Biological Computing

The search for new computing paradigm is encouraging researchers to explore uncharted territories. Researchers have been working on using network-based computing and highly efficient molecular motors. The main advantage of this approach is extreme low power and it could solve the problem with high parallelism.

One could argue that quantum computer also promise of similar promises regarding performance and power consumption. However, we need to understand that quantum computers need almost zero kelvin temperature and on the other hand, bio computing do not fave this stringent demands of operation environment.

In this bio-computer, protein or any other bio-molecular  solve the problem by moving through nano network of channels which is designed according to the algorithm, it intends to implement.

”The biological computing units can multiply themselves to adapt to the difficulty of the mathematical problem”, explains Till Korten, Ph.D. from TU Dresden, co-coordinator of the project. These biological computing units act like processor and memory as they traverse the network.

One can click here to know more about the development.

 

Multi-Chip module GPU

GPUs has played and will play an important role in the development of high-performance computing

No doubt, Graphic Processor Units will be key to develop artificial intelligence and is required in conditions requiring extensive computing resources. GPUs are becoming more powerful with each year, and Moore’s law can be attributed for such improvements over the year. However, with the law slowing down, the number of transistors that can be fit in a die-size won’t grow, leading to a halt in performance improvement. This could impede the progress of many promising technological advancements.

Researchers have proposed Multi-Chip Module GPU (MCM-GPU) architecture based on aggregating GPU modules rather than using single high-performance chip used at