Static Rate-Optimal Scheduling of Multirate DSP Algorithms via Retiming and Unfolding

Zhu, Xun; Geilen, Marc; Basten, Twan; Stuijk, Sander

doi:10.1109/rtas.2012.15

Cited by 17 publications

(22 citation statements)

References 19 publications

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“…For developing our method, we define the behavior of an SDFG G in terms of a labeled transition system, represented by LTS(G), similar to [8]. We use tn(e) to record the current number of tokens on edge e. SDFGs allow simultaneous firings of an actor.…”

Section: An Operational Semantics Of Sdfgsmentioning

confidence: 99%

“…The operational semantics extends the semantics in [8] by adding tnb(E) to record the storage requirement.…”

Section: "Efiring(b)mentioning

confidence: 99%

“…A rate-optimal schedule can be delivered from it [8]. A storage requirement can also be computed according to the semantics we define in Section III.…”

Section: Memory Constrained Self-timed Executionmentioning

confidence: 99%

“…STE analysis is used in [4] to construct static periodic rate-optimal schedules with minimal buffer sizes for homogenous synchronous dataflow graphs (HSDFGs), which is a special type of SDFGs. It is used in [5] to compute the minimal storage space under a given throughput constraint, and it is used in [8] to get a rate-optimal schedule 978-3-9815370-2-4/DATE14/ c 2014 EDAA of an SDFG with and without processor constraints.…”

Section: Introduction and Related Workmentioning

confidence: 99%

“…The state space includes the information of a retiming and a rate-optimal schedule of the retimed graph [8]. We show in this paper that the state space also includes the information about memory required by a schedule.…”

Section: Introduction and Related Workmentioning

confidence: 99%

See 4 more Smart Citations

Memory-constrained static rate-optimal scheduling of synchronous dataflow graphs via retiming

Zhu¹,

Geilen²,

Basten³

et al. 2014

Design, Automation &Amp; Test in Europe Conference &Amp; Exhibition (DATE), 2014

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Abstract-Synchronous dataflow graphs (SDFGs) are widely used to model digital signal processing (DSP) and streaming media applications. In this paper, we use retiming to optimize SDFGs to achieve a high throughput with low storage requirement. Using a memory constraint as an additional enabling condition, we define a memory constrained self-timed execution of an SDFG. Exploring the state-space generated by the execution, we can check whether a retiming exists that leads to a rate-optimal schedule under the memory constraint. Combining this with a binary search strategy, we present a heuristic method to find a proper retiming and a static scheduling which schedules the retimed SDFG with optimal rate (i.e., maximal throughput) and with as little storage space as possible. Our experiments are carried out on hundreds of synthetic SDFGs and several models of real applications. Differential synthetic graph results and real application results show that, in 79% of the tested models, our method leads to a retimed SDFG whose rate-optimal schedule requires less storage space than the proven minimal storage requirement of the original graph, and in 20% of the cases, the returned storage requirements equal the minimal ones. The average improvement is about 7.3%. The results also show that our method is computationally efficient.

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Section: An Operational Semantics Of Sdfgsmentioning

confidence: 99%

“…The operational semantics extends the semantics in [8] by adding tnb(E) to record the storage requirement.…”

Section: "Efiring(b)mentioning

confidence: 99%

“…A rate-optimal schedule can be delivered from it [8]. A storage requirement can also be computed according to the semantics we define in Section III.…”

Section: Memory Constrained Self-timed Executionmentioning

confidence: 99%