Title
Streaming-enabled parallel dataflow architecture for multicore systems
Abstract
We propose a new framework design for exploiting multi-core architectures in the context of visualization dataflow systems. Recent hardware advancements have greatly increased the levels of parallelism available with all indications showing this trend will continue in the future. Existing visualization dataflow systems have attempted to take advantage of these new resources, though they still have a number of limitations when deployed on shared memory multi-core architectures. Ideally, visualization systems should be built on top of a parallel dataflow scheme that can optimally utilize CPUs and assign resources adaptively to pipeline elements. We propose the design of a flexible dataflow architecture aimed at addressing many of the shortcomings of existing systems including a unified execution model for both demand-driven and event-driven models; a resource scheduler that can automatically make decisions on how to allocate computing resources; and support for more general streaming data structures which include unstructured elements. We have implemented our system on top of VTK with backward compatibility. In this paper, we provide evidence of performance improvements on a number of applications.
Year
DOI
Venue
2010
10.1111/j.1467-8659.2009.01704.x
Comput. Graph. Forum
Keywords
Field
DocType
visualization system,event-driven model,shared memory multi-core architecture,visualization dataflow system,streaming-enabled parallel dataflow architecture,new resource,parallel dataflow scheme,flexible dataflow architecture,new framework design,multi-core architecture,multicore system,data structure
Computer architecture,Dataflow architecture,Shared memory,Visualization,Computer science,Dataflow,Execution model,Streaming data,Backward compatibility,Multicore systems
Journal
Volume
Issue
ISSN
29
3
0167-7055
Citations 
PageRank 
References 
9
0.58
21
Authors
6
Name
Order
Citations
PageRank
Huy T. Vo1103561.10
Daniel K. Osmari2161.82
Brian Summa31126.84
João L. D. Comba429524.77
Valerio Pascucci53241192.33
Cláudio T. Silva65054290.90