information Technologies The University of Sydney Sydney Australia Parallel Computing Research Laboratory Department of Electrical and Electronic Engineering The University of Western Australia Australia Department of Computer Science Old Dominion University Norfolk USA

The design of multi-layer printed circuit boards is vital in the construction of complex electronic systems. Wire routing is a crucial step in the overall design process, which can be decomposed into a number of single row routing (SRR) problems. This paper proposes an approach to solve the SRR problem based on parallel meta-heuristics. The development of this technique involves the design of an encoding strategy that allows all possible routings to be uniquely represented and the derivation of cost functions that maximizes the quality of the developed solutions. Further, parallelization of the proposed approach is attempted to improve the computational efficiency. The different stages of the development are backed by experiments to show the pros and cons of the sequential and parallel implementations.

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Hierarchical Domain Decomposition With Unitary Load Balancing For Electromagnetic Particle-In-Cell Codes

Hierarchical Domain Decomposition With Unitary Load Balancin...

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Distributed Memory computing Conference

作者： P.M. Campbell E.A. Carmona D.W. Walker Mission Research Corporation Albuquerque NM USA Weapons Laboratory Parallel Computing Research Group AFB Kirtland NM USA Department of Mathematics University of South Carolina Columbia SC USA

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Inverse scattering pre-stack depth imaging and it's comparison to some depth migration methods for imaging rich fault complex structure

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AIP Conference Proceedings 2011年第1期1454卷 83-86页

作者： Nurhandoko, Bagus Endar B. Sukmana, Indriani Mubarok, Syahrul Deny, Agus Widowati, Sri Kurniadi, Rizal Wave Inversion and Subsurface Fluid Imaging Research Laboratory WISFIR Basic Science Center A 4th floor Physics Department FMIPA Institut Teknologi Bandung Indonesia Rock Fluid Imaging Lab. Parallel Cluster Computing Center Bandung Jl. Sukasenang Raya no.2 Indonesia Department of Physics Institut Teknologi Bandung Indonesia

Migration is important issue for seismic imaging in complex structure. In this decade, depth imaging becomes important tools for producing accurate image in depth imaging instead of time domain imaging. The challenge of depth migration method, however, is in revealing the complex structure of subsurface. There are many methods of depth migration with their advantages and weaknesses. In this paper, we show our propose method of pre-stack depth migration based on time domain inverse scattering wave equation. Hopefully this method can be as solution for imaging complex structure in Indonesia, especially in rich thrusting fault zones. In this research, we develop a recent advance wave equation migration based on time domain inverse scattering wave which use more natural wave propagation using scattering wave. This wave equation pre-stack depth migration use time domain inverse scattering wave equation based on Helmholtz equation. To provide true amplitude recovery, an inverse of divergence procedure and recovering transmission loss are considered of pre-stack migration. Benchmarking the propose inverse scattering pre-stack depth migration with the other migration methods are also presented, i.e.: wave equation pre-stack depth migration, waveequation depth migration, and pre-stack time migration method. This inverse scattering pre-stack depth migration could image successfully the rich fault zone which consist extremely dip and resulting superior quality of seismic image. The image quality of inverse scattering migration is much better than the others migration methods. © 2012 American Institute of Physics.

关键词： Inverse scattering Migration Seismic

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Development Progress of SWLBM a Framework Based on Lattice Boltzmann Method for Fluid Dynamics Simulation 1

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18th International Symposium on Applied Reconfigurable computing, ARC 2022

作者： Xuesen, Chu Xiang, He Fang, Li Zhao, Liu Guangwen, Yang Department of Computer Science and Technology Tsinghua University Beijing100084 China China Ship Scientific Research Center Wuxi214082 China Taihu Laboratory of DeepSea Technological Science Wuxi214082 China Jiangnan Institute of Computing Technology Wuxi214083 China National Research Center of Parallel Computer Engineering and Technology Beijing100084 China National Supercomputing Center in Wuxi Wuxi214072 China

ISBN: (数字)9783031199837

ISBN: (纸本)9783031199820

SWLBM is a software framework based on Lattice Boltzmann Method (LBM) for Computational Fluid Dynamic (CFD) running on Sunway many-core processors. In this paper, we review the achievements of code developing in early stage and introduce the development progress recently of this software, including the development of parallel optimization for Sunway new-generation supercomputing system, functional extensions of the software like pre-process function for mesh generation from a geometry file with STL file and BMP file, Immersed boundary condition for moving subject simulation. Some applications with SWLBM will be introduced to show the advantage of this software over other CFD code in large-scale simulations. SWLBM is still under development, with the continuous improvement of functions, it will play a greater role in the field of fluid simulation. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Computational fluid dynamics

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A roadmap for the GraphBLAS C++ API 34

A roadmap for the GraphBLAS C++ API

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34th IEEE International parallel and Distributed Processing Symposium Workshops, IPDPSW 2020

作者： Brock, Benjamin Buluc, Aydin Mattson, Timothy G. McMillan, Scott Moreira, Jose E. University of California EECS Department BerkeleyCA United States Lawrence Berkeley National Laboratory Computational Research Department BerkeleyCA United States Intel Parallel Computing Labs HillsboroOR United States Carnegie Mellon University Software Engineering Institute PittsburghPA United States IBM Thomas J. Watson Research Center Yorktown HeightsNY United States

ISBN: (数字)9781728174457

ISBN: (纸本)9781728174457

The GraphBLAS are building blocks for expressing graph algorithms in terms of linear algebra. Currently, the GraphBLAS are defined as a C API. Implementations of the GraphBLAS have exposed limitations in expressiveness and performance due to limitations in C. A move to C++ should address many of these limitations while providing a simpler API. Furthermore, for methods based on user-defined types and operators, the performance should be significantly better. C++ has grown into a pervasive programming language across many domains. We see a compelling argument to define a GraphBLAS C++ API. This paper presents our roadmap for the development of a GraphBLAS C++ API. Open issues are highlighted with the goal of fostering discussion and generating feedback within the GraphBLAS user community to guide us as we develop the GraphBLAS C++ API. © 2020 IEEE.

关键词： Linear algebra

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Efficient clustering for parallel tasks execution in distributed systems

Efficient clustering for parallel tasks execution in distrib...

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International Symposium on parallel and Distributed Processing (IPDPS)

作者： A.Y. Zomaya G. Chan Advanced Networking Research Group School of Information Technologies University of Sydney Sydney NSW Australia Parallel Computing Research Laboratory Department of Electrical and Electronic Engineering University of Western Australia WA Australia

Summary form only given. The scheduling problem deals with the optimal assignment of a set of tasks to processing elements in a distributed system such that the total execution time is minimized. One approach for solving the scheduling problem is task clustering. This involves assigning tasks to clusters where each cluster is run on a single processor. This paper aims to show the feasibility of using genetic algorithms for task clustering to solve the scheduling problem. Genetic algorithms are robust optimization and search techniques that are used in this work to solve the task-clustering problem. The proposed approach shows great promise to solve the clustering problem for a wide range of clustering instances.

关键词： Clustering algorithms Optimal scheduling Processor scheduling Scheduling algorithm Costs Genetic algorithms Iterative algorithms Vectors Intelligent networks Information technology

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