Why is performance and multitasking important?
We’re all impatient these days, we want things fast and we want them all at once, especially when it comes to technology. In 2010, Intel even had an ad campaign about how watching the hourglass whilst waiting for something to load can lead to stress! They called it “Hourglass Syndrome” and I’m sure we can all relate.
But why is it that we hear AI/ML workloads in particular need more performance? Is it because we’re all so impatient and want the intelligent result faster? Is it because there is so much to process and the added compute power really is required? Well it turns out, it’s a combination of both.
So let’s take a look at two reasons AI/ML workloads require such a large amount of resources – Training and Inference. Today, I’m going to break down these two concepts in order to highlight the demanding requirements of running machine learning workloads….