Variation-Aware Placement With Multi-Cycle Statistical Timing Analysis for FPGAs

Abstract

Deep submicron processes have allowed field-programmable gate arrays (FPGAs) to grow in complexity and speed. However, such technology scaling has caused FPGAs to become more susceptible to the effects of process variation. In order to obtain sufficient yield values, it is now necessary to consider process variation during physical design. It is common for FPGAs to contain designs with multi-cycle paths to help increase the performance, but current statistical static timing analysis (SSTA) techniques cannot support this type of timing constraint. In this paper, we propose an extension to block-based SSTA to consider multi-cycle paths. We then use this new SSTA to optimize FPGA placement with our tool VMC-Place for designs with multi-cycle paths. Experimental results show our multi-cycle SSTA is accurate to 0.59% for the mean and 0.0024% for the standard deviation. Our results also show that VMC-Place is able to reduce the 95% performance yield clock period by 15.36% as compared to VPR.