Scheduling problems that are critical and prevalent in practical parallel computing are computed. A polynomial time makespan algorithm that produces a schedule of length O(V+Φ log T), which is therefore an O(log T) a...
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ISBN:
(纸本)9780897918091
Scheduling problems that are critical and prevalent in practical parallel computing are computed. A polynomial time makespan algorithm that produces a schedule of length O(V+Φ log T), which is therefore an O(log T) approximation is presented to solve these problems. The makespan algorithm can be extended to minimize the weighted average completion time over all the jobs to the same approximation factor of O(log T).
We describe a randomized CRCW PRAM algorithm that finds a minimum spanning forest of an n-vertex graph in O(log n) time and linear work. This shaves a factor of 2log* n off the best previous running time for a linear-...
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ISBN:
(纸本)9780897918091
We describe a randomized CRCW PRAM algorithm that finds a minimum spanning forest of an n-vertex graph in O(log n) time and linear work. This shaves a factor of 2log* n off the best previous running time for a linear-work algorithm. The novelty in our approach is to divide the computation into two phases, the first of which finds only a partial solution. This idea has been used previously in parallel connected components algorithms.
The goal of the μDatabase project is to understand the behaviour of data structures and their algorithms, both parallel and sequential, in a memory-mapped environment. Memory mapping allows primary-memory pointer-bas...
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The goal of the μDatabase project is to understand the behaviour of data structures and their algorithms, both parallel and sequential, in a memory-mapped environment. Memory mapping allows primary-memory pointer-based data structures to be stored on secondary storage, and subsequently traversed and modified, without transforming the embedded pointers. The project incorporates a collaboration between practitioners and theoreticians and has produced a toolkit to support a parallel memory-mapped environment, extensive concurrency tools, an analytical model for the system validated by experiments, and preliminary results involving parallel database join algorithms as well as sequential B-tree and R-tree data structures. Future work includes augmenting the toolkit, developing and testing more parallelalgorithms tuned for efficiency in a memory-mapped environment, and extending the current model to cover more general algorithms and capture more low-level details of the physical machine.
The methods for mitigating the degradation in performance caused by high latencies in parallel and distributed networks were described. Most of the analysis were centered on the simulation of unit-delay rings on netwo...
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The methods for mitigating the degradation in performance caused by high latencies in parallel and distributed networks were described. Most of the analysis were centered on the simulation of unit-delay rings on networks of workstations (NOWs) with arbitrary delays on the links. Emulations were also derived for the wide variety of other unit-delay network architectures on a NOW with high-latency links. The lower bounds that established limits on the degree to which the high latency links were proven, can be mitigated. These bounds demonstrates that overcoming latencies in dataflow types of computations that require access to large local databases is easier.
We describe a very simple deterministic parallel algorithm for linear programming in fixed dimension d that takes poly(log log n) time in the common CRCW PRAM model and does optimal O(n) work. Our algorithm is based o...
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ISBN:
(纸本)9780897918091
We describe a very simple deterministic parallel algorithm for linear programming in fixed dimension d that takes poly(log log n) time in the common CRCW PRAM model and does optimal O(n) work. Our algorithm is based on multidimensional search and an effective use of approximation algorithms to speed-up the basic search in the CRCW model. Our method also yields very fast poly(log log n) algorithm for smallest enclosing sphere and approximate ham-sandwich cuts as well as an O(log n) time work-optimal algorithm for exact ham-sandwich cuts of separable point sets. For all these problems, particularly for the fixed-dimensional linear programming, o(log n) time efficient deterministic PRAM algorithms were not known until very recently.
The Bulk-Synchronous parallel (BSP) model was proposed by Valiant as a model for general-purpose parallel computation. The objective of the model is to allow the design of parallel programs that can be executed effici...
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The Bulk-Synchronous parallel (BSP) model was proposed by Valiant as a model for general-purpose parallel computation. The objective of the model is to allow the design of parallel programs that can be executed efficiently on a variety of architectures. While many theoretical arguments in support of the BSP model have been presented, the degree to which the model can be efficiently utilized on existing parallel machines remains unclear. To explore this question, we implemented s small library of BSP functions, called the Green BSP library, on several parallel platforms. We also created a number of parallel applications based on this library. Here, we report on the performance of six of these applications on three different parallel platforms. Our preliminary results suggest that the BSP model can be used to develop efficient and portable programs for a range of machines and applications.
Gang scheduling is a resource management scheme for parallel and distributed systems that combines time-sharing with space-sharing to ensure short response times for interactive tasks and high overall system throughpu...
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Gang scheduling is a resource management scheme for parallel and distributed systems that combines time-sharing with space-sharing to ensure short response times for interactive tasks and high overall system throughput. In this paper, we present and analyze a queueing theoretic model for a general gang scheduling scheme that forms the basis of a multiprogramming environment currently being developed for IBM's SP2 parallel system and for clusters of workstations. Our model and analysis can be used to tune our scheduler in order to maximize its performance on each hardware platform.
A quantitative comparison of the BSP and LogP models for parallel computation is developed. Very efficient cross simulations between the two models are derived, showing their substantial equivalence for algorithmic de...
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ISBN:
(纸本)9780897918091
A quantitative comparison of the BSP and LogP models for parallel computation is developed. Very efficient cross simulations between the two models are derived, showing their substantial equivalence for algorithmic design guided by asymptotic analysis. It is also shown that the two models can be implemented with similar performance on most point-to-point networks. In conclusion, within the limits of our analysis that is mainly of asymptotic nature, BSP and LogP can be viewed as closely related variants within the bandwidth-latency framework for modeling parallel computation. BSP seems somewhat preferable due to greater simplicity and portability, and slightly greater power.
This paper experimentally validates performance related issues for parallel computation models on several parallel platforms (a MasPar MP-1 with 1024 processors, a 64-node GCel and a CM-5 of 64 processors). Our work c...
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This paper experimentally validates performance related issues for parallel computation models on several parallel platforms (a MasPar MP-1 with 1024 processors, a 64-node GCel and a CM-5 of 64 processors). Our work consists of three parts. First, there is an evaluation part in which we investigate whether the models correctly predict the execution time of an algorithm implementation. Unlike previous work, which mostly demonstrated a close match between the measured and predicted running times, this paper shows that there are situations in which the models do not precisely predict the actual execution time of an algorithm implementation. Second, there is a comparison part in which the models are contrasted with each other in order to determine which model induces the fastest algorithms. Finally, there is an efficiency validation part in which the performance of the model derived algorithms are compared with the performance of highly optimized library routines to show the effectiveness of deriving fast algorithms through the formalisms of the models.
NEighborhood MOdeling (NEMO) provides transparent parallelism to develop parallel spatial data processing. It addresses the following parallel issues: architecture and machine independence;communication bottlenecks;da...
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NEighborhood MOdeling (NEMO) provides transparent parallelism to develop parallel spatial data processing. It addresses the following parallel issues: architecture and machine independence;communication bottlenecks;data visualization;casualty errors;load balancing;and data coherence. NEMO is capable of processing three types of time consuming raster neighborhood models: cellular automata;propagation;and neighborhood analysis. NEMO achieves this flexibility by including five components to its design: the three application drivers such as the cellular automata driver, propagation driver, and neighborhood analysis automata driver;and the display manager and raster database manager.
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