Models and languages for parallel computation

Skillicorn, David B.; Talia, Domenico

doi:10.1145/280277.280278

Cited by 263 publications

(109 citation statements)

References 66 publications

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“…In practice, it is certainly possible to implement BSP programs using the traditional PVM [55] and MPI [45] libraries. A number of studies have shown that bulk-synchronous parallel algorithms lead to more efficient performance than their message-passing or shared-memory counterparts in many applications [61,62].…”

Section: Bsp and The Cost Modelmentioning

confidence: 99%

Distributed text search using suffix arrays

Arroyuelo¹,

Bonacic²,

Gil-Costa³

et al. 2014

Parallel Computing

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Text search is a classical problem in Computer Science, with many data-intensive applications. For this problem, suffix arrays are among the most widely known and used data structures, enabling fast searches for phrases, terms, substrings and regular expressions in large texts. Potential application domains for these operations include large-scale search services, such as Web search engines, where it is necessary to efficiently process intensive-traffic streams of on-line queries. This paper proposes strategies to enable such services by means of suffix arrays. We introduce techniques for deploying suffix arrays on clusters of distributed-memory processors and then study the processing of multiple queries on the distributed data structure. Even though the cost of individual search operations in sequential (non-distributed) suffix arrays is low in practice, the problem of processing multiple queries on distributed-memory systems, so that hardware resources are used efficiently, is relevant to services aimed at achieving high query throughput at low operational costs. Our theoretical and experimental performance studies show that our proposals are suitable solutions for building efficient and scalable on-line search services based on suffix arrays. IntroductionIn the last decade, the design of efficient data structures and algorithms for textual databases and related applications has received a great deal of attention, due to the rapid growth of the amount of text data available from different sources. Typical applications support text searches over big text collections in a client-server fashion, where the user queries are answered by a dedicated server [15]. The server efficiency-in terms of running time-is of paramount importance in cases where the services demanded by clients generate a heavy work load. A feasible way to overcome the limitations of sequential computers is to resort to the use of several computers, or processors, which work together to serve the ever increasing client demands [19].One such approach to efficient parallelization is to distribute the data onto the processors, in such a way that it becomes feasible to exploit locality via parallel processing of user requests, each on a subset of the data. As opposed to shared-memory models, this distributed-memory model provides the benefit of better * Corresponding author. Address: Av. España 1680, Valparaíso, Chile. Phone: +56 2 432 6722. Fax: +56 2 432 6702. , in distributed memory systems, and describes strategies to reduce the inter-processor communication and to improve the load balance at search time. Indexed Text SearchingThe advent of powerful processors and cheap storage has enabled alternative models for information retrieval, other than the traditional one of a collection of documents indexed by a fixed set of keywords. One is the full text model, in which the user expresses its information need via words, phrases or patterns to be matched for, and the information system retrieves those documents containing the user-specified pa...

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Section: Bsp and The Cost Modelmentioning

confidence: 99%

Distributed text search using suffix arrays

Arroyuelo¹,

Bonacic²,

Gil-Costa³

et al. 2014

Parallel Computing

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“…To identify concepts, we rely foremost on the overview given by two surveys [2,25] as our main subjects. They give a broad foundation but are dated.…”

Section: Selecting Subjects and Identifying Conceptsmentioning

confidence: 99%

“…Our survey is based on two surveys [2,25] and thus closely related to them. However, we are not aware on any survey or approach that enables a runtime system to directly support the semantics of multiple concurrency models.…”

Section: Related Workmentioning

confidence: 99%

Identifying a Unifying Mechanism for the Implementation of Concurrency Abstractions on Multi-language Virtual Machines

Marr

D'Hondt

2012

Objects, Models, Components, Patterns

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Abstract. Supporting all known abstractions for concurrent and parallel programming in a virtual machines (VM) is a futile undertaking, but it is required to give programmers appropriate tools and performance. Instead of supporting all abstractions directly, VMs need a unifying mechanism similar to INVOKEDYNAMIC for JVMs. Our survey of parallel and concurrent programming concepts identifies concurrency abstractions as the ones benefiting most from support in a VM. Currently, their semantics is often weakened, reducing their engineering benefits. They require a mechanism to define flexible language guarantees. Based on this survey, we define an ownership-based meta-object protocol as candidate for VM support. We demonstrate its expressiveness by implementing actor semantics, software transactional memory, agents, CSP, and active objects. While the performance of our prototype confirms the need for VM support, it also shows that the chosen mechanism is appropriate to express a wide range of concurrency abstractions in a unified way.

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“…Furthermore, the description of the application should be at the correct abstraction level to perform the required analysis [KNRSV00]. A comprehensive survey of models for parallel computations used in different application domains and at different abstraction levels is given in [ST98]. The most interesting models for our application domain, streaming multimedia systems, are the dataflow models.…”

Section: Related Workmentioning

confidence: 99%