A Hilbert-Curve Based Delay Fault Characerization Framework for Fpgas

Abstract

With the increasing process variations in advanced technologies, delay defects are gaining a larger impact on Field Programmable Gate Array (FPGA) timing yield. If the delay defect areas can be quickly and accurately located, FPGA timing yield can be improved by avoiding them. Conventional delay testing methods do not take into account the spatial information of variability-induced delay faults, thus cannot accurately locate the delay defects to a well restricted area. Based on the superb locality preserving feature of space-filling curves, we propose a method to locate delay faults and generate a delay variation map (DVM) with scalable resolutions in this thesis. The method uses Hilbert curves to guide the test configurations of FPGAs. It is able to work on FPGAs with regular or arbitrary dimensions. Compared with normal test approaches, our method achieved around 60% increase in delay faults locating resolution.