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Dual BEM for crack growth analysis on distributed-memory multiprocessors

ADVANCES IN ENGINEERING SOFTWARE 2000年第12期31卷 921-927页

作者： González, P Pena, TF Cabaleiro, JC Rivera, FF Univ Santiago de Compostela Dept Elect & Comp Sci Santiago De Compostela 15706 Spain

The Dual Boundary Element Method (DBEM) has been presented as an effective numerical technique for the analysis of linear elastic crack problems [Portela A, Aliabadi MH. The dual boundary element method: effective implementation for crack problems. Int J Num Meth Engng 1992;33:1269-1287]. Analysis of large structural integrity problems may need the use of large computational resources, both in terms of CPU time and memory requirements. This paper reports a message-passing implementation of the DEEM formulation dealing with the analysis of crack growth in structures. We have analyzed the construction of the system and its resolution. Different data distribution techniques have been studied with several problems. Results in terms of scalability and load balance for these two stages are presented in this paper. (C) 2000 Civil-Comp Ltd. and Elsevier Science Ltd. All rights reserved.

关键词： dual boundary element method cracks in structures distribution techniques distributed-memory multiprocessors message-passing interface

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Parallel solution of sparse linear least squares problems on distributed-memory multiprocessors

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PARALLEL COMPUTING 1997年第13期23卷 2075-2093页

作者： Sun, CG Cornell Univ Cornell Theory Ctr Adv Comp Res Inst Ithaca NY 14853 USA

This paper studies the parallel solution of large-scale sparse linear least squares problems on distributed-memory multiprocessors. The key components required for solving a sparse linear least squares problem are sparse QR factorization and sparse triangular solution. A block-oriented parallel algorithm for sparse QR factorization has already been described in the literature. In this paper, new block-oriented parallel algorithms for sparse triangular solution are proposed. The arithmetic and communication complexities of the new algorithms applied to regular grid problems are analysed. The proposed parallel sparse triangular solution algorithms together with the block-oriented parallel sparse QR factorization algorithm result in a highly efficient approach to the parallel solution of sparse linear least squares problems. Performance results obtained on an IBM Scalable POWERparallel system SP2 are presented. The largest least squares problem solved has over two million rows and more than a quarter million columns. The execution speed for the numerical factorization of this problem achieves over 3.7 gigaflops per second on an IBM SP2 machine with 128 processor. (C) 1997 Elsevier Science B.V.

关键词： parallel algorithms sparse matrix orthogonal factorization multifrontal method least squares problems triangular solution distributed-memory multiprocessors

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Parallel sparse orthogonal factorization on distributed-memory multiprocessors

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SIAM JOURNAL ON SCIENTIFIC COMPUTING 1996年第3期17卷 666-685页

作者： Sun, CG Adv. Computing Research Institute Cornell Theory Center Cornell University Ithaca NY 14853-3801 United States

In this paper,we propose anew parallel multifrontal algorithm for the orthogonal factorization of large sparse matrices on distributed-memory multiprocessors. We explore the use of block partitioning schemes in parallel sparse orthogonal factorization. Our block-oriented parallel algorithm for sparse orthogonal factorization achieves high performance by incurring strictly less communication overhead than the conventional nonblock algorithm, maintaining relatively balanced load distribution among processors, and accelerating the parallel numerical kernel via increased cache utilization. We analyze the performance of our parallel algorithm and present its arithmetic and communication complexities for regular grid problems. We report the experimental results of an implementation of our parallel algorithm on an Intel iPSC/860 machine. Through our theoretical analysis and experimental results, we demonstrate that our new block-oriented algorithm outperforms the conventional nonblock algorithm impressively.

