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Christopher Schuermyer Phones & Addresses

  • 9750 SE 134Th Ave, Happy Valley, OR 97086 (503) 465-2793
  • Clackamas, OR
  • 2131 Evans Ave, Troutdale, OR 97060 (503) 465-2793
  • Portland, OR
  • Anderson Island, WA

Publications

Us Patents

Cell-Aware Fault Model Creation And Pattern Generation

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US Patent:
20100229061, Sep 9, 2010
Filed:
Mar 5, 2010
Appl. No.:
12/718799
Inventors:
Friedrich HAPKE - Winsen, DE
Rene Krenz-Baath - Hamburg, DE
Andreas Glowatz - Heidenau, DE
Juergen Schloeffel - Buchholz/Sproetze, DE
Peter Weseloh - Rosengarten/Westerhof, DE
Michael Wittke - Pinneberg, DE
Mark A. Kassab - Wilsonville OR, US
Christopher W. Schuermyer - Happy Valley OR, US
International Classification:
G01R 31/3177
G06F 11/25
US Classification:
714740, 714E11155
Abstract:
Cell-aware fault models directly address layout-based intra-cell defects. They are created by performing analog simulations on the transistor-level netlist of a library cell and then by library view synthesis. The cell-aware fault models may be used to generate cell-aware test patterns, which usually have higher defect coverage than those generated by conventional ATPG techniques. The cell-aware fault models may also be used to improve defect coverage of a set of test patterns generated by conventional ATPG techniques.

Hybrid Memory Failure Bitmap Classification

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US Patent:
20130219216, Aug 22, 2013
Filed:
Feb 15, 2013
Appl. No.:
13/769230
Inventors:
MENTOR GRAPHICS CORPORATION - , US
Christopher W. Schuermyer - Happy Valley OR, US
Assignee:
MENTOR GRAPHICS CORPORATION - Wilsonville OR
International Classification:
G06F 11/07
US Classification:
714 26
Abstract:
Aspects of the invention relate to techniques for classifying memory failure bitmaps using both rule-based classification and artificial neural network-based classification methods. The rule-based classification method employs classification rules comprising those for global failure patterns. The artificial neural network-based classification method classifies local failure patterns. One of the artificial neural network models is the Kohonen self-organizing map model. The input vector for a failure pattern may contain four elements: pattern aspect ratio, failing bit ratio, dominant failing column number and dominant failing row number.

Generating Root Cause Candidates For Yield Analysis

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US Patent:
20140059511, Feb 27, 2014
Filed:
Aug 22, 2013
Appl. No.:
13/973998
Inventors:
Christopher Schuermyer - Happy Valley OR, US
Jonathan J. Muirhead - Tigard OR, US
Leo Chang - Taichung City, TW
Assignee:
Mentor Graphics Corporation - Wilsonville OR
International Classification:
G06F 17/50
US Classification:
716136
Abstract:
Aspects of the invention relate to yield analysis techniques for generating root cause candidates for yield analysis. With various implementations of the invention, points of interest are first identified in a layout design. Next, regions of interest are determined for the identified points of interest. Next, one or more properties are extracted from the regions of interest. Based at least on the one or more properties, diagnosis reports of failing devices fabricated according to the layout design are analyzed to identify probable root causes.

Unique Binary Identifier Using Existing State Elements

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US Patent:
20080052029, Feb 28, 2008
Filed:
Aug 24, 2006
Appl. No.:
11/466846
Inventors:
Robert B. Benware - Clackamas OR, US
Mark A. Ward - West Linn OR, US
Christopher W. Schuermyer - Troutdale OR, US
Assignee:
LSI LOGIC CORPORATION - Milpitas CA
International Classification:
G06F 19/00
G06F 17/50
US Classification:
702117, 716 1, 702108
Abstract:
A method of retrieving a unique, repeatable identification value from an integrated circuit by identifying a plurality of state elements within the integrated circuit, where the state elements are part of standard functional circuitry within the integrated circuit, and are not part of a specialized circuit designed to primarily produce the unique, repeatable identification value, performing an initializing process on the state elements to bring the state elements to repeatable states, where the repeatable states of different state elements are dependent at least in part on differences between the different state elements, reading the repeatable states on the state elements, and joining the repeatable states into a binary number as the unique, repeatable identification value.

Generating Root Cause Candidates For Yield Analysis

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US Patent:
20170103158, Apr 13, 2017
Filed:
Sep 12, 2016
Appl. No.:
15/263014
Inventors:
- Wilsonville OR, US
Christopher Schuermyer - Happy Valley OR, US
Jonathan J. Muirhead - Tigard OR, US
Chen-Yi Chang - Taichung City, TW
Assignee:
Mentor Graphics Corporation - Wilsonville OR
International Classification:
G06F 17/50
Abstract:
Aspects of the invention relate to yield analysis techniques for generating root cause candidates for yield analysis. With various implementations of the invention, points of interest are first identified in a layout design. Next, regions of interest are determined for the identified points of interest. Next, one or more properties are extracted from the regions of interest. Based at least on the one or more properties, diagnosis reports of failing devices fabricated according to the layout design are analyzed to identify probable root causes.
Christopher William Schuermyer from Happy Valley, OR, age ~45 Get Report