Improved volume diagnosis throughput using dynamic design partitioning

A method based on dynamic design partition is presented to increase the throughput of volume diagnosis by increasing the number of failing dies diagnosed within a given time T using given constrained computational resources C. Recently we proposed a static design partitioning method to reduce the diagnosis memory footprint for large designs [1] to achieve this objective. The method in [1] is applied once for each design without using the information of test patterns and failure files, and then diagnosis is performed on an appropriate block(s) of the design partition for a failure file. Even though the memory footprint of diagnosis is reduced the diagnosis quality is impacted to unacceptable levels for some types of defects such as bridges. In this paper, we propose a new failure dependent design partitioning method to improve volume diagnosis throughput with a minimal impact on diagnosis quality. For each failure file, the proposed method first determines the small partition needed to diagnose this failure, and then performs the diagnosis on this partition instead of the complete design. Since the partition is far smaller, both the run time and the memory usage of diagnosis can be significantly reduced better than when earlier proposed static partition is used. Extensive experiments were conducted on several large industrial designs to validate the proposed method. It has been observed that the typical partition size for various defects is less than 3% of the size of the original design. Also diagnosis runs much faster (>;2X) on the partition. Combining these two factors, the throughput of volume diagnosis can be improved by an order of magnitude.