Chinese algorithm boosts Nvidia GPU performance 800-fold in science computing
Published: 7:00am, 30 Jan 2025 A high-performance algorithm that could solve complicated material design problems on consumer GPUs has been developed by Chinese researchers, achieving a groundbreaking 800-fold increase in speed over traditional methods. Developed by a research team at Shenzhen MSU-BIT University, co-founded by Lomonosov Moscow State University and Beijing Institute of Technology, the new algorithm enhances the computational efficiency of peridynamics (PD), a cutting edge, non-local theory that solves difficult physical issues such as cracks, damage and fractures. It opens up new possibilities for solving complex mechanical problems across various industries, including aerospace and military applications, on widely available chips that are low-cost and not subject to US sanctions .
Peridynamics has proven advantageous in modelling material damage, but its high computational complexity has traditionally made large-scale simulations inefficient, with issues such as high memory usage and slow processing speeds. To address these challenges, Yang Yang, an associate professor, leveraged Nvidia's CUDA programming technology to create the PD-General framework. By making an in-depth analysis of the chip's unique structure, her team optimised algorithm design and memory management that led to a remarkable performance boost. Their research was published in the Chinese Journal of Computational Mechanics on January 8.
'This efficient computational power allows researchers to reduce calculations that would typically take days to just a few hours – or even minutes – using an ordinary home-level GPU, which is a significant advancement for PD research,' Yang wrote in the paper.
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