Abstract
Placement and routing are two time-consuming steps in the FPGA physical design flow and can take hours or even days. The placement steps map the logic elements of the netlist onto the computational resources of the FPGA, and the routing step is responsible for finding paths to connect the logic blocks through the FPGA routing fabric. The routing resources have a fixed capacity; using them beyond their capacity results in congestion. Congestion can cause routing failures and make it difficult to achieve timing closure and the placement algorithms should produce solutions that do not generate congestion in routing. Researchers have employed many approaches, from elementary ways (e.g., counting the number of pins) to accurate artificial intelligence-driven methods. This article categorizes congestion estimation methods developed over the last 25 years, providing an overview and survey of methods belonging to each category. To aid in understanding, simple experiments are included to illustrate each method's application. Finally, the article concludes by outlining potential future research directions in the field.
| Original language | English |
|---|---|
| Title of host publication | 2025 6th International Conference on Artificial Intelligence, Robotics, and Control, AIRC 2025 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 281-290 |
| Number of pages | 10 |
| ISBN (Electronic) | 9798331543488 |
| DOIs | |
| State | Published - 2025 |
| Event | 6th International Conference on Artificial Intelligence, Robotics, and Control, AIRC 2025 - Savannah, United States Duration: 7 May 2025 → 9 May 2025 |
Publication series
| Name | 2025 6th International Conference on Artificial Intelligence, Robotics, and Control, AIRC 2025 |
|---|
Conference
| Conference | 6th International Conference on Artificial Intelligence, Robotics, and Control, AIRC 2025 |
|---|---|
| Country/Territory | United States |
| City | Savannah |
| Period | 7/05/25 → 9/05/25 |
Bibliographical note
Publisher Copyright:© 2025 IEEE.
Keywords
- FPGA
- congestion prediction
- generative AI
- machine and deep learning
- placement
- routing
ASJC Scopus subject areas
- Mechanical Engineering
- Control and Optimization
- Artificial Intelligence
- Computer Science Applications