Chelsea Robinson, Product Marketing Manager, Digital Realty, highlights what makes a colocation provider AI-ready, and the way today’s enterprises can spot innovative colo businesses. What once began as a dystopian, futuristic, robots-take-over-the-world notion is currently getting a universally accepted strategy for conducting companies. Virtually all industries are adopting some form of AI to stay ahead of competition, simplify strategies for company challenges, and enhance customer experience.
But how can companies implement AI into their operations? It comes down to their IT environment. Not each facility is equipped to encourage AI workloads.
This server colocation the special chance to research what actually qualifies a data center to support artificial intelligence: the ability to support high-density workloads and power requirements, as well as the ability to provide innovative cooling technology to keep those workloads running and stable.
Landauer’s Principle is a theoretical proof that was developed in 1961 that shows a upper limit of the number of computations could be processed for each kilowatt-hour. At a fundamental level, computers need to operate within the laws of physics and additional computing power causes energy use and generates more heat. Where does this leave organizations who want to maximize or optimize their power?
Power Innovation GPUs (graphics processing units) can perform complex mathematical algorithms considerably faster and economically than a standard CPU (processor ). One example of this is NVIDIA’s DGX-1 servers, where the GPU technology could absorb and process 140 times faster than CPU-only servers. This would have a server that is CPU-only within hours. With this kind of learning that is profound it takes 5 hours with the DGX-1. This gifts an opportunity to improve their information processing and company performance to companies. Think of what a business could do with 1-2 petaflops of calculating power and the way which may help an organization accomplish their business objectives faster.
With the rise of artificial intelligence and machine learning, energy efficiency takes on new importance for data centers. The volume of information that machine learning software require to process the high-density loads (think complex algorithms, predictive modelling and more) increases power needs dramatically.
When energy-demanding artificial intelligence software are known to use more than 30 kW per rack, electricity demands frequently exceed standard data centre power standards. Colocation providers and Information centers need to make sure that they have redundant power plans to minimize downtime.
With greater density workloads comes more power, which translates to more heat. Not many data centers are built to support the requirements placed on these gains in power and cooling requirements since power consumption can translate to a need for cooling methods beyond fan cooling system. Gartner predicts that more than 30 will no longer be economic to operate by 2020. If cooling abilities are not in place, your IT infrastructure will fail to operate and will negatively affect your business.
At the heart of running seamless artificial intelligence software is the user experience (UX). Direct-to-chip liquid cooling is used by some solutions system, while some use water to cool the air with a heat exchanger. No matter the procedure, liquid cooling has significant benefits over fan cooling–in certain cases reducing electricity usage by 20% (from 1.5-2.0 PUE to below 1.1).
While liquid cooling is effective, it does increase water intake. For data centers which use this methodology, water usage may be lower than its liquid cooled cousin. It’s critical that colo providers address the impact by relying on water for cooling instead of water that is potable, which makes them both green and AI-ready. This permits the customer to protect their investment and the environment.
Easy User Interface
At the heart of running seamless artificial intelligence applications is the user experience (UX).
If your colo spouse isn’t assuring a minimum of five nines (99.999percent ) of bandwidth –that is less than six minutes per year of downtimethen you may not have a highly reliable partner. Reliability is essential for any business. In 2014, Gartner calculated in fact that companies could lose well over $300K on average in an hour downtime–a figure that has only increased over the previous five years.
Exceptional User Interface
Clients should expect from their colocation provider excellent service and undisrupted data transfer in a safe environment, especially when talking to AI software. Choosing the right data centre provider is a strategic decision that’s so critical to achieving your business goals.