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

arXiv: https://arxiv.org/abs/2503.12946 · HTML: https://mlsanity.com/paper/2503.12946/

## 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 (most cited first, 8 of 8)

- [How Powerful are Graph Neural Networks?](https://mlsanity.com/paper/1810.00826/) (2018)
- [A Modern Primer on Processing in Memory](https://mlsanity.com/paper/2012.03112/) (2020)
- [Benchmarking End-To-End Performance of AI-Based Chip Placement Algorithms](https://mlsanity.com/paper/2407.15026/) (2024)
- [Hier-RTLMP: A Hierarchical Automatic Macro Placer for Large-scale Complex IP Blocks](https://mlsanity.com/paper/2304.11761/) (2023)
- [Reinforcement Learning Policy as Macro Regulator Rather than Macro Placer](https://mlsanity.com/paper/2412.07167/) (2024)
- [Timing-Driven Global Placement by Efficient Critical Path Extraction](https://mlsanity.com/paper/2503.11674/) (2025)
- [Analytical Die-to-Die 3D Placement with Bistratal Wirelength Model and GPU Acceleration](https://mlsanity.com/paper/2310.07424/) (2023)
- [Analytical Heterogeneous Die-to-Die 3D Placement with Macros](https://mlsanity.com/paper/2403.09070/) (2024)

## Built on by (most cited first, 4 of 4)

- [Advancing Automated Algorithm Design via Evolutionary Stagewise Design with LLMs](https://mlsanity.com/paper/2603.07970/) (2026)
- [AgenticECO: An Agentic Framework for ECO on 3D Integrated Circuits](https://mlsanity.com/paper/2608.03738/) (2026)
- [Re2MaP: Macro Placement by Recursively Prototyping and Packing Tree-based Relocating](https://mlsanity.com/paper/2511.08054/) (2025)
- [A PPA-Driven 3D-IC Partitioning Selection Framework with Surrogate Models](https://mlsanity.com/paper/2604.18806/) (2026)

## 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.