What is parallel programming? It is a common process that is used in every facet of computer programming in this country, and after its rebirth in late 2015, it has fast overtaken concurrent programming as the first choice for any programmer who has several architectures that need to be processed at the same time. Here is a quick primer, complete with advantages and disadvantages of the process as well as a rundown of where it is used, for students and professionals who are just coming to understanding what parallel computing is.

What is Parallel Programming?

In very simple terms, it is the use of multiple resources, in this case, processors, to solve a problem. This type of programming takes a problem, breaks it down into a series of smaller steps, delivers instructions, and processors execute the solutions at the same time. It is also a form of programming that offers the same results as concurrent programming but in less time and with more efficiency. Many computers, such as laptops and personal desktops, use this programming in their hardware to ensure that tasks are quickly completed in the background.


There are two major advantages to using this programming over concurrent programming. One is that all processes are sped up when using parallel structures, increasing both the efficiency and resources used in order to achieve quick results. Another benefit is that parallel computing is more cost efficient than concurrent programming simply because it takes less time to get the same results. This is incredibly important, as parallel processes are necessary for accumulating massive amounts of data into data sets that can be easy to process or for solving complicated problems.


There are several disadvantages to parallel processing. The first is that it can be difficult to learn; programming that targets parallel architectures can be overwhelming at first, so it does take time to fully understand. Additional, code tweaking is not straightforward and must be modified for different target architectures to properly improve performance. It’s also hard to estimate consistent results because communication of results can be problematic for certain architectures. Finally, power consumption is a problem for those instituting a multitude of processors for various architectures; a variety of cooling technologies will be required in order cool the parallel clusters.

Where is it Used?

This type of programming can be used for everything from science and engineering to retail and research. It’s most common use from a societal perspective is in web search engines, applications, and multimedia technologies. Nearly every field in America uses this programming in some aspect, whether for research and development or for selling their wares on the web, making it an important part of computer science.

Parallel computing is the future of programming and is already paving the way to solving problems that concurrent programming consistently runs into. Although it has its advantages and disadvantages, it is one of the most consistent programming processes in use today. Now that there is an answer to the question of what is parallel programming, the next question should be, how can a professional use this type of programming in their field?