ISPD 2019 Initial Detailed Routing Contest and Benchmark with Advanced Routing Rules

Liu, Wenhao; Mantik, Stefanus; Chow, Wing-Kai; Ding, Yixiao; Farshidi, Amin; Posser, Gracieli

doi:10.1145/3299902.3311067

Cited by 28 publications

(13 citation statements)

References 8 publications

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“…In this work, we consider two academic Detailed Routing tools: Dr. CU [33] and TritonRoute [38]. Initial Detailing Routing has been the subject of two recent Contests, ISPD 2018 [15] and ISPD 2019 [16]. TritonRoute won first place in the ISPD 2018 Contest, and Dr. CU won second and first places in ISPD 2018 and ISPD 2019 Contests, respectively.…”

Section: A Experimental Methodologymentioning

confidence: 99%

“…We chose the benchmarks from ISPD 2018 [15] and ISPD 2019 [16] CAD Placement Contests because they are the most recent and complete benchmark sets for placement and routing stages. In ISPD 2018 and ISPD 2019 Contests suites, there are circuits designed with three different technology nodes: 65nm, 45nm, and 32nm.…”

Section: Benchmarksmentioning

confidence: 99%

“…Searching to fill this gap, in this work, we experimentally explored twelve flows built up from academic placers and routers to find which one can lead to the best results so that researchers can use them as references. In order to evaluate those flows, we used the ISPD 2018 [15] and ISPD 2019 [16] CAD Contest benchmarks, which are the most realistic academic benchmarks available with placement and routing information.…”

Section: Introductionmentioning

confidence: 99%

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Towards a Reference Place and Route Flow for Academic Research

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et al. 2022

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Due to the complexity of contemporary circuits, physical synthesis has become a crucial step for achieving design closure. The placement of cells direct impacts the routing solution. For example, a region with a high cell density can lead to pin access issues in detailed routing. Therefore, small inefficiencies in the placement solution can be boosted during routing, which has a negative impact on design quality and convergence. Unfortunately, most academic research works evaluate the results only in the target step without considering the complete place and route flows. In this work, we experimentally explored different flows built up from academic placers and routers to find which one leads to the best overall results so that researchers can use them as a reference. In order to evaluate those flows, we used the ISPD 2018 and ISPD 2019 CAD Contest benchmarks, which are the most realistic academic benchmarks available with placement and routing information. Considering the evaluator reports, no combination of tools achieved the best result for all circuits. Nevertheless, the flow Contest placement + CUGR + TritonRoute achieved the best results in fifteen out of twenty benchmarks.

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Section: A Experimental Methodologymentioning

confidence: 99%

Section: Benchmarksmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Towards a Reference Place and Route Flow for Academic Research

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Netto

Almeida

et al. 2022

JICS

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show abstract

“…Algorithm 2 demonstrates the backward trace step to get the optimal MSV design solution, the edge with the smallest cost connected to the pseudo sink node is found first (Line 1), and the corresponding placement configuration will be used for the highest layer (Line 2). Lines [3][4][5][6][7][8] utilize the prev function to iteratively derive the placement configuration on the lower adjacent layer, and the optimal MSV design can be constructed from the highest layer to the lowest layer.…”

Section: Graph Optimization Problem Of Msvmentioning

confidence: 99%

“…for concurrent methodologies using ILP formulations, some design rules can hardly be formulated into ILP constraints. For example, the adjacent cut spacing rule addressed by [ 4] specifies an adjacent spacing of a target via if a specific number of vias is within a range of the target via. Fig.…”

Section: Introductionmentioning

confidence: 99%