
GPUs in University Research: Powering the Next Era of Discovery
Universities are increasingly adopting Graphics Processing Units (GPUs) to accelerate research in fields like medicine, climate science, and artificial intelligence, which depend on processing massive datasets. Their parallel processing capabilities enable breakthroughs in complex tasks such as protein folding, large-scale climate modelling, and analysing cultural texts. The NVIDIA H100 GPU is a key technology in this shift, offering significant improvements in speed, memory bandwidth, and energy efficiency, allowing researchers to undertake larger projects. Beyond research, GPUs are being integrated into university curricula to prepare students for the modern AI workforce. While institutions face challenges like high costs and management complexity, recommendations include investing in shared clusters, forming vendor partnerships, and adopting hybrid on-premises and cloud models to maximise investment and foster innovation.
14 minute read
•Energy and Utilities