Generative AI has incredible potential to improve productivity and drive innovation across domains and sectors. But the challenge to enterprises is twofold as cost and carbon footprint complicate the path forward.
GenAI models require growing volumes of data and storage, and the graphics processing units (GPUs) on which GenAI relies to move and process data require an enormous amount of energy to run. The complexities of price and power drain that result from the massive amounts of data and GPUs are a huge hurdle for enterprises seeking to create a greener, more sustainable future.
This has important implications for hyperscalers and other enterprises that operate data centers, as well as for businesses, communities, and all living things across the planet.
Despite barriers to early adoption, GenAI is here to stay. Software developers, support staff, and consumers are already using GenAI, which will only surge with greater applications and adoption, thus becoming as common as mobile devices.
That said, sustainable data centers will be critical for GenAI expansion and the world.
I predict that sustainable data centers will become mandatory in the next five years.
Here are five steps to help your enterprise build a sustainable data center:
1. Address data management
Data is the lifeblood of GenAI applications, so it’s important for enterprises to have data management systems and strategies that provide access to the right data at the right time.
Application data may reside on premises, in the cloud or the edge. Ensure that your data management strategy enables you to access data from whichever platform suits your needs at the optimal cost and in a secure manner. This will contain costs, limit your risk, and help you differentiate your business.
To address the rapidly growing data volume of GenAI, you should also explore compression technology, which can store the same data, with 60% less footprint, decreasing your need for power and lowering your carbon emissions.
Distributed, dark data is another challenge. With so much data in so many places, you may not know where all of your data resides. Address that by using data cataloging, compliance, ediscovery and governance solutions to understand what data you have, where it sits, and how to integrate data to reduce waste and use your data to drive business results.
Data governance and compliance can be tricky given the rapidly intensifying complexity. Many organizations lack the skills, industry knowledge and expertise to tackle this alone. Engage with a partner with deep industry knowledge that has baked that knowledge into their tools.
2. Explore your data store
Optimal data management will help you strike the right balance between the data storage and processing you need to support your GenAI applications and your sustainability commitments.
Don’t store multiple copies of data. Only hang on to the data that your business really needs.
Keep the most important information in hot storage. Put the data for which you don’t have an immediate need in cold storage, which will reduce your costs and lower your carbon footprint.
Select a data storage solution that is highly engineered for performance and sustainability. Validate the solution by reviewing what independent third parties say about its sustainability.
3. Process data where it lives
Data movement consumes time and power, so avoid unnecessarily moving data.
Ensure you have the technology to process data close to the source and use metadata management to access what you need and transport only the data you need to move.
4. Implement liquid cooling systems
GenAI attracted 100 million users in less than two months after launch, and an Enterprise Strategy Group study sponsored by Hitachi Vantara indicates that 97% of enterprises see GenAI as a top five priority. But the massive GPU infrastructure needed to power GenAI applications generates a lot of heat in data centers.
Over the years, companies have tried to cool equipment by doing everything from submerging data centers in the ocean to locating data facilities in remote parts of the world like Iceland.
However, you don’t need to dive deep or travel far to cool your data center. Instead, you can use liquid cooling, which can.
5. Take a holistic approach
Rapidly growing data, GPU requirements and data centers — and the complexity, risk and environmental impacts they entail — make sustainability more important than ever.
The green data center of the future will be simple, smart, secure, self-healing, scalable and sustainable. It calls for a holistic approach that addresses server, software and storage efficiency, employs the right mix of sustainable energy sources, and uncovers opportunities to use innovations and eco-friendly solutions to make the best use of data and limit carbon footprint.
When companies and data centers are more sustainable, everybody benefits. The world becomes a better place, customers enjoy better outcomes and businesses grow stronger.