Abstract-With the evolution of today's semiconductor technology, chip temperature increases rapidly mainly due to the growth in power density. For modern embedded real-time systems, it is crucial to estimate maximal temperatures in order to take mapping or other design decisions to avoid burnout, and still be able to guarantee meeting real-time constraints. This paper provides answers to the question: When work-conserving scheduling algorithms, such as earliest-deadlinefirst (EDF), rate-monotonic (RM), deadline-monotonic (DM), are applied, what is the worst-case peak temperature of a real-time embedded system under all possible scenarios of task executions? We propose an analytic framework, which considers a general event model based on network and real-time calculus. This analysis framework has the capability to handle a broad range of uncertainties in terms of task execution times, task invocation periods, and jitter in task arrivals. Simulations show that our framework is a cornerstone to design real-time systems that have guarantees on both schedulability and maximal temperatures. Keywords-real-time systems; compositional analysis; worst-case peak temperature; thermal analysis I. INTRODUCTION Power density has been continuously increasing in modern processors, leading to high on-chip temperatures. A system could fail if the operating temperature exceeds a certain threshold, leading to low reliability and even chip burnout. Therefore, at design time, temperature reduction has been achieved through appropriate packaging and active heat dissipation mechanisms. Moreover, at run time, dynamic thermal management (DTM) can be adopted to enhance system reliability and reduce packaging costs. A large area of research investigates DTM mechanisms, e.g., [1], [10], based on dynamic voltage/frequency scaling (DVFS), to reduce system power consumption and therefore, to prevent the system from overheating. There have been many results in recent years about thermal management, including (1) [18] or determine the schedulability of real-time systems under given temperature constraints [5], (2) peak temperature reduction to meet performance constraints [2] , and (3) thermal control by applying control theory for system adaption [15] . Specifically, for thermal-constrained scheduling, in [1], an algorithm is developed to maximize the workload that can complete in a specified time window without violating thermal constraints. Formal analysis is later adopted in [5] to analyze schedulability of real-time tasks under thermal constraints. In [18] , approximation algorithms are developed to minimize the completion time, while each task is restricted to execute at one speed. In [4], workload maximization is explored for discrete DVS speeds, under thermal constraints. Moreover, for reducing the peak temperature in the system in [2], the on-line algorithm for energy efficiency proposed in [17] is adopted. To model uncertainties of task execution, ambient temperature changes, or power variations, control theoretical approaches have been adopted, e.g., in [15] .
This drawback is addressed in REF , where the worst-case peak temperature of a real-time system is calculated from its system-level specification.
Worst-case temperature analysis for real-time systems
2011 Design, Automation & Test in Europe
2011 Design, Automation & Test in Europe
Computer Science