Abstract:

GPU platforms are becoming increasingly attractive for implementing accelerators because they feature a larger number
of cores with improved programmability. In this paper, we describe our implementation of a state-of-the-art
academic multi-level analytical placer mPL [8] on Nvidia's massively parallel GT200 series platforms. We detail our efforts
on performance tuning and optimizations. When compared to software implementation on Intel's recent generation
Xeon CPU, the speed of the global placement part of mPL is 15X faster on average using a Tesla C1060 card, with
comparable WL. (less than 1% WL degradation on average)