Scheduling multiple data visualization query workloads on a shared memory machine

H. Andrade; T. Kurc; A. Sussman; J. Saltz

doi:10.1109/IPDPS.2002.1015482

Scheduling multiple data visualization query workloads on a shared memory machine

H. Andrade
, T. Kurc
, A. Sussman
, J. Saltz

Biomedical Informatics

University of Maryland, College Park

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

11 Scopus citations

Abstract

Query scheduling plays an important role when systems are faced with limited resources and high workloads. It becomes even more relevant for servers applying multiple query optimization techniques to batches of queries, in which portions of datasets as well as intermediate results are maintained in memory to speed up query evaluation. We present a dynamic query scheduling model based on a priority queue implementation using a directed graph and a strategy for ranking queries. We examine the relative performance of several ranking strategies on a shared-memory machine using two different versions of an application, called the Virtual Microscope, for browsing digitized microscopy images.

Original language	English
Title of host publication	Proceedings - International Parallel and Distributed Processing Symposium, IPDPS 2002
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	102-109
Number of pages	8
ISBN (Electronic)	0769515738, 9780769515731
DOIs	https://doi.org/10.1109/IPDPS.2002.1015482
State	Published - 2002
Event	16th International Parallel and Distributed Processing Symposium, IPDPS 2002 - Ft. Lauderdale, United States Duration: Apr 15 2002 → Apr 19 2002

Publication series

Name	Proceedings - International Parallel and Distributed Processing Symposium, IPDPS 2002

Conference

Conference	16th International Parallel and Distributed Processing Symposium, IPDPS 2002
Country/Territory	United States
City	Ft. Lauderdale
Period	04/15/02 → 04/19/02

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10.1109/IPDPS.2002.1015482

Cite this

Andrade, H., Kurc, T., Sussman, A., & Saltz, J. (2002). Scheduling multiple data visualization query workloads on a shared memory machine. In Proceedings - International Parallel and Distributed Processing Symposium, IPDPS 2002 (pp. 102-109). Article 1015482 (Proceedings - International Parallel and Distributed Processing Symposium, IPDPS 2002). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IPDPS.2002.1015482

Andrade, H. ; Kurc, T. ; Sussman, A. et al. / Scheduling multiple data visualization query workloads on a shared memory machine. Proceedings - International Parallel and Distributed Processing Symposium, IPDPS 2002. Institute of Electrical and Electronics Engineers Inc., 2002. pp. 102-109 (Proceedings - International Parallel and Distributed Processing Symposium, IPDPS 2002).

@inproceedings{a461be470ca34031b851f0d8e351371f,

title = "Scheduling multiple data visualization query workloads on a shared memory machine",

abstract = "Query scheduling plays an important role when systems are faced with limited resources and high workloads. It becomes even more relevant for servers applying multiple query optimization techniques to batches of queries, in which portions of datasets as well as intermediate results are maintained in memory to speed up query evaluation. We present a dynamic query scheduling model based on a priority queue implementation using a directed graph and a strategy for ranking queries. We examine the relative performance of several ranking strategies on a shared-memory machine using two different versions of an application, called the Virtual Microscope, for browsing digitized microscopy images.",

author = "H. Andrade and T. Kurc and A. Sussman and J. Saltz",

note = "Publisher Copyright: {\textcopyright} 2002 IEEE.; 16th International Parallel and Distributed Processing Symposium, IPDPS 2002 ; Conference date: 15-04-2002 Through 19-04-2002",

year = "2002",

doi = "10.1109/IPDPS.2002.1015482",

language = "English",

series = "Proceedings - International Parallel and Distributed Processing Symposium, IPDPS 2002",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "102--109",

booktitle = "Proceedings - International Parallel and Distributed Processing Symposium, IPDPS 2002",

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Andrade, H, Kurc, T, Sussman, A & Saltz, J 2002, Scheduling multiple data visualization query workloads on a shared memory machine. in Proceedings - International Parallel and Distributed Processing Symposium, IPDPS 2002., 1015482, Proceedings - International Parallel and Distributed Processing Symposium, IPDPS 2002, Institute of Electrical and Electronics Engineers Inc., pp. 102-109, 16th International Parallel and Distributed Processing Symposium, IPDPS 2002, Ft. Lauderdale, United States, 04/15/02. https://doi.org/10.1109/IPDPS.2002.1015482

Scheduling multiple data visualization query workloads on a shared memory machine. / Andrade, H.; Kurc, T.; Sussman, A. et al.
Proceedings - International Parallel and Distributed Processing Symposium, IPDPS 2002. Institute of Electrical and Electronics Engineers Inc., 2002. p. 102-109 1015482 (Proceedings - International Parallel and Distributed Processing Symposium, IPDPS 2002).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Sussman, A.

AU - Saltz, J.

PY - 2002

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N2 - Query scheduling plays an important role when systems are faced with limited resources and high workloads. It becomes even more relevant for servers applying multiple query optimization techniques to batches of queries, in which portions of datasets as well as intermediate results are maintained in memory to speed up query evaluation. We present a dynamic query scheduling model based on a priority queue implementation using a directed graph and a strategy for ranking queries. We examine the relative performance of several ranking strategies on a shared-memory machine using two different versions of an application, called the Virtual Microscope, for browsing digitized microscopy images.

AB - Query scheduling plays an important role when systems are faced with limited resources and high workloads. It becomes even more relevant for servers applying multiple query optimization techniques to batches of queries, in which portions of datasets as well as intermediate results are maintained in memory to speed up query evaluation. We present a dynamic query scheduling model based on a priority queue implementation using a directed graph and a strategy for ranking queries. We examine the relative performance of several ranking strategies on a shared-memory machine using two different versions of an application, called the Virtual Microscope, for browsing digitized microscopy images.

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DO - 10.1109/IPDPS.2002.1015482

M3 - Conference contribution

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T3 - Proceedings - International Parallel and Distributed Processing Symposium, IPDPS 2002

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EP - 109

BT - Proceedings - International Parallel and Distributed Processing Symposium, IPDPS 2002

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 16th International Parallel and Distributed Processing Symposium, IPDPS 2002

Y2 - 15 April 2002 through 19 April 2002

ER -

Andrade H, Kurc T, Sussman A, Saltz J. Scheduling multiple data visualization query workloads on a shared memory machine. In Proceedings - International Parallel and Distributed Processing Symposium, IPDPS 2002. Institute of Electrical and Electronics Engineers Inc. 2002. p. 102-109. 1015482. (Proceedings - International Parallel and Distributed Processing Symposium, IPDPS 2002). doi: 10.1109/IPDPS.2002.1015482

Scheduling multiple data visualization query workloads on a shared memory machine

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