CLOUD
“STORING AND PROCESSING DATA TO TRAIN MACHINE LEARNING AND LARGE LANGUAGE MODELS IS STEADILY DRIVING UP ENERGY CONSUMPTION ”
MARC GARNER SVP SECURE POWER EUROPE , SCHNEIDER ELECTRIC
Turning the technology on itself Another way for data centre leaders to cope with the increasing demands of AI is to use the technology to their advantage .
“ Data centres can benefit from using AI-powered automation , data analytics and machine learning to find opportunities for efficiency gains and decarbonisation ,” Garner asserts . “ By using data insights more efficiently , we can drive new , more sustainable , behaviours .
“ This process is powered by physical infrastructure and software tools thatsupport data centre design and operation , including DCIM , EPMS , BMS , and digital twins . These applications decrease the risk of unexpected behaviour with complex electrical networks and provide a digital replica of the data centre to identify constrained power and cooling resources to inform layout decisions .”
For instance , Equinix improved the energy efficiency of its data centre by 9 % using AI-based cooling , which enabled the company to reduce the energy consumption of cooling systems by regulating them more effectively and making the system more efficient .
Achieving more computing power within the same physical footprint As Garner concludes , what ’ s clear is that AI applications are escalating power consumption in data centres at a time when they need to become more sustainable . Yet , AI is also providing the intelligence to design and operate data centres in a smarter , more energy-efficient way , and if deployed correctly , can help the planet ’ s journey toward net zero .
“ By combining the key attributes of data centre physical infrastructure with the efficiency gains of AI , owners , operators and end-users can more effectively manage the power demands of high-density AI clusters while maintaining efficiency , reliability and sustainability ,” he says .
98 March 2024