Virtual Probe: A Statistical Framework for Low-Cost Silicon Characterization of Nanoscale Integrated Circuits
In this paper, we propose a new technique, referred to as virtual probe (VP), to efficiently measure, characterize, and monitor spatially-correlated inter-die and/or intra-die variations in nanoscale manufacturing process. VP exploits recent breakthroughs in compressed sensing to accurately predict...
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| Veröffentlicht in: | IEEE transactions on computer-aided design of integrated circuits and systems 2011-12, Vol.30 (12), p.1814-1827 |
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| container_title | IEEE transactions on computer-aided design of integrated circuits and systems |
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| creator | Wangyang Zhang Xin Li Liu, F. Acar, E. Rutenbar, R. A. Blanton, R. D. |
| description | In this paper, we propose a new technique, referred to as virtual probe (VP), to efficiently measure, characterize, and monitor spatially-correlated inter-die and/or intra-die variations in nanoscale manufacturing process. VP exploits recent breakthroughs in compressed sensing to accurately predict spatial variations from an exceptionally small set of measurement data, thereby reducing the cost of silicon characterization. By exploring the underlying sparse pattern in spatial frequency domain, VP achieves substantially lower sampling frequency than the well-known Nyquist rate. In addition, VP is formulated as a linear programming problem and, therefore, can be solved both robustly and efficiently. Our industrial measurement data demonstrate the superior accuracy of VP over several traditional methods, including 2-D interpolation, Kriging prediction, and k-LSE estimation. |
| doi_str_mv | 10.1109/TCAD.2011.2164536 |
| format | Article |
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A.</creatorcontrib><creatorcontrib>Blanton, R. D.</creatorcontrib><title>Virtual Probe: A Statistical Framework for Low-Cost Silicon Characterization of Nanoscale Integrated Circuits</title><title>IEEE transactions on computer-aided design of integrated circuits and systems</title><addtitle>TCAD</addtitle><description>In this paper, we propose a new technique, referred to as virtual probe (VP), to efficiently measure, characterize, and monitor spatially-correlated inter-die and/or intra-die variations in nanoscale manufacturing process. VP exploits recent breakthroughs in compressed sensing to accurately predict spatial variations from an exceptionally small set of measurement data, thereby reducing the cost of silicon characterization. By exploring the underlying sparse pattern in spatial frequency domain, VP achieves substantially lower sampling frequency than the well-known Nyquist rate. 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Our industrial measurement data demonstrate the superior accuracy of VP over several traditional methods, including 2-D interpolation, Kriging prediction, and k-LSE estimation.</description><subject>Characterization</subject><subject>Compressed sensing</subject><subject>Frequency domain analysis</subject><subject>integrated circuit</subject><subject>Integrated circuit reliability</subject><subject>Integrated circuits</subject><subject>Interpolation</subject><subject>Monitors</subject><subject>Nanocomposites</subject><subject>Nanomaterials</subject><subject>Nanostructure</subject><subject>process variation</subject><subject>Sampling</subject><subject>Silicon</subject><subject>Statistical analysis</subject><subject>Virtual manufacturing</subject><issn>0278-0070</issn><issn>1937-4151</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpdkEtr3DAQgEVIoZu0P6DkInLpyZsZS_Ijt8V5wtIW8rgKWR63SrxWIsmE5NfHy4YechoYvm8YPsZ-ICwRoT65bVZnyxwQlzkWUolijy2wFmUmUeE-W0BeVhlACV_ZQYwPAChVXi_Y5t6FNJmB_wm-pVO-4jfJJBeTs_PyIpgNvfjwyHsf-Nq_ZI2Pid-4wVk_8uafCcYmCu5tduaF7_kvM_o4u8Svx0R_g0nU8cYFO7kUv7EvvRkiff-Yh-zu4vy2ucrWvy-vm9U6s7LClFWChGw71aHtRC2lta0pa2kLKUXdF4B9KVWLoEzVUanatgJFoutV3oFsy04csp-7u0_BP08Uk964aGkYzEh-irouRFVABTiTx5_IBz-FcX5O16ByUEW-hXAH2eBjDNTrp-A2JrxqBL3Nr7f59Ta__sg_O0c7xxHRf76AcsZRvAPIX4FA</recordid><startdate>201112</startdate><enddate>201112</enddate><creator>Wangyang Zhang</creator><creator>Xin Li</creator><creator>Liu, F.</creator><creator>Acar, E.</creator><creator>Rutenbar, R. 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A.</au><au>Blanton, R. D.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Virtual Probe: A Statistical Framework for Low-Cost Silicon Characterization of Nanoscale Integrated Circuits</atitle><jtitle>IEEE transactions on computer-aided design of integrated circuits and systems</jtitle><stitle>TCAD</stitle><date>2011-12</date><risdate>2011</risdate><volume>30</volume><issue>12</issue><spage>1814</spage><epage>1827</epage><pages>1814-1827</pages><issn>0278-0070</issn><eissn>1937-4151</eissn><coden>ITCSDI</coden><abstract>In this paper, we propose a new technique, referred to as virtual probe (VP), to efficiently measure, characterize, and monitor spatially-correlated inter-die and/or intra-die variations in nanoscale manufacturing process. VP exploits recent breakthroughs in compressed sensing to accurately predict spatial variations from an exceptionally small set of measurement data, thereby reducing the cost of silicon characterization. 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| language | eng |
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| source | IEEE Electronic Library (IEL) |
| subjects | Characterization Compressed sensing Frequency domain analysis integrated circuit Integrated circuit reliability Integrated circuits Interpolation Monitors Nanocomposites Nanomaterials Nanostructure process variation Sampling Silicon Statistical analysis Virtual manufacturing |
| title | Virtual Probe: A Statistical Framework for Low-Cost Silicon Characterization of Nanoscale Integrated Circuits |
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