Rebooting Computing

The need for High Performance Computing data centers is rapidly growing in order to cater to the growing demand in processing and storing Big Data arising due to the Digital India and other initiatives.

We are working towards a vision of realising resource constrained magnetic chips for ultra low power portable artificial intelligent applications. Nanomagnetic Logic (NML) based computation started emerging as a key alternative towards the Beyond CMOS based Rebooting Computing paradigm.

Many modern systems such as speech and face recognition systems and IoT enabled devices for remote health monitoring require highly computationally and energy-intensive neural networks. Hence, it is not practically affordable to perform these computations in the portable hand-held devices. With these major limitations, all the machine learning algorithms used in these Artificial Intelligent applications runs on remote systems.

These factors put forth a clear demand for low power chip design in the area of Artificial Intelligence. To address these issues, highly intensive convolutions should be performed using ultra low power, least energy consuming, and area efficient devices, thus motivated us to explore the MQCA based nanomagnetic architecture designs for next generation rebooting computing platform.

Performing AI computing on edge with approximate nanomagnetic logic deployed on the magnetic ICs is an attempt towards the futuristic computations.

The power consumed by the modern chips are enormously high as the standby power required to maintain the logic states in the chip is equal to the power consumed by the chip during computation. 

Traditionally, electronic phenomena are used for information processing (CMOS Devices) and the magnetic phenomena are widely used for data storage (Hard Disks). However, the traditional CMOS devices consumes power supply (standby power) to maintain its ‘logic states’ required for computing information, thus making it volatile. 

On the contrary, the emerging next generation electronic devices using coupled nanomagnets’ for computing and information propagation requires no standby power to maintain its logic states thus making it non-volatile. Thus the magnetic chip design started emerging as potential alternative to CMOS based computing which faces challenges with the Moore's law approaching towards its end.

Dr. Santhosh Sivasubramani says, "We are glad that our work has been featured in the International Roadmap. International recognition to this scholarly contribution in the emerging field of Rebooting Computing motivates us further to perform translational research from fundamentals to its applications. Energy efficient computing is the need of the hour and this work will certainly pave way towards it". Speaking about this contribution Dr. Amit Acharyya says "This is the first step towards futuristic computation. We are proud to be in the 0.1% of contribution from Indian Academia towards the global contribution for IRDS". This research performs the Boolean Optimizations on the unexplored configuration of three input nanomagnetic majority gate. In addition, the researchers have achieved area efficient and high-speed architecture design methodology for binary adder using this proposed majority gate. The results show promising aspects of its envisaged applications in next generation low power magnetic computing devices.

Magnetic Graphene for Rebooting Computing:

The growing popularity of digital devices has spurred the need for integrated circuits that are light weight, consume ultra-low power and are highly efficient. Technology companies are increasingly focusing on nano electronics for developing such devices but using nano material like graphene is still challenging as there is little evidence of it showing intrinsic magnetism. 

Graphene came into the limelight after its exceptional quantum properties fetched Andre Geim and Konstantin Novoselov the 2010 Nobel Prize in Physics. " In order to make ‘graphene processors’ a reality, the key issue to be addressed is thermal management. To achieve this, we need a mechanism which could harness excess heat generated in the operation of gadgets to induce magnetism. Our group envisaged a processor application using a single-layer zigzag graphene nanoribbon which could potentially harness heat generated in the system, to reduce the voltage requirement and to perform computations (information propagation) using spins.

RSL Quantum explores the intertwining of Nano and Quantum aspects of Computing. 

The need for Rebooting Computing has been well established in the recent days and in particular the focus towards Beyond CMOS computing paradigm. Nanomagnetic logic (NML) based computing architecture design methodology started emerging as a potential candidate representing spintronics and nanomagnetics.