• Title/Summary/Keyword: Distributed and Parallel Computing

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A framework for parallel processing in multiblock flow computations (다중블록 유동해석에서 병렬처리를 위한 시스템의 구조)

  • Park, Sang-Geun;Lee, Geon-U
    • Transactions of the Korean Society of Mechanical Engineers B
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    • v.21 no.8
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    • pp.1024-1033
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    • 1997
  • The past several years have witnessed an ever-increasing acceptance and adoption of parallel processing, both for high performance scientific computing as well as for more general purpose applications. Furthermore with increasing needs to perform the complex flow calculations in an efficient manner, the use of the message passing model on distributed networks has emerged as an important alternative to the expensive supercomputers. This work attempts to provide a generic framework to enable the parallelization of all CFD-related works using the master-slave model. This framework consists of (1) input geometry, (2) domain decomposition, (3) grid generation, (4) flow computations, (5) flow visualization, and (6) output display as the sequential components, but performs computations for (2) to (5) in parallel on the workstation clustering. The flow computations are parallized by having multiple copies of the flow-code to solve a PDE on different spatial regions on different processors, while their flow data are exchanged across the region boundaries, and the solution is time-stepped. The Parallel Virtual Machine (PVM) is used for distributed communication in this work.

Fully Distributed Economic Dispatching Methods Based on Alternating Direction Multiplier Method

  • Yang, Linfeng;Zhang, Tingting;Chen, Guo;Zhang, Zhenrong;Luo, Jiangyao;Pan, Shanshan
    • Journal of Electrical Engineering and Technology
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    • v.13 no.5
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    • pp.1778-1790
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    • 2018
  • Based on the requirements and characteristics of multi-zone autonomous decision-making in modern power system, fully distributed computing methods are needed to optimize the economic dispatch (ED) problem coordination of multi-regional power system on the basis of constructing decomposition and interaction mechanism. In this paper, four fully distributed methods based on alternating direction method of multipliers (ADMM) are used for solving the ED problem in distributed manner. By duplicating variables, the 2-block classical ADMM can be directly used to solve ED problem fully distributed. The second method is employing ADMM to solve the dual problem of ED in fully distributed manner. N-block methods based on ADMM including Alternating Direction Method with Gaussian back substitution (ADM_G) and Exchange ADMM (E_ADMM) are employed also. These two methods all can solve ED problem in distributed manner. However, the former one cannot be carried out in parallel. In this paper, four fully distributed methods solve the ED problem in distributed collaborative manner. And we also discussed the difference of four algorithms from the aspects of algorithm convergence, calculation speed and parameter change. Some simulation results are reported to test the performance of these distributed algorithms in serial and parallel.

Thread-Level Parallelism using Java Thread and Network Resources (자바 스레드와 네트워크 자원을 이용한 병렬처리)

  • Kim, Tae-Yong
    • Journal of Advanced Navigation Technology
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    • v.14 no.6
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    • pp.984-989
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    • 2010
  • In this paper, parallel programming technique by using Java Thread is introduced so as to develop parallel design tool to analyze the small micro flow sensor. To estimate computing time for Thread-level parallelism, the performances of two experimental models for potential problem subject to Thermal transfer equation are examined. As a result, if the number of network PC is increase, computing time for parallelism on network environment is enhanced to be almost n times. The micro sensor design tool based on distributed computing can be utilized to analyze a large scale problem.

Analysis of NEESgrid Computing and System for Korean Construction Test Equipments Infrastructure (NEESgrid 시스템의 구성과 기능별 역할 분석을 통한 우리나라 건설실험시설의 네트워크 시스템 구축)

  • Jeong, Tai Kyeong;Shim, Nak Hoon;Park, Young Suk
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.4A
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    • pp.689-692
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    • 2006
  • This paper presents the developments of Grid computing architecture which is use many data and resources from distributed and parallel system for construction test equipments, i.e., large scale computer networks meant to provide access to massive computational facilities for very large communities of users, drawing upon experiences of existing Grids architecture. In this paper, we present an efficient way to construct a construction test equipment infrastructure.

Simulation of a CIM Workflow System Using Parallel Virtual Machine (PVM)

  • Chang-Ouk Kim
    • Journal of the Korea Society for Simulation
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    • v.5 no.2
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    • pp.13-24
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    • 1996
  • Workflow is an ordered sequence of interdependent component data activities each of which can be executed on an integrated information system by accessing a remote information system. In our previous research [4], we proposed a distributed CIM Workflow system which consists of a workflow execution model called DAF-Net and an agent-based information systems called AIMIS. Given a component data activity, there needs an interaction protocol among agents which allocates the component data activity to a relevant information systems exist. The objective of this research is to propose and test two protocols: ARR(Asynchronous Request and Response)protocol and NCL(Negotiation with Case based Learning) protocol. To test the effectiveness of the protocols, we applied the PVM(Parallel Virtual Machine) software to simulate the distributed CIM Workflow system. PVM provides a distributed computing environment in which users can run different software processes in different computers while allowing communication among the processes.

