Massachusetts Institute of Technology
Modeling the scalability of acrylic stream programs
Abstract
dc:description.abstractDespite the fact that the streaming application domain is becoming increasingly widespread, few studies have focused specifically on the performance characteristics of stream programs. We introduce two models by which the scalability of stream programs can be predicted to some degree of accuracy. This is accomplished by testing a series of stream benchmarks on our numerical representations of the two models. These numbers are then compared to actual speedups obtained by running the benchmarks through the Raw machine and a Magic network. Using the metrics, we show that stateless acyclic stream programs benefit considerably from data, parallelization. In particular, programs with low communication datarates experience up to a tenfold speedup increase when parallelized to a reasonable margin. Those with high communication data rates also experience approximately a twofold speedup. We find that the model that takes synchronization communication overhead into account, in addition to a cost proportional to the communication rate of the stream, provides the highest predictive accuracy.
Degree
thesis:*- Department dc:contributor.department
- Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
- Grantor dc:publisher
- Massachusetts Institute of Technology
- Year dc:date.issued
- 2004
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Wong, Jeremy Ng, 1981-
- Advisor dc:contributor.advisor
-
- Saman P. Amarasinghe.
Subjects
dc:subject × 1Rights
dc:rights- Statement dc:rights
-
- M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
- Licence dc:rights.uri
- Language dc:language.iso
- eng
Identifiers
dc:identifier.*- Handle dc:identifier.uri
- http://hdl.handle.net/1721.1/18004
- OAI identifier oai:identifier
- oai:dspace.mit.edu:1721.1/18004