Pipelining parallel image compositing and delivery for efficient remote visualization

Qishi Wu, Jinzhu Gao, Zizhong Chen, Michelle Zhu

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

Scientific datasets of large volumes generated by next-generation computational sciences need to be transferred and processed for remote visualization and distributed collaboration among a geographically dispersed team of scientists. Parallel visualization using high-performance computing facilities is a typical approach to processing such increasingly large datasets. We propose an optimized image compositing scheme with linear pipeline and adaptive transport to support efficient image delivery to a remote client. The proposed scheme arranges an arbitrary number of parallel processors within a cluster in a linear order and divides the image into a carefully selected number of segments, which flow through the linear in-cluster pipeline and wide-area networks to the remote client consecutively. We analytically determine the segment size that minimizes the final image display time and derive the conditions where the proposed image compositing and delivery scheme outperforms the traditional schemes including the binary swap algorithm. In order to match the transport throughput for image delivery over wide-area networks to the pipelining rate for image compositing within the cluster, we design a class of transport protocols using stochastic approximation methods that are able to stabilize the data flow at a target rate. The experimental results from remote visualization of large-scale scientific datasets justify the correctness of our theoretical analysis and illustrate the superior performances of the proposed method.

Original languageEnglish
Pages (from-to)230-238
Number of pages9
JournalJournal of Parallel and Distributed Computing
Volume69
Issue number3
DOIs
StatePublished - 1 Mar 2009

Fingerprint

Pipelining
Wide area networks
Visualization
Pipelines
Display devices
Throughput
Network protocols
Transport Protocol
Computational Science
Parallel Processors
Processing
Stochastic Approximation
Swap
Stochastic Methods
Linear Order
Data Flow
Large Data Sets
Approximation Methods
Justify
Divides

Keywords

  • Image compositing
  • Parallel and distributed systems
  • Pipelining
  • Remote visualization
  • Transport control

Cite this

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Pipelining parallel image compositing and delivery for efficient remote visualization. / Wu, Qishi; Gao, Jinzhu; Chen, Zizhong; Zhu, Michelle.

In: Journal of Parallel and Distributed Computing, Vol. 69, No. 3, 01.03.2009, p. 230-238.

Research output: Contribution to journalArticle

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