An online overclocking scheme for bursty real-time tasks and an evaluation of its thermal impact

摘要

This paper proposes a scheme which drives a processor beyond its rated operation frequency, e. g., by exploiting Intel's boost technology, to digest the peak workload of the system in time. In the setting of deadline constrained workloads, this is far from trivial: the boost mode can only be used during short time spans, therefore it can only help to digest the peak workload, rather than serving the normal case. A lowered processor frequency, used outside the peak workload time, yields a backlog of not completed jobs. This backlog may result in deadline violations or buffer overflows, if the next burst of job arrivals appears too early. To overcome the above problem, we propose a peak workload aware speed assignment strategy, which only allows the system to build up computation backlog if the absence of high computation demands is assured. Contrasting the existing body of work, we take advantage of bursty arrival patterns of compute jobs, thereby progressing over the standard (non-bursty sporadic) job release model. Together with our scheme, we also present a tool chain and simulations of synthetic workloads for investigating the thermal effects of different speed assignment strategies.