Comprehensive and Efficient Design Parameter Selection for Soft Error Resilient Processors via Universal Rules

Soft errors have been significantly degrading the reliability of current processors whose feature sizes and supply voltages are fast scaling down. In this paper, we propose two effective approaches to characterize processor reliability against soft errors at presilicon stage. By utilizing a rule sea...

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Bibliographic Details
Published in:IEEE transactions on computers 2014-09, Vol.63 (9), p.2201-2214
Main Authors: Duan, Lide, Zhang, Ying, Li, Bin, Peng, Lu
Format: Article
Language:English
Subjects:
Computational modeling
Design
Design engineering
Design parameters
Electric potential
Hardware reliability
Measurement
modeling and prediction
modeling of computer architecture
Patients
Processors
Program processors
Regression tree analysis
Reliability engineering
Searching
Soft errors
Training
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Summary:Soft errors have been significantly degrading the reliability of current processors whose feature sizes and supply voltages are fast scaling down. In this paper, we propose two effective approaches to characterize processor reliability against soft errors at presilicon stage. By utilizing a rule search strategy named Patient Rule Induction Method (PRIM), we are capable of generating a set of selective rules on key design parameters. These rules quantify the design space subregion with the lowest effective soft error rate (SER), thus providing useful guidelines in designing reliable processors. Furthermore, we also propose to use Classification and Regression Trees (CART) to partition the design space into a number of small subregions each being associated with a representative SER value. This gives the processor designer a global view of the SER distribution, enabling a comprehensive analysis over the entire design space. More importantly, both approaches generate "universal" models whose effectiveness is validated with a set of test programs unseen to training. Compared to traditional application-specific design space studies, our models' cross-program capability can save great training effort in the era of multithreading. Finally, a case study on multiprocessors is performed to simultaneously balance multiple design metrics, including reliability, performance, and power.
ISSN:0018-9340
1557-9956
DOI:10.1109/TC.2013.24