What are some of the challenges and best practices of parallelizing legacy or sequential code?

1 Why parallelize legacy code?

Legacy code is code that has been written for a previous or outdated system, platform, or architecture. It may not be optimized for parallel computing, or it may rely on assumptions or features that are no longer valid or supported. However, legacy code may also contain valuable functionality, logic, or data that you want to reuse or enhance. Parallelizing legacy code can help you improve its performance, scalability, portability, or compatibility with modern hardware and software. It can also enable you to tackle new problems or applications that require parallel processing.

2 How to identify parallelism opportunities?

Before you start parallelizing your legacy code, you need to identify where and how you can introduce parallelism. This involves analyzing your code to find out its structure, dependencies, data flow, and computational patterns. You can use tools such as profilers, analyzers, or compilers to help you with this task. You should look for parts of your code that are independent, repetitive, or intensive, and that can be divided into smaller or simpler tasks that can run concurrently or in parallel. You should also consider the trade-offs between parallelism and overhead, such as communication, synchronization, or memory costs.

3 How to choose a parallel programming model?

A parallel programming model is a set of concepts, rules, and constructs that define how parallelism is expressed, managed, and executed in your code. There are many parallel programming models available, such as shared memory, distributed memory, message passing, or task-based models. Each model has its own advantages, disadvantages, and suitability for different types of problems and architectures. You should choose a parallel programming model that matches your parallelism opportunities, your legacy code characteristics, and your target platform capabilities. You should also consider the learning curve, the portability, and the support of the model.

4 How to refactor your legacy code?

Refactoring is the process of improving the quality, readability, or maintainability of your code without changing its functionality. Refactoring your legacy code can help you prepare it for parallelization, by removing unnecessary or redundant code, simplifying complex or nested code, modularizing or decomposing your code into functions or classes, or applying design patterns or best practices. Refactoring can also help you identify and eliminate bugs, errors, or vulnerabilities in your code, which can affect the correctness or security of your parallel program.

5 How to parallelize your legacy code?

Parallelizing your legacy code is the process of modifying your code to use the parallel programming model that you have chosen. This may involve adding or changing keywords, directives, annotations, libraries, or frameworks to your code, depending on the model. You should follow the guidelines and documentation of the model to ensure that you use it correctly and efficiently. You should also test and verify your parallel code incrementally, by comparing its output and behavior with your original sequential code. You should also measure and evaluate your parallel code performance, scalability, and efficiency, by using metrics such as speedup, efficiency, or overhead.

6 How to debug your parallel code?

Debugging is the process of finding and fixing errors or defects in your code. Debugging your parallel code can be more challenging than debugging your sequential code, because parallel code can introduce new types of errors or bugs, such as race conditions, deadlocks, livelocks, or non-determinism. You can use tools such as debuggers, monitors, or visualizers to help you with this task. You should also use good practices such as logging, commenting, or documenting your code, using assertions or checks, or applying defensive programming techniques. You should also avoid common pitfalls such as using global variables, assuming sequential order, or ignoring edge cases.