EffiTest: Efficient Delay Test and Statistical Prediction for Configuring Post-silicon Tunable Buffers
Abstract
At nanometer manufacturing technology nodes, process variations significantly affect circuit performance. To combat them, post- silicon clock tuning buffers can be deployed to balance timing bud- gets of critical paths for each individual chip after manufacturing. The challenge of this method is that path delays should be mea- sured for each chip to configure the tuning buffers properly. Current methods for this delay measurement rely on path-wise frequency stepping. This strategy, however, requires too much time from ex- pensive testers. In this paper, we propose an efficient delay test framework (EffiTest) to solve the post-silicon testing problem by aligning path delays using the already-existing tuning buffers in the circuit. In addition, we only test representative paths and the delays of other paths are estimated by statistical delay prediction. Exper- imental results demonstrate that the proposed method can reduce the number of frequency stepping iterations by more than 94% with only a slight yield loss.
Cite
@article{arxiv.1705.04992,
title = {EffiTest: Efficient Delay Test and Statistical Prediction for Configuring Post-silicon Tunable Buffers},
author = {Grace Li Zhang and Bing Li and Ulf Schlichtmann},
journal= {arXiv preprint arXiv:1705.04992},
year = {2017}
}
Comments
ACM/IEEE Design Automation Conference (DAC), June 2016