This paper addresses the problem of minimizing the peak temperature for pipelined multi-core systems under hard end-to-end deadline constraints by adversely using the Pay-Burst-Only-Once principle. The Periodic Thermal Management is adopted to control the temperature and every core is periodically switched between two power modes. With the peak temperature representation, we first formulate the problem of finding the thermal optimal periodic schemes which satisfies deadline constraints and then present a fast heuristic algorithm to solve it. Adopting real life processor platforms and applications, our simulation demonstrates that our approach reduces the peak temperature by up to 15°C on the 4-stage ARM platform compared to sub-deadline partition approach. Moreover, our algorithm is shown to be scalable w.r.t. the number of pipelined stages and its effectiveness is validated by the brutally searching approach.
['Long Cheng', 'Kai Huang', 'Gang Chen', 'Biao Hu', 'Alois Knoll']
Minimizing peak temperature for pipelined hard real-time systems