A number of developments over the past decades have paved the foundations for nano-technology and nano-science. It was the famous Nobel prize winning physicist Richard Feynman who talked of “tiny machinery” of the size of an atom that could be “worked on” to produce the next generation of computing devices. Another scientist, Adleman, in 1994 produced an unusual DNA-based “easy” solution to a well known “NP-hard problem” in graph theory. The ideas of quantum computing that use quantum interference to model massively parallel computers using “natural” materials provided another impetus to nano-computing. Some amazingly interesting alternatives to the conventional “lithography” provided the possibility of nano-computing entering the mainstream. Thanks to Moore’s Law, the computing power of a microprocessor chip has been doubling every eighteen months; to continue to keep the pace of growth of Moore’s Law, we would be forced to look at devices that are much smaller in size and much faster in performance than currently available microsystems; that is the place nano-computing would fill in. Naturally, as we move from “micro” technology to “nano” technology, the complexity increases thousand fold; of course, the challenges posed make this area thousand times more interesting too.

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Broadly, the technology development in nano computing can be classified as follows: Electronics engineers working on two state devices that are much faster and exceptionally smaller, thereby providing alternatives to transistors; logic design using the next generation of transistors; and, fabrication of sub-systems using new forms of lithography that goes well beyond the current state of micro miniaturisation. Mechanical engineers who are perfecting “a miniature Babbage Engine” and working on MEMS technology — micro motors, sensors and transducers that are re-designed for the nanotechnology devices and systems. Computer scientists, physicists and mathematicians perfecting new models of computing, including alternatives to Von Neumann architecture that dominates contemporary computing models; alternative realisation of Turing Machine using nanotechnology devices; new paradigms that are possible due to massively parallel computing architectures that are possible using “natural” materials; and, foundational mathematical issues in cryptography, computational complexity and new generation algorithms. What are the challenges for the educators and students? A key challenge in nano-computing is to work on interdisciplinary mode with experts drawn from sciences, engineering and computing disciplines. Broadly the students must be exposed to: Characterising, measurement and a larger understanding of issues relating to devices that operate at nanometer size; challenges involved in designing, analysing and simulating sub-systems that uses nano-size components; “manufacturing” processes and “fabrication” techniques at such extremely small sizes, using new generation materials and tools (often biological nature); innovate, design and develop products that exploit the power of such thousand fold powerful computing model that would stabilise over the decade (till 2010) and grow over the next couple of decades (2011-2030). We need both knowledge-oriented and learning-oriented education in this evolving area that holds immense promise.

Naturally, nano-technology is exciting. Recently the First International Conference on Nanotechnology was hosted by the Shanmuga Engineering College, Tanjore (in Tamilnadu) and research activities have been initiated. India should get an early bird advantage in this emerging science through some fundamental contributions.

(S Sadagopan is the Director of the Indian Institute of Information Technology, Bangalore. His e-mail is ss@iiitb.ac.in)