I have a pretty good experience in performance and tuning in Oracle database, PL/SQL and SQL. I can say that, by far, the significant gain in execution time lies in how the software is designed. The same steps that I’ve used, we are going to use in the course.
First, do not touch the code without knowing how bad it is. Benchmarking is a must. Before, during and after, these metrics will guide our work and justify hours of analysis and development. It must be done right like a methodic scientist collecting vital data and not rushing. The more depth of info you get, the easiest will be the next steps.
Second, target the right piece of the software. Don’t waste time analyzing tasks that perform well. Instead, aim the ones that take more time, consume more CPU or memory.
Third, experiment changes and compare the execution time with the first step. It will guide us like a trial and test.
Lastly, implement the solution and compare the results of the first step.
We can use simple tools to collect data, for example, using a bash script or the time binary. There are commercial tools out there that collect much more data. Sometimes, too much data is overwhelming. Try to keep it simple at first and get more if needed.
So, we find the bad guy. Now what? Try to use a completely different approach. I like the sound volume example explained by our professor. Changing the music’s volume is not as trivial as I thought. Digital audio takes the wave sound and translate it as tiny dots equally spaced throughout the wave. This process is called sampling. The Y coordinate is the position of the number in the list, and the number represents the X. Then, we end up with a massive list of values—all of them at the volume 1.000 (the maximum). Our volume ranges from 0.000 to 1.000. If we need to keep it down not to disturb the neighbours, we need to multiply every number by the volume factor. Easy right? There is no other way?
I caught myself amazed that our professor listed FOUR ways to do it. The other one is the lookup table. Using a 16bit sampling, we can get only 65,536 values. What if we create a table with the volume, the original value and the calculated one? In this case, instead of doing math, we simply query the value. This approach takes more memory, though.
The third method will do the math, but it will do in binary and using 32bits. This will avoid the float-point conversion used in the first method.
The fourth is called fixed-point math. It will use SIMD instructions and do the math in parallel. By the way, parallelism is a valid tool to deal with performance issues and is relatively easy to implement.
To conclude, being creative and think out-of-the-box is an excellent skill for tuning applications. Also, knowing in-depth, the business and the program tend to produce better results. I like the feeling of being the one that defeated the bad guy that slows down our lovely software. Don't you?
See you.
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