SUSTAINABLE COMPUTING IS CRUCIAL IN OUR GLOBAL EFFORTS TO STOP THE DAMAGE CAUSED TO OUR ENVIRONMENT .
UNCOVERING THE LAYERS
Computing ( HPC ) jobs like simulations , AI and networking tasks .
The solution isn ’ t just hardware . Using the right software and AI models for efficiency is paramount for reducing both cost and environmental impact . By using GPUs , more projects can be completed , faster . One of the world ’ s largest supercomputers , Perlmutter , saw energy efficiency gains of 9.8x for weather forecasting applications when accelerated with GPU hardware .
Gains like this mean that the 8,000 + scientists using the supercomputer can tackle bigger challenges , like molecular dynamics , material science , weather forecasting and subatomic interactions to find new green energy sources .
AI models themselves can also be optimised for efficiency . More efficient training schemas like Colossal-AI ’ s Gemini mechanism , or on a smaller scale in laptops , NVIDIA ’ s Max-Q technologies use Deep Learning to automatically direct power to a CPU , a GPU , or a GPU ’ s memory to increase system efficiency .
Beyond hardware and software , time to delivery or insight can be improved with
AI and simulation to drive sustainability . In energy , Siemens Gamesa uses a digital twin to analyse wind turbine wakes and optimise their arrangement for power generation . In retail , PepsiCo uses computer vision to optimise its distribution centres , allowing faster processing and less waste . Mercedes- Benz uses AI for its dashboard display which considers battery capacity , weather conditions and topography into route planning and Lockheed Martin uses AI and digital twins to predict and direct resources to fighting wildfires .
Accelerating climate science research
Supercomputers can be used to combat climate change by helping us to understand critical points in the changing atmosphere and the long-term effects those changes have . Scientists have long used GPUs to model climate scenarios and predict weather patterns , and advances in AI are continually accelerating climate research .
Utility providers are embracing Machine Learning to move towards a stable and smart green power grid , and power production can be modelled with digital twins to predict maintenance and model new energy sources like fusion-reactors .
Organisations like NVIDIA are working with global organisations to accelerate climate-disaster management with its plan to build Earth-2 , a digital twin of the planet , and training data scientists around the world to use AI to monitor the effects of climate change .
Today ’ s technology , when planned carefully and optimised properly , can help us model trends , predict change and anticipate what the future holds . �
SUSTAINABLE COMPUTING IS CRUCIAL IN OUR GLOBAL EFFORTS TO STOP THE DAMAGE CAUSED TO OUR ENVIRONMENT .
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