A two-stage variation-aware placement method for FPGAS exploiting variation maps classification

Technology scaling causes increasing and unavoidable delay variability in FPGAs. This paper proposes a 2-stage variation-aware placement method that benefits from the optimality of a full-chipwise (chip-by-chip) placement but only requires a fraction of total execution time for a large number of FPGAs with different variation patterns. By classifying variation maps into finite number of classes, variation-aware placement only need to be executed based on the median map of each class to produce the placement for the other FPGAs (variation maps) in that class to save execution time. Our proposed method is implemented in a modified version of VPR 5.0 and verified using variation maps measured from 129 DE0 boards equipped with Cyclone III FPGAs. The mean timing gain of 7.36% is observed in 20 MCNC benchmarks with 16 clusters, while reducing execution time by a factor of 8 compared to full-chipwise placement.