This is sort of a confusing article because it assumes the premise of "you have a fixed hardware profile" and then argues within that context ("Most scientific computing runs on queues. These queues can be months long for the biggest supercomputers".) Of course if you're getting 100% utilization then you'll find better raw pricing (and this article conveniently leaves out staffing costs), but this model misses one of the most powerful parts of cloud providers: autoscaling. Why would you want to waste scientist time by making them wait in a queue when you can just instead autoscale as high as needed? Giving scientists a tight iteration loop will likely be the biggest cost reduction and also the biggest benefit. And if you're doing that on prem then you need to provision for the peak load, which drives your utilization down and makes on prem far less cost effective.