1. Dataflow-Driven Placement: This approach significantly improves chip wirelength and timing, resulting in better PPA (Power, Performance, Area).
2. Mixed Macro/Cell Placement: Simultaneous macro and cell placement minimizes congestion and improves timing. 
3. Packing Technology: Macro-packing algorithms efficiently decrease the dead space in macro placement.
4. Exploration Methodology: It systematically explores various placement options, utilizing stage-by-stage filtering to reduce runtime.
5. Clustering Methodology: It can dramatically reduce runtime by 10x while maintaining a high correlation.

MaxPlace™ RL Reward Platform1. 100 Times Quicker: It can drastically expedite the physical design process, condensing months of work into a matter of days, achieving a placement speed that is 100 times faster.2. Enhanced Performance: Reinforcement learning proves more effective in optimizing chip performance due to its ability to provide higher correlation rewards.3. Production Proven: This approach's effectiveness has been validated through real production scenarios, as evidenced by its successful implementation in the MediaTek 5G Dimensity series chip.

Maxeda maintains ongoing collaborations with partners, including tier 1 clients and research institutions, aiming to consistently develop proven solutions that address real-world challenges. We are engaged in cooperating with tier-one foundries to meet customer demands in the post-Moore era. Our objective is to extend our success beyond Taiwan to the global market by leveraging a robust partner ecosystem such as this.

Manufacture and Enginnering Technology; Information and Communiction Technology (ICT); IC Design; AR/VR