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Nathan Fisher Wayne State University

Explore reliability models like Electromigration to optimize speed schedules for real-time jobs while considering temperature impacts. Learn about void growth rates and mathematical models. Consider the variations in current density, thermal energy, and activation energy for efficient system operations. Examine the differences between reliability-aware and temperature-aware approaches in maintaining system longevity and task completion. Investigate feasibility algorithms and approximation techniques for maximizing processor lifetimes.

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Nathan Fisher Wayne State University

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  1. Thermal-Aware Reliability for Real-Time Systems(inspired by title of concurrent talk in Workshop on Low Power System on Chip -- “Reliability/Wear out-Aware Design” by Mircea Stan) Nathan Fisher Wayne State University

  2. Reliability Model:Electromigration (EM) “[EM] is the aging process in metal interconnects caused by the exchange of momentum between electrons” -Z. Lu, J. Lach, M. Stan, and K. Skadron, IEEE Micro 2005 • Effect: • Atoms aggregation; • Voids form (open-circuit failure!)

  3. Reliability Model:Electromigration (EM) • Mathematical Model of Void Growth Rate: Where s(t) – speed function; I(s,t) – current density (e.g., speed-scaled: I(t) = σs2 (t) ) kT(s,t) – thermal energy (e.g., Fourier’s Law : dT/dt = aP(t) – bT(t) ). Q – activation energy.

  4. Lifetime Analysis:Single Processor (Interconnect) • L = lifetime of processor. • Objective: Determine a speed schedule s that maximizes Ls.t. and schedules real-time jobs {Ji = (ai, wi, di)}i where F – Void Threshold ai – Arrival Time wi– Work Requirement di -- Deadline

  5. Issues/Questions • How is reliability-aware different than temperature-aware? • Potential Answer: It might be better to run at a higher temp for short periods of time. • Feasibility Algorithms: • Exact? • Approximation algorithms w/ ratio c that guarantee a lifetime Lopt/c? • Online Algorithms

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