VLSI CMOS-memristor Building-block for Future Autonomous Air Platforms

Award Information
Agency:
Department of Defense
Amount:
$100,000.00
Program:
STTR
Contract:
FA8750-11-C-0114
Solitcitation Year:
2010
Solicitation Number:
2010.B
Branch:
Air Force
Award Year:
2011
Phase:
Phase I
Agency Tracking Number:
F10B-T31-0242
Solicitation Topic Code:
AF10-BT31
Small Business Information
Orora Design Technologies, Inc.
18378 Redmond Fall CIty Road, Redmond, WA, 98052-
Hubzone Owned:
N
Woman Owned:
N
Socially and Economically Disadvantaged:
N
Duns:
010947088
Principal Investigator
 Lili Zhou
 Senior Member of Technical Staff
 (425) 702-9196
 lili.zhou@orora.com
Business Contact
 Tracey Luo
Title: Board Member
Phone: (425) 702-9196
Email: tracey.luo@orora.com
Research Institution
 University of Albany
 Professor W Wang
 CNSE, 255 Fuller Rd.
Albany, NY, 12222-
 (518) 956-7057
 Nonprofit college or university
Abstract
ABSTRACT: In this project, Orora Design Technologies, Inc. is teaming up with researchers from the University at Albany and the University of Washington to develop techniques to design, simulate and fabricate CMOS-memristor CMOL crossnet building blocks and neuromorphic processors. Phase I objective is to simulate and demonstrate autonomous computing building cell blocks with power consumption of less to 2x10-11 watts and footprint area of less than 2x10-13 m2. Specific emphasis will be on (1) exploring the efficient and reliable fabrication/integration methods for MEMRISTOR devices and CMOS devices; (2) designing and demonstrating a CMOL crossnet cell (3) designing and simulating the CMOS-MEMRISTOR crossnet processor and the development of suitable CAD tool framework. This project is expected to show the potential of memristor-like technology (passive memory devices: memristor, magnetic junction, and/or continuous variable resistance devices) for enabling massively parallel large scale neuromorphic computing processor architecture development. BENEFIT: .. It is expected that this project will enable new ultra-compact, ultra-fast, and self-learning CMOS-memristory systems for both military and commercial applications such as command, control, surveillance and communications, as well as consumer electronics, digital signal processing and biomedical applications.

* information listed above is at the time of submission.

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