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3rd International Symposium on parallel and distributed Processing and Applications, ISPA 2005

作者： Yang, Chao-Tung Shih, Po-Chi Lin, Cheng-Fang Hsu, Ching-Hsien Li, Kuan-Ching High Performance Computing Laboratory Department of Computer Science and Information Engineering Tunghai University Taichung 40704 Taiwan Department of Computer Science and Information Engineering Chung Hua University Hsinchu 300 Taiwan Parallel and Distributed Processing Center Department of Computer Science and Information Management Providence University Taichung 43301 Taiwan

ISBN: (纸本)3540297693

In order to identify and schedule jobs that are suitable for determined resources, an execution time estimation model is required. In this paper, it is described a Chronological history-based execution time estimation model to predict current execution time, according to the previous execution results. We built a heterogeneous computational Grid environment using Globus Toolkit, and our research is focused in Grid computing environments and to execute parallel jobs on multiple resources by measuring its accuracy. The experimental results shown that our model can accurately predict the execution time of embarrassingly parallel applications. © Springer-Verlag Berlin Heidelberg 2005.

关键词： distributed computer systems

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Performance analysis of applying replica selection technology for Data Grid environments

Performance analysis of applying replica selection technolog...

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8th International Conference on parallel computing Technologies, PaCT 2005

作者： Yang, Chao-Tung Chen, Chun-Hsiang Li, Kuan-Ching Hsu, Ching-Hsien High-Performance Computing Laboratory Department of Computer Science and Information Engineering Tunghai University Taichung 40704 Taiwan Parallel and Distributed Processing Center Department of Computer Science and Information Management Providence University Taichung 43301 Taiwan Department of Computer Science and Information Engineering Chung Hua University Hsinchu 300 Taiwan

The Data Grid enables the sharing, selection, and connection of a wide variety of geographically distributed computational and storage resources for solving large-scale data intensive scientific applications. Such technology efficiently manage and transfer terabytes or even petabytes of data for data-intensive, high-performance computing applications in wide-area, distributed computing environments. Replica selection process allows an application to choose a replica from replica catalog, based on its performance and data access features. In this paper, we build a Grid environment based on three existing PC Cluster environments and perform performance analysis of data transfers using GridFTP protocol over these systems. In addition, based on experimental results, it is proposed a cost model to pick the best replica, in real and dynamic network situations. © Springer-Verlag Berlin Heidelberg 2005.

关键词： distributed computer systems

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Visuel: A novel performance monitoring and analysis toolkit for cluster and grid environments

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6th International Conference on Algorithms and Architectures for parallel Processing, ICA3PP

作者： Li, Kuan-Ching Cheng, Hsiang-Yao Yang, Chao-Tung Hsu, Ching-Hsien Wang, Hsiao-Hsi Hsu, Chia-Wen Hung, Sheng-Shiang Chang, Chia-Fu Liu, Chun-Chieh Pan, Yu-Hwa Parallel and Distributed Processing Center Department of Computer Science and Information Management Providence University Taichung 43301 Taiwan High Performance Computing Laboratory Department of Computer Science and Information Engineering Tunghai University Taichung 40704 Taiwan Department of Computer Science and Information Engineering Chung Hua University Hsinchu 300 Taiwan

ISBN: (纸本)3540292357

The computing power provided by high performance low-cost PC-based Cluster and Grid platforms are attractive, and they are equal or superior to supercomputers and mainframes widely available. In this research paper, we present the design rationale and implementation of Visuel, a toolkit for performance measurement and analysis of MPI parallel programs and real time resources monitoring in cluster and grid computing environments. The proposed toolkit is web-based interface to show performance activities of all computing nodes involved in the execution of a MPI parallel program, such as CPU and memory usage levels of each computing node, and monitors all computing nodes of a computing platform by displaying real time performance data. In addition, this toolkit is able to display comparative performance data charts of multiple executions of MPI parallel application under investigation, which facilitates the "what-if" analysis. The usage of this toolkit shows that it outperforms in easing the process of investigation of parallel applications. © Springer-Verlag Berlin Heidelberg 2005.

关键词： distributed computer systems

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A massively parallel knowledge-base server using a hypercube multiprocessor

A massively parallel knowledge-base server using a hypercube...

