New Way of Computing

A New Way of Computing

Janet Gillis | October 29, 2015

Researchers from the Univ. of South Florida College of Engineering have proposed a new form of computing that uses circular nanomagnets to solve quadratic optimization problems orders of magnitude faster than that of a conventional computer.
A wide range of application domains can be potentially accelerated through this research such as finding patterns in social media, error-correcting codes to big data and biosciences.

The artist’s portrayal is an illustration of a nanomagnetic coprocessor solving complex optimization problems andhighlights the shape-engineered nanomagnet’s two unique energy minimum states – vortex and single domain. Source: http://www.usf.edu/engineering/documents/10262015-sanjukta-bhanja.pdf 

<more at http://www.rdmag.com/news/2015/10/new-way-computing; related links: http://www.nature.com/nnano/journal/vaop/ncurrent/full/nnano.2015.245.html (Non-Boolean computing with nanomagnets for computer vision applications. Sanjukta Bhanja, D. K. Karunaratne, Ravi Panchumarthy, Srinath Rajaram and Sudeep Sarkar. Nature Nanotechnology (2015). doi:10.1038/nnano.2015.245. Published online October 26, 2015 [Abstract: The field of nanomagnetism has recently attracted tremendous attention as it can potentially deliver low-power, high-speed and dense non-volatile memories. It is now possible to engineer the size, shape, spacing, orientation and composition of sub-100 nm magnetic structures. This has spurred the exploration of nanomagnets for unconventional computing paradigms. Here, we harness the energy-minimization nature of nanomagnetic systems to solve the quadratic optimization problems that arise in computer vision applications, which are computationally expensive. By exploiting the magnetization states of nanomagnetic disks as state representations of a vortex and single domain, we develop a magnetic Hamiltonian and implement it in a magnetic system that can identify the salient features of a given image with more than 85% true positive rate. These results show the potential of this alternative computing method to develop a magnetic coprocessor that might solve complex problems in fewer clock cycles than traditional processors.]) and  http://www.usf.edu/engineering/documents/10262015-sanjukta-bhanja.pdf (Research Team has Findings Published in Nature Nanotechnology. Nano-scale magnets could compute complex functions significantly faster than conventional computers. October 26, 2015)>