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697GG Nano Computering Fall 2005. CMOL: Device, Circuits, and Architectures. Konstantin K.Likharev and Dmitri B. Strukov Stony Brook University. Prepared by Sheng Xu. The Device. There is a tradeoff between molecule simplicity and functionality
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697GG Nano Computering Fall 2005 CMOL: Device, Circuits, and Architectures Konstantin K.Likharev and Dmitri B. Strukov Stony Brook University Prepared by Sheng Xu
The Device • There is a tradeoff between molecule simplicity and functionality --Simple ones with nonlinear but monotonic I-V curves are insufficient for highly functional intergrated circuits --Complex molecule have many configurations are “soft” to thermal fluctuations --Short and ridig molecules have just few metastable internal states is best choice --Example of a possible circuit: • --The challenges : • 1. no process is available of acceptable yield yet due to the difficulty to ensure a unique position of the molecule relative to the electrodes • possible solutions: chemical synthesis of molecules including large “floating electrodes”; Self-assembled monolayer (SAM) on the surface • 2.Fabrication of wires with nanometer-scale cross-section is difficult • possible solutions: Nanoimprint, interference lithography
The circuit • The only plausible way toward high-performance nanoelectronic circuits: hybrid of integrate molecular device, nanowires and CMOS • Fabrication brings the circuit design two requirements: no precise alignment with each other and with CMOS subsystem • The resistivit of semiconductor nanowire would be too high for hybrid circuits • Chemical synthesized semi- nanowires into highly ordered parallel arrays is not available yet. • An approach and CMOL circuit implementation -form a small angle between nanowire and CMOS wires need precise aligned with former nanowire -CMOL modified the form “In-Bar” networks by providing contact pins distributed all over the circuit area.
CMOL Memories • CMOL architecture need to be defect-tolerant -Chemically-dricted self-assemlby of molecular deviecs can not achieve 100% yield • Two major techniques: memory matrix reconfiguration, error correction • Several analysis results: chip area VS linear n size of blocks optimized area per bit VS the molecular device yield
CMOL FPGA: Boolean Logic Circuits • Why FPGA style circuits -The location of a defective gate from outside is hardly possible -The error detection and correction method is inefficient • Two FPGA varieties: LUT & PLA • existing problem: • LUT: memory array can not provide address decding and output signal sensing. Must be implemented in CMOS subsystem leading to a large overhead • PLA: the fraction of open device is of the order of on half comparing to LUT’s one devie which leads to a high power consumption. Meanwhile dynamic logic is not realistic in nanodevices. • CMOL cell-based FPGA • Mol FPGA configuration approach to reduce original exponential circuit size. NOR input
CMOL CrossNets: Neuromorphic Networks • From Neural network and more… • Neural cell bodies: nanowires • Axon and dendrites: mutually perpendicular nanowires of the CMOL crossbar • Synapses: molecular latching switches • Remark property of CMOL CrossNet: the connectivity could be very large • No external software code needed, can be trained to perform certain tasks. • Challenges: --swicth between continuous signal and discrete --difficult to control synapse --processes of control single-electron latches are statistical FlossBar CMOL CrossNet