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RDP: A storage-tier-aware Robust Data Placement strategy for Hadoop in a Cloud-based Heterogeneous Environment

  • Muhammad Faseeh Qureshi, Nawab;Shin, Dong Ryeol
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.9
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    • pp.4063-4086
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    • 2016
  • Cloud computing is a robust technology, which facilitate to resolve many parallel distributed computing issues in the modern Big Data environment. Hadoop is an ecosystem, which process large data-sets in distributed computing environment. The HDFS is a filesystem of Hadoop, which process data blocks to the cluster nodes. The data block placement has become a bottleneck to overall performance in a Hadoop cluster. The current placement policy assumes that, all Datanodes have equal computing capacity to process data blocks. This computing capacity includes availability of same storage media and same processing performances of a node. As a result, Hadoop cluster performance gets effected with unbalanced workloads, inefficient storage-tier, network traffic congestion and HDFS integrity issues. This paper proposes a storage-tier-aware Robust Data Placement (RDP) scheme, which systematically resolves unbalanced workloads, reduces network congestion to an optimal state, utilizes storage-tier in a useful manner and minimizes the HDFS integrity issues. The experimental results show that the proposed approach reduced unbalanced workload issue to 72%. Moreover, the presented approach resolve storage-tier compatibility problem to 81% by predicting storage for block jobs and improved overall data block placement by 78% through pre-calculated computing capacity allocations and execution of map files over respective Namenode and Datanodes.

A Data Transfer Method of the Sub-Cluster Group based on the Distributed and Shared Memory (분산 공유메모리를 기반으로 한 서브 클러스터 그룹의 자료전송방식)

  • Lee, Kee-Jun
    • The KIPS Transactions:PartA
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    • v.10A no.6
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    • pp.635-642
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    • 2003
  • The radical development of recent network technology provides the basic foundation which can establish a high speed and cheap cluster system. It is a general trend that conventional cluster systems are built as the system over a fixed level based on stabilized and high speed local networks. A multi-distributed web cluster group is a web cluster model which can obtain high performance, high efficiency and high availability through mutual cooperative works between effective job division and system nodes through parallel performance of a given work and shared memory of SC-Server with low price and low speed system nodes on networks. For this, multi-distributed web cluster group builds a sub-cluster group bound with single imaginary networks of multiple system nodes and uses the web distributed shared memory of system nodes for the effective data transmission within sub-cluster groups. Since the presented model uses a load balancing and parallel computing method of large-scale work required from users, it can maximize the processing efficiency.

Parallel Algorithm of Improved FunkSVD Based on Spark

  • Yue, Xiaochen;Liu, Qicheng
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.5
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    • pp.1649-1665
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    • 2021
  • In view of the low accuracy of the traditional FunkSVD algorithm, and in order to improve the computational efficiency of the algorithm, this paper proposes a parallel algorithm of improved FunkSVD based on Spark (SP-FD). Using RMSProp algorithm to improve the traditional FunkSVD algorithm. The improved FunkSVD algorithm can not only solve the problem of decreased accuracy caused by iterative oscillations but also alleviate the impact of data sparseness on the accuracy of the algorithm, thereby achieving the effect of improving the accuracy of the algorithm. And using the Spark big data computing framework to realize the parallelization of the improved algorithm, to use RDD for iterative calculation, and to store calculation data in the iterative process in distributed memory to speed up the iteration. The Cartesian product operation in the improved FunkSVD algorithm is divided into blocks to realize parallel calculation, thereby improving the calculation speed of the algorithm. Experiments on three standard data sets in terms of accuracy, execution time, and speedup show that the SP-FD algorithm not only improves the recommendation accuracy, shortens the calculation interval compared to the traditional FunkSVD and several other algorithms but also shows good parallel performance in a cluster environment with multiple nodes. The analysis of experimental results shows that the SP-FD algorithm improves the accuracy and parallel computing capability of the algorithm, which is better than the traditional FunkSVD algorithm.

Implementation Of Asymmetric Communication For Asynchronous Iteration By the MPMD Method On Distributed Memory Systems (분산 메모리 시스템에서의 MPMD 방식의 비동기 반복 알고리즘을 위한 비대칭 전송의 구현)

  • Park Pil-Seong
    • Journal of Internet Computing and Services
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    • v.4 no.5
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    • pp.51-60
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    • 2003
  • Asynchronous iteration is a way to reduce performance degradation of some parallel algorithms due to load imbalance or transmission delay between computing nodes, which requires asymmetric communication between the nodes of different speeds. To implement such asynchronous communication on distributed memory systems, we suggest an MPMD method that creates an additional separate server process on each computing node, and compare it with an SPMD method that creates a single process per node.

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Design of an efficient routing algorithm on the WK-recursive network

  • Chung, Il-Yong
    • Smart Media Journal
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    • v.11 no.9
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    • pp.39-46
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    • 2022
  • The WK-recursive network proposed by Vecchia and Sanges[1] is widely used in the design and implementation of local area networks and parallel processing architectures. It provides a high degree of regularity and scalability, which conform well to a design and realization of distributed systems involving a large number of computing elements. In this paper, the routing of a message is investigated on the WK-recursive network, which is key to the performance of this network. We present an efficient shortest path algorithm on the WK-recursive network, which is simpler than Chen and Duh[2] in terms of design complexity.