Technology Introduction:
This project focuses on the development and promotion of Digital Annealing (DA) and GPU-based annealing technologies, combining hardware acceleration with software innovation. On the hardware side, DA and GPU annealing are applied to combinatorial optimization, scheduling, experimental design, drug molecule discovery, photomask inverse design, and MicroLED process optimization. On the software side, the work centers on QUBO model construction and transformation, AI-enhanced solving strategies, and GPU parallel performance improvement.

The project will also establish a localized annealing platform to reduce cost, enhance flexibility, and ensure privacy, thereby supporting both academic research and industrial adoption. Through this integration of hardware and software, the project aims to accelerate practical applications, strengthen domestic competitiveness, and open new opportunities for innovation across pharmaceuticals, semiconductors, advanced manufacturing, and other fields.
Industry Applicability:
Digital Annealing (DA) accelerates drug discovery by improving molecular screening and binding energy evaluation, thus enhancing efficiency and reducing experimental costs. It is a valuable tool for advancing new drug development. In combinatorial optimization, DA addresses key problems: solving scheduling for better workforce and resource allocation, optimizing routing for logistics and transportation, and tackling knapsack problems for portfolio and asset management. Beyond healthcare, DA is applicable in semiconductors for photomask inverse design, in display technologies for optimizing MicroLED fabrication, and in manufacturing for smarter scheduling and higher capacity utilization. These diverse applications highlight DA’s broad cross-industry potential as both a scientific and industrial innovation driver.