Distributed processing in integrated data preparation flow

The era of week-long turn around times (TAT) and half-terabyte databases is at hand as seen by the initial 90 nm production nodes. A quadrupling of TAT and database volumes for the subsequent nodes is considered to be a conservative estimate of the expected growth by most mask data preparation (MDP) groups, so how will fabs and mask manufacturers address this data explosion with a minimal impact to cost? The solution is a multi-tiered approach of hardware and software. By shifting from costly Unix servers to cheaper Linux clusters, MDP departments can add hundreds to thousands of CPU's at a fraction of the cost. This hardware change will require the corresponding shift from multithreaded (MT) to distributed-processing tools or even a heterogeneous configuration of both. Can the EDA market develop the distributed-processing tools to support the era of data explosion? This paper will review the progression and performance (run time and scalability) of the distributed-processing MDP tools (DRC, OPC, fracture) along with the impact to the hierarchy preservation. It will consider the advantages of heterogeneous processing over homogenous. In addition, it will provide insight to potential non-scalable overhead components that could eventually exist in a distributed configuration. Lastly, it will demonstrate the cost of ownership aspect of the Unix and Linux platforms with respect to targeting TAT.