Novel memristor wafer integration technology paves the way for brain-like AI chips

A analysis group led by Professor Sanghyeon Choi from the Department of Electrical Engineering and Computer Science at DGIST has efficiently developed a memristor, which is gaining recognition as a next-generation semiconductor gadget, via mass-integration at the wafer scale.

The examine, published in the journal Nature Communications, proposes a brand new technological platform for implementing a extremely built-in AI semiconductor replicating the human brain, overcoming the limitations of typical semiconductors.

The human mind accommodates about 100 billion neurons and round 100 trillion synapses, permitting it to retailer and course of monumental quantities of data inside a compact area.

Next-generation AI analysis goals to develop brain-like AI chips that replicate this construction. Yet, present AI semiconductors stay far much less environment friendly than the human mind, largely due to their intricate circuitry and substantial energy necessities.

The memristor is an rising different possibility that may overcome these limitations. As a semiconductor gadget able to remembering the quantity of present flowing, it concurrently executes reminiscence and computation duties.

Owing to its easy structure, the circuit will be configured with a a lot greater density than typical semiconductors. Specifically, an association in a crossbar format allows dozens of occasions extra data to be saved in the similar space, in comparison with SRAM.

However, memristor integration technology has to this point been restricted to small-scale experimental demonstrations. The major causes embrace course of complexity, low yield (product completion charge), voltage loss, and present leakage, all of which have hindered its growth to large-scale wafer manufacturing.

Thus, Professor Choi and his group carried out joint analysis with Dr. Dmitri Strukov’s group at UC Santa Barbara and launched a brand new strategy of co-designing materials, part, circuit, and algorithm. This technique enabled the implementation of a memristor crossbar circuit that achieved an roughly 95% yield on a 4-inch wafer with out requiring a fancy fabrication course of.

Furthermore, the analysis group efficiently demonstrated a 3D vertical stacking construction. This signifies the chance of a memristor-based circuit being expanded right into a large-scale AI computation system in the future.

In addition, when a spiking neural community was utilized based mostly on the proposed technology, notable effectivity and secure execution have been confirmed in precise AI computation.

Professor Choi acknowledged, “This study proposed a method for improving memristor integration technology, which had been limited in the past. We are expecting it to lead to the development of a next-generation semiconductor platform in the future.”