Statistical placement for FPGAs considering process variation

Statistical placement for FPGAs considering process variation

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Process variations affecting timing and power is an important issue for modern integrated circuits in nanometre technologies. Field programmable gate arrays (FPGA) are similar to application-specific integrated circuit (ASIC) in their susceptibility to these issues, but face unique challenges in that critical paths are unknown at test time. The first in-depth study on applying statistical timing analysis with cross-chip and on-chip variations to speed-binning and guard-banding in FPGAs has been presented. Considering the uniqueness of re-programmability in FPGAs, the effects of timing-model with guard-banding and speed-binning on statistical performance and timing yield are quantified. A new variation aware statistical placement, which is the first statistical algorithm for FPGA layout and achieves a yield loss of 29.7% of the original yield loss with guard-banding and a yield loss of 4% of the original one with speed-binning for Microelectronics Center of North Carolina (MCNC) and Quartus University Interface Program (QUIP) designs, has also been developed.


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