The size and complexity of modern VLSI computer chips are growing at a rapid pace. Functional debugging is increasingly becoming a bottleneck in the design flow where it can take up to 60% of the total verification time. Scaling existing automated debugging tools is necessary in order to continue along this path of rapid growth and innovation in the semiconductor industry. This thesis aims to scale automated debugging techniques with two contributions. The first contribution introduces a succinct memory model for automated design debugging that dramatically lowers the memory requirements for the debugging problem. The second contribution presents a scalable SAT-based design debugging algorithm that uses a mathematical technique called interpolation to divide the debugging problem into multiple parts across time which greatly reduces the peak memory requirements of the debugging problem. Extensive experiments on real designs demonstrate the benefit of this work.
| Identifer | oai:union.ndltd.org:TORONTO/oai:tspace.library.utoronto.ca:1807/18789 |
| Date | 12 February 2010 |
| Creators | Keng, Brian |
| Contributors | Veneris, Andreas |
| Source Sets | University of Toronto |
| Language | en_ca |
| Detected Language | English |
| Type | Thesis |
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