How well your Code is Performing in real world environment?

Now a days most of the people without second thought on how the code will perform are copying blindly from stack overflow or some websites in the projects. This makes the code to crash in real environment where they have to go through entire code base for debugging which is a big nightmare for any team.

We never had a second thought like how our code is performing or how we can optimize the code. Now it’s time that everyone should think how we can make sure code perform better in real world with less breakdowns instead of frequent breakdowns.

When I say an optimized code, some think about code restructuring so that number of lines of code is decreased. But the actual thing is Code should be written in such a way that it uses least possible memory, minimizes CPU time, network bandwidth and makes best use of additional cores. The basic requirements optimization methods should comply with, is that an optimized program must have the same output and side effects as its non-optimized version.

Some of the important Code optimization techniques are Dead Code Elimination, Compile Time evaluation, Common sub-expression elimination, Code movement and Strength Reduction.

If manual optimization is being done then one doesn’t just need to know how exactly optimization should be done, but also what part of the program should be optimized. Manual optimization takes a lot of time so we they will concentrate mainly on the critical 10% of the code. Optimizing from the start doesn’t save any time in the end when the code being optimized is replaced by a built-in or third-party function. Instead of going through manual way we can use tools so that tools will suggest which part of the code needs to be optimized so that we can get better performance.

Parallelware Analyzer is one such tool which can increase the performance of your code in many ways from optimizing memory usage to parallelizing your code. Most important thing is Parallelware analyzer provides actionable insights through performance optimization reports that help ensure best practices to speed up the code using Vectorization, Parallelization and offloading to accelerators. In addition, this tool can detect defects due to race conditions and data movement issues, verifies the correctness of parallel code and helps enforce best programming practices. Ultimately, it will help you speed up the performance of your code while increasing code quality and reducing maintenance costs.