Most of today’s real-time embedded systems consist of a heterogeneous mix of fully-programmable processors, fixed-function components or hardware accelerators, and partially-programmable engines. Hence, system designers are faced with an array of implementation possibilities for an application at hand. Such possibilities typically come with different tradeoffs involving cost, power consumption and packaging constraints. As a result, a designer is no longer interested in one implementation that meets the specified real-time constraints (i.e. is schedulable), but would rather like to identify all schedulable implementations that expose the different possible performance tradeoffs. In this paper we formally define this multicriteria schedulability analysis problem and derive a polynomial-time approximation algorithm for solving it. This result is interesting because the problem of optimally computing even one schedulable solution in our setup (and in most common setups) is computationally intractable (NP-hard). Further, our algorithm is reasonably easy to implement, returns good quality (approximate) solutions, and offers significant speedups over optimally computing all schedulable tradeoffs.
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