关键词： parallel algorithms sparse matrix orthogonal factorization multifrontal method block partitioning scheme distributed-memory multiprocessors

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RELIABLE BUTTERFLY distributed-memory multiprocessors

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IEEE TRANSACTIONS ON COMPUTERS 1994年第9期43卷 1004-1013页

作者： TZENG, NF Center for Adv. Comput. Studies Southwestern Louisiana Univ. Lafayette LA USA Abstract Authors References Cited By Keywords Metrics Similar Download Citation Email Print Request Permissions

Since the butterfly network possesses various attractive topological properties and its constituent node has a fixed degree, independent of the system size, interconnecting processors in accordance with the butterfly topology to construct a distributed-memory multiprocessor is advantageous, especially for a large sized system. Every butterfly node in a multiprocessor so constructed is a processor, not simply a switch. In this paper, we examine a reliable butterfly-based multiprocessor that preserves its full rigid butterfly configuration even in the presence of faults. The proposed butterfly parallel system can tolerate any single and many multiple node/link failures, giving rise to significantly improved reliability. Reconfiguration in response to an operational fault in our design is easy and may be performed in a distributed manner. A system after reconfiguration is ensured to provide the same high performance. Reliability results show that our design compares favorably with an earlier design. An extension to this reliable design is also addressed.

关键词： BUTTERFLY NETWORK SYSTEMS distributed-memory multiprocessors FAULT-TOLERANCE RECONFIGURATION PROCEDURES RELIABILITY EVALUATION

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Performing BMMC permutations efficiently on distributed-memory multiprocessors with MPI

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ALGORITHMICA 1999年第3-4期24卷 349-370页

作者： Cormen, TH Clippinger, JC Dartmouth Coll Dept Comp Sci Hanover NH 03755 USA

This paper presents an architecture independent method for performing BMMC permutations on multiprocessors with distributed memory. All interprocessor communication uses the MPI function *** () The number of elements and number of processors must he powers of 2, with at least one element per processor, and there is no inherent upper bound on the ratio of elements per processor. Our method transmits only data without transmitting any source or target indices, which conserves network bandwidth. When data is transmitted, the source and target processors implicitly agree on each other's identity and the indices of the elements being transmitted. A C-callable implementation of our method is available from Netlib. The implementation allows preprocessing (which incurs a modest cost) to he factored out for multiple runs of the same permutation, even if on different data. Data may be laid out in any one of several ways: processor-major, processor-minor, or anything in between. Experimental results indicate that our method works well compared with several other candidate methods on three different platforms. In particular, the slower the interconnection network, the greater the relative advantage of our method.

关键词： BMMC permutations affine transformations distributed-memory multiprocessors MPI

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PARALLEL SOLUTION OF TRIANGULAR SYSTEMS ON distributed-memory multiprocessors

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SIAM JOURNAL ON SCIENTIFIC AND STATISTICAL COMPUTING 1988年第3期9卷 558-588页

作者： HEATH, MT ROMINE, CH

Several parallel algorithms are presented for solving triangular systems of linear equations on distributed-memory multiprocessors. New wavefront algorithms are developed for both row-oriented and column-oriented matrix storage. Performance of the new algorithms and several previously proposed algorithms is analyzed theoretically and illustrated empirically using implementations on commercially available hypercube multiprocessors.

关键词： 65F 65W triangular systems parallel algorithms distributed-memory multiprocessors

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MODIFIED CYCLIC ALGORITHMS FOR SOLVING TRIANGULAR SYSTEMS ON distributed-memory multiprocessors

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SIAM JOURNAL ON SCIENTIFIC AND STATISTICAL COMPUTING 1988年第3期9卷 589-600页

作者： EISENSTAT, SC HEATH, MT HENKEL, CS ROMINE, CH OAK RIDGE NATL LAB MATH SCI SECTOAK RIDGETN 37831 N CAROLINA STATE UNIV DEPT NUCL ENGNRALEIGHNC 27695

New parallel algorithms and comparative test results are given for solving triangular systems of linear equations on distributed-memory multiprocessors. These results supplement those given in a previous paper. All of the new algorithms are variations on the cyclic algorithms discussed previously. The new algorithms are shown to provide substantial performance improvements.