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International Conference on Tools for Artificial Intelligence (ICTAI)

作者： F. Dehne A.G. Ferreira A. Rau-Chaplin Center for Parallel & Distributed Computing School of Computer Science Carleton University Ottawa Canada Laboratoire de l'Informatique du Parallelisme-IMAG Lyon France

The authors study the parallel implementation of a traditional frame-based knowledge representation system for a general-purpose massively parallel hypercube architecture (such as the Connection Machine). It is shown that, using a widely available parallel system (instead of a special-purpose architecture), it is possible to provide multiple users with efficient shared access to a large-scale knowledge-base. parallel algorithms are presented for answering multiple inference assert, and retract queries on both single and multiple inheritance hierarchies. In addition to theoretical time complexity analysis, empirical results obtained from extensive testing of a prototype implementation are presented.< >

关键词： Hypercubes Knowledge representation parallel architectures Computer architecture distributed computing Computer science Large-scale systems Testing Prototypes Concurrent computing

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A Dynamic Replication Mechanism to Reduce Response-Time of I/O Operations in High Performance computing Clusters

A Dynamic Replication Mechanism to Reduce Response-Time of I...

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IEEE International Conference on Social computing (SocialCom)

作者： Ehsan Mousavi Khaneghah Seyedeh Leili Mirtaheri Lucio Grandinetti Amir Saman Memaripour Mohsen Sharifi Center of High Performance Computing for Parallel and Distributed Processing University of Calabria Rende Italy School of Computer Engineering Iran University of Science and Technology Tehran Iran

ISBN: (纸本)9781479915194

Extraordinary large datasets of high performance computing applications require improvement in existing storage and retrieval mechanisms. Moreover, enlargement of the gap between data processing and I/O operations' throughput will bound the system performance to storage and retrieval operations and remarkably reduce the overall performance of high performance computing clusters. File replication is a way to improve the performance of I/O operations and increase network utilization by storing several copies of every file. Furthermore, this will lead to a more reliable and fault-tolerant storage cluster. In order to improve the response time of I/O operations, we have proposed a mechanism that estimates the required number of replicas for each file based on its popularity. Besides that, the remaining space of storage cluster is considered in the evaluation of replication factors and the number of replicas is adapted to the storage state. We have implemented the proposed mechanism using HDFS and evaluated it using MapReduce framework. Evaluation results prove its capability to improve the response time of read operations and increase network utilization. Consequently, this mechanism reduces the overall response time of read operations by considering files' popularity in replication process and adapts the replication factor to the cluster state.

关键词： Time factors High performance computing Bandwidth Reliability Throughput System performance History

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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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A parallel algorithm for zero skew clock tree routing 98

A parallel algorithm for zero skew clock tree routing

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Proceedings of the 1998 international symposium on Physical design

作者： Zhaoyun Xing Prithviraj Banerjee Sun Microsystems Laboratories 2550 Garcia Avenue Mountain View CA Center for Parallel and Distributed Computing Northwestern University 2145 Sheridan Road Evanston IL

ISBN: (纸本)9781581130218

In deep sub-micron fabrication technology, clock skew is one of the dominant factors which determine system performance. Previous works in zero skew clock tree routing assume that the wires have uniform size, and previous wire-sizing algorithms for general signal nets do not produce the exact zero skew. In this paper, we first propose an algorithm to get the exact zero skew wire-sizing by using an iterative method to make the wire size improvement. Our experiments on benchmark clock trees show that the algorithm reduces the source sink delay more than 3 times that of the clock trees with uniform wire sizes and keeps the clock skew zero. Motivated by the computation intensive nature of the zero skew clock tree construction and wire-sizing, we propose a parallel algorithm using a cluster-based clock tree construction algorithm and our zero skew wire-sizing algorithm. Without sacrificing the quality of the solution, on the average we obtain speedups of 7.8 from the parallel clustering based clock tree construction algorithm on an 8 processor SUN SPARC Server 1000E shared memory multi-processor.

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A mathematical model for empowerment of Beowulf clusters for exascale computing

A mathematical model for empowerment of Beowulf clusters for...

