2019
DOI: 10.3390/electronics8121439
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ParaLarPD: Parallel FPGA Router Using Primal-Dual Sub-Gradient Method

Abstract: In the field programmable gate array (FPGA) design flow, one of the most time-consuming steps is the routing of nets. Therefore, there is a need to accelerate it. In a recent work by Hoo et al., the authors have developed a linear programming (LP)-based framework that parallelizes this routing process to achieve significant speed-ups (the resulting algorithm is termed as ParaLaR). However, this approach has certain weaknesses. Namely, the constraints violation by the solution and a standard routing metric coul… Show more

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Cited by 9 publications
(31 citation statements)
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“…There are two other important metrics used to determine the efficiency of the FPGA routing process; the total wire length and the critical path delay, with the later one being more easily measurable. In [4], we showed that on an average, ParaLarPD achieved the same total wire length but a slightly deteriorated critical path delay when compared with ParaLaR.…”
Section: Introductionmentioning
confidence: 87%
See 1 more Smart Citation
“…There are two other important metrics used to determine the efficiency of the FPGA routing process; the total wire length and the critical path delay, with the later one being more easily measurable. In [4], we showed that on an average, ParaLarPD achieved the same total wire length but a slightly deteriorated critical path delay when compared with ParaLaR.…”
Section: Introductionmentioning
confidence: 87%
“…In one of our recent works [4], we substantially improved the constraints violation drawback of Par-aLaR. We achieved this by developing a more problem specific version of the sub-gradient method and fine tuning the size of its iterative step.…”
Section: Introductionmentioning
confidence: 99%
“…Next, we give a brief idea of LASSO and ADMM, which we use. The general LASSO problem is given as [45] minz12false∥Azbfalse∥22+λfalse∥zfalse∥1,where zdouble-struckRn, Adouble-struckRp×n, bdouble-struckRp, false∥·false∥2 is the 2 norm and λ>0 is a scalar regularization parameter also called Lagrangian parameter [46]. Further, () is transformed into a form solvable by ADMM [44].…”
Section: Compressed Sensingmentioning
confidence: 99%
“…where z ∈ ℝ n , A ∈ ℝ p×n , b ∈ ℝ p , ‖ ⋅ ‖ 2 is the 2 norm and > 0 is a scalar regularization parameter also called Lagrangian parameter [46]. Further, ( 7) is transformed into a form solvable by ADMM [44].…”
Section: Reconstruction Of the Approximate Signalmentioning
confidence: 99%
“…To diminish the required internal occupied resources, it is necessary to take into account specifics of logic elements implementing FSM circuits [8,9]. Nowadays, field programmable gate arrays (FPGAs) [10][11][12] are widely used in the implementation of digital systems [9,[13][14][15]. Due to it, we choose FPGA-based FSMs as a research object in the given article.…”
Section: Introductionmentioning
confidence: 99%