Lower bound estimation of hardware resources for scheduling in high-level synthesis

Shen, Zexiang; Jong, Ching Chuen

doi:10.1007/bf02960762

Cited by 5 publications

(1 citation statement)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Ohm et al [11] presented a technique for lower-bound estimation. Shen and Jong [17] proposed a stepwise refinement algorithm for resource estimation based on execution interval analysis. Their approach can handle loop folding and conditional branches at the same time.…”

Section: Related Workmentioning

confidence: 99%

Efficient Resource Constrained Scheduling Using Parallel Structure-Aware Pruning Techniques

Chen

Zhang

et al. 2016

IEEE Trans. Comput.

View full text Add to dashboard Cite

Branch-and-bound approaches are promising in pruning fruitless search space during the resource constrained scheduling. However, such approaches only compare the estimated upper and lower bounds of an incomplete schedule to the length of the best feasible schedule at that iteration, which does not fully exploit the potential of the pruning during the search. Aiming to improve the performance of resource constrained scheduling, this paper proposes a parallel structure-aware pruning approach that can traverse the search space significantly faster than state-of-the-art branch-and-bound techniques. This paper makes three major contributions: i) it proposes an efficient pruning technique using the structural scheduling information of the obtained best feasible schedules; ii) it investigates how to perform parallel search to enable efficient multi-directional search and generation of effective fences by tuning the operation enumeration order; and iii) it presents a framework that supports the sharing of minimum upper-bound and fence information among different search tasks to enable efficient parallel structure-aware pruning. The experimental results demonstrate that our parallel pruning approach can drastically reduce the overall resource constrained scheduling time under a wide variety of resource constraints.

show abstract

Section: Related Workmentioning

confidence: 99%