Title

Queering Buddhism Or Buddhist De-Queering?: Reflecting On Differences Amongst Western Lgbtqi Buddhists And The Limits Of Liberal Convert Buddhism

Keywords

Computation Sharing; Continuous Query; Graphical Processing Unit (GPU); kNN; Location-Based Services; Mobile Database Systems; Parallel Processing; Performance Model; Range Query; Spatio-Temporal Data Streams

Abstract

The efficient processing of spatio-temporal data streams is an area of intense research. However, all methods rely on an unsuitable processor (Govindaraju, 2004), namely a CPU, to evaluate concurrent, continuous spatio-temporal queries over these data streams. This paper presents a performance model of the execution of spatio-temporal queries over the authors' GEDS framework (Cazalas & Guha, 2010). GEDS is a scalable, Graphics Processing Unit (GPU)-based framework, employing computation sharing and parallel processing paradigms to deliver scalability in the evaluation of continuous, spatio-temporal queries over spatio temporal data streams. Experimental evaluation shows the scalability and efficacy of GEDS in spatio-temporal data streaming environments and demonstrates that, despite the costs associated with memory transfers, the parallel processing power provided by GEDS clearly counters and outweighs any associated costs. To move beyond the analysis of specific algorithms over the GEDS framework, the authors developed an abstract performance model, detailing the relationship of the CPU and the GPU. From this model, they are able to extrapolate a list of attributes common to successful GPU-based applications, thereby providing insight into which algorithms and applications are best suited for the GPU and also providing an estimated theoretical speedup for said GPU-based applications. © 2012, IGI Global. All rights reserved.

Publication Date

1-1-2012

Publication Title

Theology and Sexuality

Volume

18

Issue

3

Number of Pages

198-214

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1179/1355835813Z.00000000015

Socpus ID

85002586910 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85002586910

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