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Reducing control overhead in dataflow architectures
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Proceedings of the 15th international conference on Parallel architectures and compilation techniques table of contents
Seattle, Washington, USA
SESSION: Instruction fetch and control flow table of contents
Pages: 182 - 191  
Year of Publication: 2006
ISBN:1-59593-264-X
Authors
Andrew Petersen  University of Washington, Seattle, WA
Andrew Putnam  University of Washington, Seattle, WA
Martha Mercaldi  University of Washington, Seattle, WA
Andrew Schwerin  University of Washington, Seattle, WA
Susan Eggers  University of Washington, Seattle, WA
Steve Swanson  University of Washington, Seattle, WA
Mark Oskin  University of Washington, Seattle, WA
Sponsor
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 9,   Downloads (12 Months): 55,   Citation Count: 1
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ABSTRACT

In recent years, computer architects have proposed tiled architectures in response to several emerging problems in processor design, such as design complexity, wire delay, and fabrication reliability. One of these architectures, WaveScalar, uses a dynamic, tagged-token dataflow execution model to simplify the design of the processor tiles and their interconnection network and to achieve good parallel performance. However, using a dataflow execution model reawakens old problems, including the instruction overhead required for control flow. Previous work compiling the functional language Id to the Monsoon Dataflow System found this overhead to be 2–3× that of programs written in C and targeted to a MIPS R3000.In this paper, we present and analyze three compiler optimizations that significantly reduce control overhead with minimal additional hardware. We begin by describing how to translate imperative code into dataflow assembly and analyze the resulting control overhead. We report a similar 2–4× instruction overhead, which suggests that the execution model, rather than a specific source language or target architecture, is responsible. Then, we present the compiler optimizations, each of which is designed to eliminate a particular type of control overhead, and analyze the extent to which they were able to do so. Finally, we evaluate the effect using all optimizations together has on program performance. Together, the optimizations reduce control overhead by 80% on average, increasing application performance between 21–37%.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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"The WaveScalar architecture," In submission to ACM Transactions on Computer Systems (TOCS), 2006.
 
14
Arvind, "Dataflow: Passing the token," in Keynote at the International Symposium on Computer Architecture (ISCA), 2005.
 
15
 
16
 
17
18
19
20
 
21
 
22
23
24
25
 
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R. Nikhil, "The parallel programming language id and its compilation for parallel machines," in the Workshop on Mazzive Paralleism: Hardware, Programming and Applications, Acamedic Press, 1990.
 
27
28
 
29
 
30
D. E. Culler, S. C. Goldstein, K. E. Schauser, and T. von Eicken, "Empirical study of a dataflow language on the CM-5," in the 2nd Workshop on Dataflow Computing, pp. 187--210, 1992.
31
 
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M. Budiu, P. V. Artigas, and S. C. Goldstein, "Dataflow: A complement to superscalar," in the IEEE International Symposium on Performance Analysis of Systems and Software, pp. 177--186, 2005.
 
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Collaborative Colleagues:
Andrew Petersen: colleagues
Andrew Putnam: colleagues
Martha Mercaldi: colleagues
Andrew Schwerin: colleagues
Susan Eggers: colleagues
Steve Swanson: colleagues
Mark Oskin: colleagues