关键词： 65F 65W triangular systems parallel algorithms distributed-memory multiprocessors

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Combining static and dynamic scheduling on distributed-memory multiprocessors 94

Combining static and dynamic scheduling on distributed-memor...

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Proceedings of the 1994 International Conference on Supercomputing

作者： Plata, O. Rivera, F.F. Dept. Electrónica y Computación University of Santiago de Compostela E-15706 Santiago de Compostela SPAIN

ISBN: (纸本)9780897916653

Loops are a large source of parallelism for many numerical applications. An important issue in the parallel execution of loops is how to schedule them so that the workload is well balanced among the processors. Most existing loop scheduling algorithms were designed for shared-memory multiprocessors, with uniform memory access costs. These approaches are not suitable for distributed-memory multiprocessors where data locality is a major concern and communication costs are high. This paper presents a new scheduling algorithm in which data locality is taken into account. Our approach combines both worlds, static and dynamic scheduling, in a two-level (overlapped) fashion. This way data locality is considered and communication costs are limited. The performance of the new algorithm is evaluated on a CM-5 message-passing distributed-memory multiprocessor.

关键词： loop scheduling dynamic and static scheduling distributed-memory multiprocessors load balancing message-passing

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AN ALGORITHM FOR FIFO MESSAGE DELIVERY AMONG MIGRATING TASKS

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INFORMATION PROCESSING LETTERS 1995年第5期53卷 261-267页

作者： BARBOSA, VC PORTO, SCS UFF DEPT ENGN TELCOMUNBR-24220 NITEROIRJBRAZIL PUC RJ DEPT INFORMATBR-22453900 RIO JANEIROBRAZIL

We consider distributed-memory parallel machines that support the FIFO delivery of messages among processors, and present an asynchronous distributed algorithm that ensures the FIFO delivery of messages among tasks that migrate in such machines. For the concurrent migration of a set K of tasks, the algorithm requires O(nm(K)) interprocessor messages and O(n) time to run, where n is the number of processors in the system and m(K), is the number of pairs of communicating tasks involving the migrating tasks. However, for a great number of current distributed-memory architectures, these complexities can be reduced to O(m(K)) and O(1), respectively.

关键词： distributed COMPUTING distributed-memory multiprocessors MESSAGE-PASSING PROGRAMS TASK MIGRATION FIFO MESSAGE DELIVERY

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Low-cost task scheduling for distributed-memory machines

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IEEE TRANSACTIONS ON PARALLEL AND distributed SYSTEMS 2002年第6期13卷 648-658页

作者： Radulescu, A van Gemund, AJC Philips Res Labs Eindhoven Netherlands Delft Univ Technol NL-2600 AA Delft Netherlands

In compile-time task scheduling for distributed-memory systems, list scheduling is generally accepted as an attractive approach since it pairs low cost with good results. List scheduling algorithms schedule tasks in order of their priority. This priority can be computed either 1) statically, before the scheduling, or 2) dynamically, during the scheduling. In this paper, we show that list scheduling with statically computed priorities can be performed at a significantly lower cost than existing approaches, without sacrificing performance. Our approach is general, i.e., it can be applied to any list scheduling algorithm with static priorities. The low-complexity is achieved by using low-complexity methods for the most time consuming parts in list scheduling algorithms, i.e., processor selection and task selection, preserving the criteria used in the original algorithms. We exemplify our method by applying it to the MCP algorithm. Using an extension of this method, we can also reduce the time complexity of a particular class of list scheduling with dynamic priorities (including algorithms such as DLS, ETF, or ERT). Our results confirm that the modified versions of the list scheduling algorithms obtain a performance comparable to their original versions, yet at a significantly lower cost. We also show that the modified versions of the list scheduling algorithms consistently outperform multistep algorithms, such as DSC-LLB, which also have higher complexity and clearly outperform algorithms in the same class of complexity, such as CPM.

关键词： compile-time task scheduling list scheduling dataflow graphs distributed-memory multiprocessors

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