What to measure and how?
Optimizations almost always add complexity to your code. High-level optimizations, such as choosing algorithms and data structures, can make the intention of the code clearer, but for the most part, optimizations will make the code harder to read and maintain. We therefore want to be absolutely sure that the optimizations we add have an actual impact on what we are trying to achieve in terms of performance. Do we really need to make the code faster? In what way? Does the code really use too much memory? To understand what optimizations are possible, we need to have a good understanding of the requirements, such as latency, throughput, and memory usage.
Optimizing code is fun, but it's also very easy to get lost without any measurable gains. We will start this section with a suggested workflow to follow when tuning your code:
- Define a goal: It's easier to know how to optimize and when to stop optimizing if you have a well-defined...
