A configurable algorithm for parallel image-compositing applications

Collective communication operations can dominate the cost of large-scale parallel algorithms. Image compositing in parallel scientific visualization is a reduction operation where this is the case. We present a new algorithm called Radix-k that in many cases performs better than existing compositing...

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Published in:Proceedings of the Conference on High Performance Computing Networking, Storage and Analysis pp. 1 - 10
Main Authors: Peterka, Tom, Goodell, David, Ross, Robert, Shen, Han-Wei, Thakur, Rajeev
Format: Conference Proceeding
Language:English
Published: New York, NY, USA ACM 14.11.2009
Series:ACM Conferences
Subjects:
Bandwidth
communication
Costs
Government
image compositing
Information systems > Information systems applications
Libraries
Lower bound
Optimization
parallel scientific visualization
Pipelines
Program processors
Rendering (computer graphics)
Vectors
communication
parallel scientific visualization
image compositing
ISBN:1605587443, 9781605587448
ISSN:2167-4329
Online Access:Get full text
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Abstract Collective communication operations can dominate the cost of large-scale parallel algorithms. Image compositing in parallel scientific visualization is a reduction operation where this is the case. We present a new algorithm called Radix-k that in many cases performs better than existing compositing algorithms. It does so through a set of configurable parameters, the radices, that determine the number of communication partners in each message round. The algorithm embodies and unifies binary swap and direct-send, two of the best-known compositing methods, and enables numerous other configurations through appropriate choices of radices. While the algorithm is not tied to a particular computing architecture or network topology, the selection of radices allows Radix-k to take advantage of new supercomputer interconnect features such as multiporting. We show scalability across image size and system size, including both powers of two and nonpowers-of-two process counts.
AbstractList Collective communication operations can dominate the cost of large-scale parallel algorithms. Image compositing in parallel scientific visualization is a reduction operation where this is the case. We present a new algorithm called Radix-k that in many cases performs better than existing compositing algorithms. It does so through a set of configurable parameters, the radices, that determine the number of communication partners in each message round. The algorithm embodies and unifies binary swap and direct-send, two of the best-known compositing methods, and enables numerous other configurations through appropriate choices of radices. While the algorithm is not tied to a particular computing architecture or network topology, the selection of radices allows Radix-k to take advantage of new supercomputer interconnect features such as multiporting. We show scalability across image size and system size, including both powers of two and nonpowers-of-two process counts.
Author Goodell, David
Thakur, Rajeev
Shen, Han-Wei
Peterka, Tom
Ross, Robert
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  fullname: Shen, Han-Wei
  organization: The Ohio State University
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  givenname: Rajeev
  surname: Thakur
  fullname: Thakur, Rajeev
  organization: Argonne National Laboratory
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Keywords communication
parallel scientific visualization
image compositing
Language English
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Snippet Collective communication operations can dominate the cost of large-scale parallel algorithms. Image compositing in parallel scientific visualization is a...
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SubjectTerms Bandwidth
communication
Costs
Government
image compositing
Information systems -- Information systems applications
Libraries
Lower bound
Optimization
parallel scientific visualization
Pipelines
Program processors
Rendering (computer graphics)
Vectors
Title A configurable algorithm for parallel image-compositing applications
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