The proceedings contains 32 papers from the 9th annualacmsymposium on parallelalgorithms and architectures. Topics discussed include: Cilk programs;parallel scheduling algorithms;reactive diffracting trees;load bal...
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The proceedings contains 32 papers from the 9th annualacmsymposium on parallelalgorithms and architectures. Topics discussed include: Cilk programs;parallel scheduling algorithms;reactive diffracting trees;load balancing and data remapping for adaptive grid calculations;spectral partitioners;three-dimensional pattern matching;matrix-factorization algorithms;shared-memory models;fault-prone Bulk-Synchronous parallel (BSP) machines;parallel bandwidth;external memory algorithms;system area network mapping;multi-class routing algorithms;interconnection networks;deadlock-free oblivious wormhole routing algorithms;all-optical networks;approximation algorithms;fine-grain multithreading;speculative retirement and instruction windows.
We prove a number of negative results about practical (i.e., numerically accurate) algorithms for certain matrix factorizations. In particular, we prove that the popular Givens' method for computing the QR decompo...
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ISBN:
(纸本)9780897918909
We prove a number of negative results about practical (i.e., numerically accurate) algorithms for certain matrix factorizations. In particular, we prove that the popular Givens' method for computing the QR decomposition is inherently sequential over the realistic model of floating point arithmetic. We also prove a number of additional results concerning Gaussian Elimination for computing the LU decomposition. Altogether, the results of this paper support the widespread belief that there is a tradeoff between parallelism and accuracy in numerical algorithms.
Recently there has been an increasing interest in models of parallel computation that account for the bandwidth limitations in communication networks. Some models (e.g., BSP and LOGP) account for bandwidth limitations...
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Recently there has been an increasing interest in models of parallel computation that account for the bandwidth limitations in communication networks. Some models (e.g., BSP and LOGP) account for bandwidth limitations using a per-processor parameter g>1, such that each processor can send/receive at most h messages in g·h time. Other models (e.g., PRAM(m)) account for bandwidth limitations as an aggregate parameter mΩ(√lg p) separation known previously.
This paper describes the derivation of an empirically efficient parallel two-dimensional Delaunay triangulation program from a theoretically efficient CREW PRAM algorithm. Compared to previous work, the resulting impl...
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ISBN:
(纸本)9780897918909
This paper describes the derivation of an empirically efficient parallel two-dimensional Delaunay triangulation program from a theoretically efficient CREW PRAM algorithm. Compared to previous work, the resulting implementation is not limited to datasets with a uniform distribution of points, achieves significantly better speedups over good serial code, and is widely portable due to its use of MPI as a communication mechanism. Results are presented for a loosely-coupled cluster of workstations, a distributed-memory multicomputer, and a shared-memory multiprocessor. The Machiavelli toolkit used to transform the nested data parallelism inherent in the divide-and-conquer algorithm into achievable task and data parallelism is also described and compared to previous techniques.
An earlier parallel list ranking algorithm performs well for problem sizes N that are extremely large in comparison to the number of PUs P. However, no existing algorithm gives good performance for reasonable loads. W...
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ISBN:
(纸本)9780897918909
An earlier parallel list ranking algorithm performs well for problem sizes N that are extremely large in comparison to the number of PUs P. However, no existing algorithm gives good performance for reasonable loads. We present a novel family of algorithms, that achieve a better trade-off between the number of start-ups and the routing volume. We have implemented them on an Intel Paragon, and they turn out to considerably outperform all earlier algorithms: with P = 2 the sequential algorithm is already beaten for N = 25,000;for P = 100 and N = 107, the speed-up is 21, and for N = 108 it even reaches 30. A modification of one of our algorithms solves a theoretical question: we show that on one-dimensional processor arrays, list ranking can be solved with a number of steps equal to the diameter of the network.
It is well known that simple randomized load balancing schemes can balance load effectively while incurring only a small overhead, making such schemes appealing for practical systems. In this paper, we provide new ana...
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ISBN:
(纸本)9780897918909
It is well known that simple randomized load balancing schemes can balance load effectively while incurring only a small overhead, making such schemes appealing for practical systems. In this paper, we provide new analyses for several such dynamic randomized load balancing schemes. Unlike previous analyses, we do not assume that in equilibrium each server is stochastically independent from other servers. Our work extends a previous analysis of the supermarket model, a model that abstracts a simple, efficient load balancing scheme in the setting where jobs arrive at a large system of parallel processors. In this model, customers arrive at a system of n servers as a Poisson stream of rate λn, λ
External memory (EM) algorithms are designed for computational problems in which the size of the internal memory of the computer is only a small fraction of the problem size. For certain large scale applications this ...
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ISBN:
(纸本)9780897918909
External memory (EM) algorithms are designed for computational problems in which the size of the internal memory of the computer is only a small fraction of the problem size. For certain large scale applications this is necessarily true. Typically, the cost models proposed for external memory algorithms have measured only the number of I/O operations, and the algorithms have been specially crafted for the EM situation. In the past, several attempts have been made to relate the large body of work based on parallelalgorithms to EM, but with limited success. In this paper we provide simulation techniques which produce efficient EM algorithms from efficient algorithms developed under BSP-like parallel computing models. Our techniques can accommodate one or multiple processors on the EM target machine, each with one or more disks, and they also adapt to the disk blocking factor of the target machine. In addition to the main simulation result we obtain a more comprehensive cost model for EM algorithms, which considers the total costs incurred by the algorithm including computation, I/O and communication costs.
We present a parallel algorithm on a CRCW PRAM for three-dimensional pattern matching, i.e., finding all occurrences of a pattern of size m3 in a text of size n3. The text search of the algorithm is alphabet-independe...
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ISBN:
(纸本)9780897918909
We present a parallel algorithm on a CRCW PRAM for three-dimensional pattern matching, i.e., finding all occurrences of a pattern of size m3 in a text of size n3. The text search of the algorithm is alphabet-independent and runs in optimal constant time. The preprocessing computes a witness array for the pattern, and it runs in O(log m) time using m3 processors. The witness computation uses multilayer suffix trees and it works for any dimensions. Our result is based on a new characterization of three-dimensional periodicity. The parallel algorithm can be translated into a sequential algorithm for three-dimensional pattern matching whose text search is alphabet-independent and runs in O(n3) time and whose preprocessing runs in O(m3 log σ) time, where σ = min(|Σ|, m3) and Σ is the alphabet of symbols.
Mesh adaption is a powerful tool for efficient unstructured-grid computations but causes load imbalance among processors on a parallel machine. We present a novel method to dynamically balance the processor workloads ...
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ISBN:
(纸本)9780897918909
Mesh adaption is a powerful tool for efficient unstructured-grid computations but causes load imbalance among processors on a parallel machine. We present a novel method to dynamically balance the processor workloads with a global view. This paper presents, for the first time, the implementation and integration of all major components within our dynamic load balancing strategy for adaptive grid calculations. Mesh adaption, repartitioning, processor assignment, and remapping are critical components of the framework that must be accomplished rapidly and efficiently so as not to cause a significant overhead to the numerical simulation. Previous results indicated that mesh repartitioning and data remapping are potential bottlenecks for performing large-scale scientific calculations. We resolve these issues and demonstrate that our framework remains viable on a large number of processors.
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