mlsanityData to 14 Oct 2026

Open3DBench: Open-Source Benchmark for 3D-IC Backend Implementation and PPA Evaluation

arXiv 2503.12946 ↗First posted 17 Mar 2025cs.AR cs.AIcited by 4

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Abstract (arXiv)

This work introduces Open3DBench, an open-source 3D-IC backend implementation benchmark built upon the OpenROAD-flow-scripts framework, enabling comprehensive evaluation of power, performance, area, and thermal metrics. Our proposed flow supports modular integration of 3D partitioning, placement, 3D routing, RC extraction, and thermal simulation, aligning with advanced 3D flows that rely on commercial tools and in-house scripts. We present two foundational 3D placement algorithms: Open3D-Tiling, which emphasizes regular macro placement, and Open3D-DMP, which enhances wirelength optimization through cross-die co-placement with analytical placer DREAMPlace. Experimental results show significant improvements in area (51.19%), wirelength (24.06%), timing (30.84%), and power (5.72%) compared to 2D flows. The results also highlight that better wirelength does not necessarily lead to PPA gain, emphasizing the need of developing PPA-driven methods. Open3DBench offers a standardized, reproducible platform for evaluating 3D EDA methods, effectively bridging the gap between open-source tools and commercial solutions in 3D-IC design.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 8 of its 81 references that are in the map. First posted on arXiv 17 Mar 2025.

Builds on

8 of 81 references.

References · 8

  1. 2018How Powerful are Graph Neural Networks?cited by 4,393
  2. 2020A Modern Primer on Processing in Memorycited by 32
  3. 2024Benchmarking End-To-End Performance of AI-Based Chip Placement Algorithmscited by 14
  4. 2023Hier-RTLMP: A Hierarchical Automatic Macro Placer for Large-scale Complex IP Blockscited by 11
  5. 2024Reinforcement Learning Policy as Macro Regulator Rather than Macro Placercited by 10
  6. 2025Timing-Driven Global Placement by Efficient Critical Path Extractioncited by 4
  7. 2023Analytical Die-to-Die 3D Placement with Bistratal Wirelength Model and GPU Accelerationcited by 1
  8. 2024Analytical Heterogeneous Die-to-Die 3D Placement with Macroscited by 1

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 3.

4 papers.