ABSTRACT
This paper describes the structured ASIC technology and impacts to the implementation flow. With an optimized and programmable structure, the structured ASIC technology indeed introduces a dramatically reduce ASIC cost and manufacturing turn-around time. While, the structured ASIC implementation flow is more complex than the conventional cell-based flow. There would be slightly impacts to structured ASIC implementation problems. Finally, the structured ASIC solutions provided by Faraday would be given. There are 3 structured ASIC solutions for customers' different applications. The three solutions are MPCA (Metal programmable Cell Array), MPIO (Metal Programmable I/O), and the structured ASIC platform. With the most competitive architecture, our customers can implement their ASIC at a lower cost with a faster turn-around-time.
- Magma BlastFusion User's Guide and Document Reference Manual. 2003.Google Scholar
- Cadence SocEncounter User's Guide and Document Reference Manual. 2003.Google Scholar
- Synopsys Design Compiler User's Guide and Document Reference Manual.2003.Google Scholar
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