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dc.contributor.author俞力行en_US
dc.contributor.authorYu, Li-Xingen_US
dc.contributor.author蕭培墉en_US
dc.contributor.authorXiao, Pei-Yongen_US
dc.date.accessioned2014-12-12T02:19:46Z-
dc.date.available2014-12-12T02:19:46Z-
dc.date.issued1997en_US
dc.identifier.urihttp://140.113.39.130/cdrfb3/record/nctu/#NT864394010en_US
dc.identifier.urihttp://hdl.handle.net/11536/63636-
dc.description.abstractchip placement is very important in MCM design and the problem has been provento be NP-hard even for the point-model. For the design of full custom MCM, it hasbeen made more harder with various additional constraints on its bare die sizeand layout region shape/dimension. In order to solve the MCM placement problem,we had a intensive study of a series of journal papers about query-based self-organizing neural network (QBSONN) and got inspiration. QBSONN is a general neuralnetwork model which uses the query oracle technique in machine learning to improvethe learning process of the self-organizing neural network. The model was used toresolve VLSI cell placement and succeeded in yielding a proper placement result. In this thesis, we attempt to apply QBSONN to resolve the MCM placement problemand implement a MCM placement tool "AMPER 1.0". The AMPER 1.0 is developed by usingVisual C++4.0 (MFC) and works on Windows 95 environment. So it has a friendlygraphical user interface and a high portability. During the development process ofthe AMPER, we have learned a valuable experience for Windows programming. The wirelength minimization and module overlap-free are as our primary objective. Our placerconsiders the actual shapes of the bare dies and can resolve the rectangular chipplacement problem on a rectilinear region with various layout styles (such as chiparray or full custom). Finally, the placement results of some benchmark test circuitsare presented which demonstrate that our MCM placer is certainly effective.zh_TW
dc.language.isozh_TWen_US
dc.subject多晶片模組zh_TW
dc.subject自我組織類神經網路zh_TW
dc.subject擺置zh_TW
dc.subject佈局自動化zh_TW
dc.subject資訊zh_TW
dc.subject電腦科學zh_TW
dc.subjectMCMen_US
dc.subjectself-organizing neural networken_US
dc.subjectplacementen_US
dc.subjectautomatic layouten_US
dc.subjectINFORAMTIONen_US
dc.subjectCOMPUTER-SCIENCEen_US
dc.title多晶片模組佈局自動擺置研究zh_TW
dc.titleAutomatic Placement for MCM Layouten_US
dc.typeThesisen_US
dc.contributor.department資訊科學與工程研究所zh_TW
Appears in Collections:Thesis