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Multithreaded File I/O


What This All Means

Overall, the results show that multithreaded file I/O can both improve or decrease performance significantly. Keep in mind that an application typically does not only read data, but also processes the data read in a more ore less CPU-intensive way. This leads to different results for every application and even tasks within a application. This also may or may not be the case for writing data. Furthermore, there are very different ways in how and when files will be read or written, as well as different hardware and software configurations that a application will meet. There is no general advice software developers can follow. For example, in one application I measured clearly that using multiple threads per sequential read file increased performance significantly in the 64-bit version. But with the 32-bit version more threads decreased performance on the same machine, the same operating system (Windows XP x64) and the same source code. In another case, where an application opened and appended thousands of files, the best solution was to create 8 threads that did nothing but close files (on a average dual-core machine).

The bottom line is:

  • Make multithreading configurable! The number of threads used in a program should always be configurable from 0 (no additional threads at all) to an arbitrary number. This not only allows a customization for optimal performance, but it also proves to be a good debugging tool and sometimes a lifesaver when unknown race conditions occur on client systems. I remember more than one situation where customers were able to overcome fatal bugs by switching off multithreading. This of course does not only apply to multithreaded file I/O.

Consider the following pseudocode:


int CMyThreadManger::AddThread(CThreadObj theTask)

{
	if(mUsedThreadCount >= gConfiguration.MaxThreadCount())
		return theTask.Execute(); // execute task in main thread
	// add task to thread pool and start the thread
	...
}

Such a mechanism is not very complicated (though a little bit more work will probably be needed than shown here), but it sometimes is very effective. It also may be used with prebuilt threading libraries such as OpenMP or Intel's Threaded Building Blocks. Considering the measurements shown here, its a good idea to include more than one configurable thread count (for example, one for file I/O and one for core CPU tasks). The default might probably be 0 for file I/O and <number of cores found> for CPU tasks. But all multithreading should be detachable. A more sophisticated approach might even include some code to test multithreaded performance and set the number of threads used automatically, may be even individually for different tasks.

Conclusion

So far multithreaded file I/O is a under-researched field. Although its simple to measure, there is not much common knowledge about it. The measurements I present here show that multithreading can improve performance of file access directly, as well as indirectly by utilizing available cores to process the data read. In general, however, there are no rules of thumb. In this article, I've tried to bring a few "hard" numbers into this area, although I think that more measurements and theoretical analysis is needed to enable applications, that perform better on I/O.


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