Performant is an unofficial adjective used in computer science to indicate a program‘s ability to perform acceptably. It’s sometimes used to indicate a program runs efficiently, but traditionally it means the program meets the standard of good enough. Not all in the computing industry like this word, claiming that it isn’t legitimate or should not be used, but it has been adopted heavily in computer science nonetheless.
In many computer systems, an acceptably performant program allows administrators or automation software to deal with other issues or optimization processes. But although performant suggests that a computer program or application runs sufficiently for common use, this will not always be enough. For example, in cloud computing, workload and application management should be optimized for exceptional data transmission, analysis, and protection. A performant program suggests that it runs successfully; however, it may not meet the current standard for highly optimized virtual data management or cloud computing.
Though the terms are frequently used in the same conversation, performant and high performance computing are not quite the same. While performant refers to a system that’s running sufficiently, high performance computing focuses on exceptional computing performance: developers improve and streamline coding processes to save computing energy. Computing performance includes the speed of the computing unit; the memory, which affects data storage and management; and the transfer of data between memory and computing resources.
In high performance computing for Python, for example, programmers optimize Python coding processes to improve the program’s efficiency. Though the program may be performing well enough, removing extraneous steps or shortening a process means that the data can move more lightly and use less energy. Programmers can rewrite code to make a program more efficient. While a performant program does not work to optimize its processes, high performance computing does.