Late Breaking Results: An Efficient and Scalable Track Assignment with GPU Parallelism

The track assignment has been introduced between global routing and detail routing. Based on the independence and divisibility of track assignment, we propose a GPU-accelerated parallel track assignment algorithm. To estimate routability more accurately, the proposed algorithm simultaneously considers global and local nets, and incorporates several strategies for optimization. Moreover, an asynchronous parallelism strategy is proposed to divide the computation of routing resources and the track assignment into fine-grained tasks. Experimental results show that, compared to related work, our algorithm achieves a significant speedup with a better routability estimation.