Proceedings Article | 4 April 2011
Proc. SPIE. 7974, Design for Manufacturability through Design-Process Integration V
KEYWORDS: Semiconductors, Lithography, Data modeling, Visualization, Pattern recognition, Manufacturing, Design for manufacturing, Computer aided design, Semiconducting wafers, Device simulation
In today's semiconductor industry, prior to wafer fabrication, it has become a desirable practice to scan layout designs
for lithography-induced defects using advanced process window simulations in conjunction with corresponding
manufacturing checks. This methodology has been proven to provide the highest level of accuracy when correlating
systematic defects found on the wafer with those identified through simulation. To date, when directly applying this
methodology at the full chip level, there has been unfavorable expenses incurred that are associated with simulation
which are currently overshadowing its primary benefit of accuracy - namely, long runtimes and the requirement for an
abundance of cpus. Considering the aforementioned, the industry has begun to lean towards a more practical application
for hotspot identification that revolves around topological pattern recognition in an attempt to sidestep the simulation
runtime. This solution can be much less costly when weighing against the negative runtime overhead of simulation. The
apparent benefits of pattern matching are, however, counterbalanced with a fundamental concern regarding detection
accuracy; topological pattern identification can only detect polygonal configurations, or some derivative of a
configuration, which have been previously identified. It is evident that both systems have their strengths and their
weaknesses, and that one system's strength is the other's weakness, and vice-versa.
A novel hotspot detection methodology that utilizes pattern matching combined with lithographic simulation will be
introduced. This system will attempt to minimize the negative aspects of both pattern matching and simulation. The
proposed methodology has a high potential to decrease the amount of processing time spent during simulation, to relax
the high cpu count requirement, and to maximize pattern matching accuracy by incorporating a multi-staged pattern
matching flow prior to performing simulation on a reduced data set. Also brought forth will be an original methodology
for constructing the core pattern set, or candidate hotspot library, in conjunction with establishing hotspot and coldspot
pattern libraries. Lastly, it will be conveyed how this system can automatically improve its potential as more designs are
passed through it.
