DocumentCode :
465374
Title :
Shared Resource Access Attributes for High-Level Contention Models
Author :
Bobrek, Alex ; Paul, JoAnn M. ; Thomas, Donald E.
Author_Institution :
Carnegie Mellon Univ., Pittsburgh
fYear :
2007
fDate :
4-8 June 2007
Firstpage :
720
Lastpage :
725
Abstract :
Emerging single-chip heterogeneous multiprocessors feature hundreds of design elements contending for shared resources, making it difficult to isolate performance impacts of individual design changes. This work is the first to parameterize shared resource accesses in the form of access attributes, summarizing the impact of shared resource contention on system performance, analogous to the way RTL parameters summarize more detailed transistor models. The intuition behind access attributes is that much application and architecture dependent contention information is known during detailed cycle-accurate simulations, and would be useful to inform a higher level model. The detailed contention information is sampled from a short cycle-accurate simulation, "training" a high-level statistical regression model of contention. This contention model can then be used in simulation to estimate the impact of shared resource accesses at a high level of abstraction, enabling the designers to explore contention-related performance impacts of design decisions. Using the access attribute-based contention models resulted in speedups of 40X over cycle-accurate simulation, with average simulation errors of less than 1% with 95% confidence intervals of about plusmn3%.
Keywords :
circuit simulation; integrated circuit modelling; microprocessor chips; regression analysis; RTL parameters; access attribute-based contention model; cycle-accurate simulation; high-level contention model; shared resource; single-chip heterogeneous multiprocessors; statistical regression model; system performance; Analytical models; Concurrent computing; Data mining; Information analysis; Interleaved codes; Permission; Sampling methods; System performance; Yarn; Contention Modeling; Design; Heterogeneous Multiprocessors; Performance; Performance Modeling; Simulation; Statistical Regression Models;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Design Automation Conference, 2007. DAC '07. 44th ACM/IEEE
Conference_Location :
San Diego, CA
ISSN :
0738-100X
Print_ISBN :
978-1-59593-627-1
Type :
conf
Filename :
4261277
Link To Document :
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