Paid Post There’s no doubt that the repurposing of GPU silicon has accelerated the development of artificial intelligence technology over the last decade.
But focusing exclusively on GPUs when building out your own AI infrastructure can leave you with a misleading picture of what your ecosystem should really look like. GPUs are not required for every stage of AI, so if you focus on GPUs only, you will be investing in GPU hardware that you do not necessarily need.
So how do you get the full picture? This infographic from Intel walks you through what a resilient AI deployment looks like. It also shows exactly where Intel’s technology doesn’t just fit in to the AI development and deployment process, but also delivers key optimizations that can supercharge your development.
For example, long before your developers can even think about training their model, they will be thinking about pre-processing data, something best done using Pandas on a CPU. But with Intel’s distribution of the open source Modin framework, this can be accelerated by a factor of 90X, while the use of Optane PMem allows the loading of larger datasets.
And while GPUs are the preferred option for training data, this doesn’t automatically mean Nvidia. In fact, Intel’s Habana Gaudi AI Training Processor delivers 40 percent better price performance than current graphics processors, according to Intel.
At the same time, Intel’s Next Gen Intel Xeon Scalable processors can be used for intermittent training sets during off peak times, such as overnight or weekends. And they deliver 1.5x greater performance across key machine learning workloads.
And ultimately, it is inference that delivers the real world benefit of all that AI investment. And here, Intel Xeon Scalable, with built-in AI acceleration, can deliver 1.7X higher price performance and 3.3X higher performance per watt than Nvidia’s 4X DGX A100 – all without the deployment challenge that comes with implementing GPU tech.
All of this is tied in with Intel’s commitment to Open Source Tooling, right through the preparation, training, and deployment phases.
It is crucial to allow your AI developers to use the tools they want, not the tools you are locked into by your hardware vendor. Intel can help ensure you are using the right hardware tools for the right problem. So, if you want to get the full picture on where GPUs and CPUs sit in the AI battle, download this infographic now.
Sponsored by Intel
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