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International Conference on High Performance computing & Simulation (HPCS)

作者： Seyedeh Leili Mirtaheri Ehsan Mousavi Khaneghah Lucio Grandinetti Mohsen Sharifi Center of High Performance Computing for Parallel and Distributed Processing University of Calabria Rende Italy School of Computer Engineering Iran University of Science and Technology Tehran Iran

High-performance computing (HPC) clusters are currently faced with two major challenges - namely, the dynamic nature of new generation of applications and the heterogeneity of platforms - if they are going to be useful for exascale computing. Processes running these applications may well demand unpredictable requirements and changes to system configuration and capabilities at runtime, thereby requiring fast system response without sacrificing the transparency and integrity of the reconfigured empowered system that is running on a heterogeneous platform. While a challenge in and of itself, platform heterogeneity is both useful and instrumental in the handling of unpredictable requests. The realization of such a dynamically reconfigurable and heterogeneous HPC cluster system for exascale computing requires a model to guide running processes to determine if they need empowerment of the current cluster, and if yes, by how much. To show the feasibility of empowerment of traditional HPC clusters for exascale computing, we have selected Beowulf as a noble candidate cluster and present a mathematical model for the empowerment of Beowulf clusters for exascale computing (EBEC). We have developed the model in line with Beowulf's cluster approach and by using vector space algebra. In contrast to traditional hardware-oriented approaches to improvise the performance of clusters, we use a software approach to the development of the proposed model by emphasizing processes, which act as the creators of the cluster and thus should decide on system (re)configuration, as the principal building blocks of the system. We have also adopted a new approach to heterogeneity by considering heterogeneity at different levels including hardware, system software, application software, and system functionality. In addition to support for heterogeneity and dynamic reconfiguration, the proposed model includes support for scalability that is crucial to exascale computing too.

关键词： Vectors Mathematical model Hardware Runtime Computers Computational modeling

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WPress: An Application-Driven Performance Benchmark for Cloud-Based Virtual Machines

WPress: An Application-Driven Performance Benchmark for Clou...

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International Conference on Enterprise distributed Object computing (EDOC)

作者： Amir Hossein Borhani Philipp Leitner Bu-Sung Lee Xiaorong Li Terence Hung Institute of High-Performance Computing (IHPC) Singapore s.e.a.l. software evolution & architecture lab University of Zurich Switzerland Parallel and Distributed Computing Center (PDCC) Nanyang Technological University Singapore

ISBN: (纸本)9781479954711

Approaching a comprehensive performance benchmark for on-line transaction processing (OLTP) applications in a cloud environment is a challenging task. Fundamental features of clouds, such as the pay-as-you-go pricing model and unknown underlying configuration of the system, are contrary to the basic assumptions of available benchmarks such as TPC-W or RUBiS. In this paper, we introduce a systematic performance benchmark approach for OLTP applications on public clouds that use virtual machines(VMs). We propose WPress benchmark, which is based on the widespread blogging software, WordPress, as a representative OLTP application and implement an open source workload generator. Furthermore, we utilize a CPU micro-benchmark to investigate CPU performance of cloud-based VMs in greater detail. Average response time and total VM cost are the performance metrics measured by WPress. We evaluate small and large instance types of three real-life cloud providers, Amazon EC2, Microsoft Azure and Rackspace cloud. Results imply that Rackspace cloud has better average response times and total VM cost on small instances. However, Microsoft Azure is preferable for large instance type.

关键词： Benchmark testing Cloud computing Time factors Servers Databases Blogs Publishing

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Data management for large-scale scientific computations in high performance distributed systems

Data management for large-scale scientific computations in h...

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International Symposium on High Performance distributed computing

作者： A. Choudhary M. Kandemir H. Nagesh J. No X. Shen V. Taylor S. More R. Thakur Center for Parallel and Distributed Computing Department of Electrical and Computer Engineering Northwestern University Evanston IL USA Mathematics and Computer Science Division Argonne National Laboratory Argonne IL USA

With the increasing number of scientific applications manipulating huge amounts of data, effective data management is an increasingly important problem. Unfortunately, so far the solutions to this data management problem either require deep understanding of specific storage architectures and file layouts (as in high-performance file systems) or produce unsatisfactory I/O performance in exchange for ease-of-use and portability (as in relational DBMSs). In this paper we present a new environment which is built around an active meta-data management system (MDMS). The key components of our three-tiered architecture are user application, the MDMS, and a hierarchical storage system (HSS). Our environment overcomes the performance problems of pure database-oriented solutions, while maintaining their advantages in terms of ease-of-use and portability. The high levels of performance are achieved by the MDMS, with the aid of user-specified directives. Our environment supports a simple, easy-to-use yet powerful user interface, leaving the task of choosing appropriate I/O techniques to the MDMS. We discuss the importance of an active MDMS and show how the three components, namely application, the MDMS, and the HSS, fit together. We also report performance numbers from our initial implementation and illustrate that significant improvements are made possible without undue programming effort.

关键词： Large-scale systems distributed computing High performance computing Data visualization Engineering management Concurrent computing Relational databases Art Data analysis Image analysis

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