TRENDING
Here are three reasons why TCO is rising and how 3D optics can help tackle them .
1 . AI is rapidly increasing data centre capacity demand
McKinsey recently released an eye-opening new study on the global demand for new data centre capacity , predicting that the overall demand for data centre capacity ‘ could rise at an annual rate of between 19 and 22 per cent from 2023 to 2030 ’. The report new infrastructure and to improve sustainability . To achieve this , the industry needs to adopt new ways of performing AI computation and reduce the power needed for AI processing , so that the processing can be done within the power limits of these data centres . This will take vision and leadership but given the power capacity constraints and the insatiable demand , it is clear that now is the time to look at these different approaches . One such approach is to use technologies like 3D optics .
One of the limitations of data centres is the current use of power-hungry silicon chip based – AI accelerators . These current chips are unable to efficiently scale and provide the level of capacity needed for AI ’ s growing compute demand within reasonable power constraints . But if data centres can use an optical AI accelerator , the benefits of low-power and energy efficiency , which are already seen in optical communications , can be utilised for computation .
Crucially , using optics for computation leads to a far more scalable approach so that the increasing demands of AI computation can continue to be met .
2 . Data centres are power hungry – and current hardware is too inefficient
The simple truth is that current hardware will not be able to efficiently match the surging performance demand required by AI models – it is either way too expensive or not efficiently possible with current chip technology .
AI is placing immense pressure on the energy consumption of servers in data centre racks . As the McKinsey study showed , ‘ average power densities have more than doubled in just two years , to 17 kilowatts ( kW ) per rack . . . and are expected to rise to as high as 30 kW by 2027 as AI workloads increase .’
Phil Burr , Director , Lumai highlights that AI is the driving force behind this , with AI-ready data centre capacity demand at 33 % and GenAI at 39 %.
To create this capacity , not only are the major cloud service providers building their new data centres but also partnering with colocation providers to use their facilities . But while McKinsey notes the prices charged by colocation providers ‘ fell steadily from 2014 to 2020 in most primary markets ’, they ‘ then rose by an average of 35 % between 2020 and 2023 ’, clearly reflecting the demand .
While this demand cannot be met solely by reusing or upgrading current infrastructure , it should be part of the overall mix both to reduce the need to build
With models like ChatGPT , energy consumption can be over ‘ 80kW per rack ’, while Nvidia ’ s latest chip may need rack densities ‘ up to 120kW ’.
The direct costs of supplying this energy and the infrastructure costs of cooling all of this power are significant ; each watt of power consumed necessitates more cooling , more energy , more infrastructure and therefore more generated emissions .
Optical AI acceleration uses photons to compute instead of electrons and performs highly parallel computing . This means that optical AI accelerators use only 10 % of the power of a GPU ( currently used in datacentres ) while also providing the necessary leap in performance . If optical computation can enable more efficient AI accelerators , this can increase the lifespan
22 INTELLIGENTCIO EUROPE www . intelligentcio . com