Download Design for Manufacturability: From 1D to 4D for 90–22 nm by Artur Balasinski PDF

By Artur Balasinski

This booklet explains built-in circuit layout for manufacturability (DfM) on the product point (packaging, purposes) and applies engineering DfM ideas to the most recent criteria of product improvement at 22 nm know-how nodes. it's a useful consultant for format designers, packaging engineers and caliber engineers, masking DfM improvement from 1D to 4D, concerning IC layout move setup, top practices, hyperlinks to production and product definition, for method applied sciences all the way down to 22 nm node, and product households together with stories, good judgment, system-on-chip and system-in-package.

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Additional info for Design for Manufacturability: From 1D to 4D for 90–22 nm Technology Nodes

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Risk reduction of post-OPC performance verification requires the use of highly regular, restricted layout. This will be discussed in Chap. 3. 3 I ncremental Improvements of IC Designs and Products: From 2D to 3D In addition to optimizing the manufacturability of flat layout pattern as discussed in previous sections, DfM techniques are also dealing with design methodology development from to 2D to 3D [41]. Recent years have seen propagation of IC DfM into the multiple aspects of semiconductor IC products.

40). , shaking it up) randomly, applies one of the three moves to evaluate the newly generated B* tree. The move is accepted or rejected depending on whether it improves placement objective such as area or wirelength, and repeated until a satisfactory solution is obtained. The sequential floorplanning relies on repeatedly applying a random move of a block and modifying the floorplan based on the acceptance of the move. A typical run will evaluate thousands of moves, creating a long chain of control and data dependencies, which must be broken to restructure the process for efficient mapping onto a GPU (Graphing Processing Unit), while preserving the solution quality.

Ranging from ±1 to ±4 nm, with would correspond to the worst case gate lengths of 32 nm + EPE_Tolerance. Cell delays are mapped to EPE tolerance using circuit simulation but neglecting the dependence of delay on input slew. Expected mask cost for each cell type can now be extracted as a function of EPE tolerance. Model-based OPC using Calibre on individual cells is followed by fracturing to obtain MEBES data volume for each pair (cell, tolerance). Though cell corrections depend on placement environment, standalone OPC is representative of data volume changes with changing EPE tolerance.

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