Task Assignment Algorithms for Heterogeneous Multiprocessors

Abstract

Consider the problem of assigning implicit-deadline sporadic tasks on a heterogeneous multiprocessor platform comprising a constant number (denoted by t ) of distinct types of processors—such a platform is referred to as a t-type platform . We present two algorithms, LPG IM and LPG NM , each providing the following guarantee. For a given t-type platform and a task set, if there exists a task assignment such that tasks can be scheduled to meet their deadlines by allowing them to migrate only between processors of the same type (intra-migrative), then : (i) LPG IM succeeds in finding such an assignment where the same restriction on task migration applies (intra-migrative) but given a platform in which only one processor of each type is 1 + α × t -1/ t times faster and (ii) LPG NM succeeds in finding a task assignment where tasks are not allowed to migrate between processors (non-migrative) but given a platform in which every processor is 1 + α times faster. The parameter α is a property of the task set; it is the maximum of all the task utilizations that are no greater than one. To the best of our knowledge, for t-type heterogeneous multiprocessors: (i) for the problem of intra-migrative task assignment, no previous algorithm exists with a proven bound and hence our algorithm, LPG IM , is the first of its kind and (ii) for the problem of non-migrative task assignment, our algorithm, LPG NM , has superior performance compared to state-of-the-art.