Memristor 2014 - Workshop on Memristor Science & Technology

Conventional computing, including both hardware platforms and computer languages, seems to be close to its physical limits in terms of speed and data density. Classical Von Neumann architectures are known to be great in number crunching; nevertheless, they struggle with tasks like face recognition, real-time navigation control, object segmentation and depth perception. On top of that, CMOS technologies are also approaching the nano-scale floor, with devices attaining comparable dimensions to their constituting atoms, imposing significant challenges on the performance and reliability of analogue and digital circuits hindering the well-exploited correlation of Moore?s law with computation capacity.
Memristors were first conjectured based on the missing constitutive link between flux and charge by Leon Chua as published in his seminal paper in 1971, which was further extended by L. O. Chua and S. M. Kang in their 1976 paper on memristive devices and systems. Recently, a physical realization of memristors was reported in Nature by HP?s Stan Williams team in 2008. To date, memristor represents the latest technology breakthrough to build electronics devices with characteristics that show an intriguing resemblance to the brain’s synapses.
The One-day Workshop on “Memristor Science & Technology” is organized in plenary talks, Positions papers and sessions with selected and invited contributions.
The One-day Workshop on “Memristor Science & Technology” will be a multidisciplinary forum for researches and industrial companies to present the latest advances in the field of memristor circuits and their latest breakthrough applications.
TOPICS AREA
You are invited to participate and submit your contributions to the DATE 2014 Friday Workshop on Memristor Science & Technology. The areas of interest include (but are not limited to) the following topics:
Nonlinear memristor dynamics
New device technologies (materials and fabrication)
Device models for CAD
Novel memristor circuits
Systems architecture harnessing memristor properties
Neuromorphic Applications