The article is interesting, but IPC is the wrong metric to focus on. Frankly, the only thing we should care about when it comes to performance is time to finish a task. It doesn't matter if it takes more instructions to compute something, as long as it's done faster.
The other metric you can mix with execution time is energy efficiency. That's about it. IPC is not a very good proxy. Fun to look at, but likely to be highly misleading.
The idea here is that it appears that you are limited by the CPU and want to make things faster.
When doing optimized code, the question "should I optimize for memory or for computing?" comes up often. Should I cache results? Should I use a more complex data structure in order to save memory or improve locality?
IPC is a good indicator on how you should tackle the problem. High IPC means you are may be doing too many calculations, while low IPC means that you should look at your memory usage. BTW, most of the time, memory is the problem.
The other metric you can mix with execution time is energy efficiency. That's about it. IPC is not a very good proxy. Fun to look at, but likely to be highly misleading.