Temperature-aware microarchitecture
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Approximation algorithm for the temperature-aware scheduling problem
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Lifetime improvement through runtime wear-based task mapping
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Proceedings of the Conference on Design, Automation and Test in Europe
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Temperature-aware design is emerging as a popular approach to addressing a variety of challenges, including system lifetime. In the case of task mapping, temperature-aware approaches indeed improve lifetime due to lifetime's strong dependence on tempera-ture. However, temperature-aware design neglects several impor-tant factors that also influence lifetime: (a) physical parameters such as supply voltage and current density, as well as (b) application and architecture characteristics that affect what failures are survivable. Only lifetime-aware task mapping can expose the relationship between physical parameters, component failure, and system lifetime, and therefore find lifetime-optimal mappings. To address this need, we have developed a new lifetime-aware task mapping technique based on ant colony optimization (ACO). Our technique produces task mappings resulting in lifetimes within 17.9% of the observed optimal results on average, outperforming a lifetime-agnostic task mapping approach by an average of 32.3%. We also observed that the lifetimes resulting from task mappings within 1% of the best maximum system temperature vary by an average of 20.1% while the lifetimes resulting from task mappings within 1% of the best average system temperature vary by an average of 32.6%. Our observations lead us to conclude that one cannot depend on temperature-aware task mapping when system lifetime is a design constraint, but one may depend on lifetime-aware task mapping when one or both of lifetime and temperature are design constraints.