Opportunities for parallelism are parts of the code (normally loops) that are good candidates to run faster when parallelized using a specific paradigm. These paradigms include CPU multi-threading and vectorization as well as offloading to accelerator devices such as GPUs.
Codee classifies loops into patterns in order to decide which qualify as good parallelization opportunities for the different supported paradigms. Software design patterns are reusable descriptions or templates for how to solve recurring problems that commonly appear during programming. They have been used for decades to speed up software development while ensuring that best-practice solutions are implemented. This follows the principle of divide and conquer where some subproblems are solved through patterns.
Using patterns facilitates reasoning and opens the door for advanced tooling. Using common categories helps developers find the solution to a problem quicker. Tools can also benefit since some solutions may be automatized at least up to a certain point, such as providing a template for the implementation.
Parallel code also exhibits recurring patterns. For instance, it is very common to perform a mathematical operation over each element of an array. Another significant example is computing a single scalar value by computing all the elements in an array. Memory accesses can also be classified into different patterns. By analyzing the properties of these recurring computation patterns. Solutions to efficiently implement them in parallel can be developed.