Optimum and heuristic transformation techniques for simultaneous optimization of latency and throughput

Although throughput alone can be arbitrarily improved for several classes of systems using previously published techniques, none of those approaches are effective when latency constraints, which are increasingly important in embedded DSP systems, are considered. After formally establishing the relationship between latency and throughput in general computation, we explore the effect of pipelining on latency, and establish necessary and sufficient conditions under which pipelining does not alter latency. Many systems are either linear, or have subsystems that are linear. For such cases we have used a state-space based approach that treats various transformations in an integrated fashion, and answers analytically whether it is possible to simultaneously meet any given combination of constraints on latency and throughput, The analytic approach is constructive in nature, and produces a complete implementation when feasibility conditions are fulfilled. We also present a suboptimal but hardware efficient heuristic approach for the special case of initially-relaxed single-input single-output linear time-invariant computations. A novel software platform consisting of a high-level synthesis system coupled to a symbolic algebra system was used to implement the proposed algorithm transformations. Instead of optimizing to improve throughput and latency, our transformations can also be used to increase the implementation efficiency while achieving the same latency and throughput as the original design.<
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