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2004 International Conference on Dependable Systems and Networks (DSN'04)   p. 177
The Impact of Technology Scaling on Lifetime Reliability

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DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/DSN.2004.1311888
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Abstract
The relentless scaling of CMOS technology has provided a steady increase in processor performance for the past three decades. However, increased power densities (hence temperatures) and other scaling effects have an adverse impact on long-term processor lifetime reliability. This paper represents a first attempt at quantifying the impact of scaling on lifetime reliability due to intrinsic hard errors, taking workload characteristics into consideration. For our quantitative evaluation, we use RAMP [The Case for Microarchitectural Awareness of Lifetime Reliability], a previously proposed industrial-strength model that provides reliability estimates for a workload, but for a given technology. We extend RAMP by adding scaling specific parameters to enable workload-dependent lifetime reliability evaluation at different technologies. We show that (1) scaling has a significant impact on processor hard failure rates - on average, with SPEC benchmarks, we find the failure rate of a scaled 65nm processor to be 316% higher than a similarly pipelined 180nm processor; (2) time-dependent dielectric breakdown and electromigration have the largest increases; and (3) with scaling, the difference in reliability from running at worst-case vs. typical workload operating conditions increases significantly, as does the difference from running different workloads. Our results imply that leveraging a single microarchitecture design for multiple remaps across a few technology generations will become increasingly difficult, and motivate a need for workload specific, microarchitectural lifetime reliability awareness at an early design stage.
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Citation:  Jayanth Srinivasan, Sarita V. Adve, Pradip Bose, Jude A. Rivers, "The Impact of Technology Scaling on Lifetime Reliability," dsn, p. 177,  2004 International Conference on Dependable Systems and Networks (DSN'04),  2004

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