In this post I want to show you how you can improve the performance of your application by using datastructures and approaches which make use of non blocking parallelism.
Recently I digged into the API's of OpenCV, which is a great image processing library. I wrote several blog posts about it, and this is sort of a follow up on these posts. However, this time I want to improve the project by introducing Scala Futures into the codebase. (Why? because its there!)
Scala Futures are an integral part of Scala 2.10 and are explained here in more detail. I want to show you how the readability of applications can benefit - as well as their performance. The latter will be more important for your managers, but using Futures combined with Scala's for comprehension have their own aesthetic appeal.
If you compare the isight-java project from this and this commit, you'll find that not very much changed for the end user, in fact it is more or less the same end user experience. However the version I'm describing here makes heavy use of the 'Futures' concept.
In short, the application is based on a filtering pipeline, starting on the grabbed image several different algorithms are applied to it, passing and mutating the Mat datastructure from one operation to the other.
Using Scala Futures and for comprehension, this translates to a code like this:
You'll recognize the pipeline structure in the code above. The neat thing is that you'll get error handling for free using the recover combinator. If you compare the code above with the one of the previous post, you'll notice that it looks much clearer and the intention of the code is really apparent. (even though IMO the last version wasn't too bad either :))
Of course, the image processing functions needed some adaptions to return futures:
You can see that using futures is quite easy and feels somewhat natural when you combine it with the for comprehensions. For a more detailed discussion on what happens under the covers, please read the article on futures on scala-lang.org.
Anyway, if you go that road with Scala Futures, with small tweaks to the source code (at least on the surface) you'll get a parallelized version which, when used in conjunction with the for comprehension, looks like a sequential code.
If your result consists of several, independent sub problems which you combine in a final step you'll get the best results when parallelizing your app.
Even if in this application this is not the case, I've nevertheless noticed a considerable improvement in responsiveness and speed (whatever reasons this had: either wishful thinking or just bad implementation beforehand ;-) ) as well as readability of the code.
It could well be that the guys over at the scalaFX camp have done something to use concurrency as convenient as the scala team did for scala futures - if not: this would be a great idea.
Check out the full source code for this blog post here.
In the meantime, I wrote a new post about using your webcam with JavaCV, maybe this interests you as well?
Recently I digged into the API's of OpenCV, which is a great image processing library. I wrote several blog posts about it, and this is sort of a follow up on these posts. However, this time I want to improve the project by introducing Scala Futures into the codebase. (Why? because its there!)
Scala Futures are an integral part of Scala 2.10 and are explained here in more detail. I want to show you how the readability of applications can benefit - as well as their performance. The latter will be more important for your managers, but using Futures combined with Scala's for comprehension have their own aesthetic appeal.
If you compare the isight-java project from this and this commit, you'll find that not very much changed for the end user, in fact it is more or less the same end user experience. However the version I'm describing here makes heavy use of the 'Futures' concept.
In short, the application is based on a filtering pipeline, starting on the grabbed image several different algorithms are applied to it, passing and mutating the Mat datastructure from one operation to the other.
Using Scala Futures and for comprehension, this translates to a code like this:
You'll recognize the pipeline structure in the code above. The neat thing is that you'll get error handling for free using the recover combinator. If you compare the code above with the one of the previous post, you'll notice that it looks much clearer and the intention of the code is really apparent. (even though IMO the last version wasn't too bad either :))
Of course, the image processing functions needed some adaptions to return futures:
Disclaimer: I've mixed up some concepts of the Scala libraries and JavaFX parallelism (I'm using JavaFX's Service and Task concepts along with Scala Futures) - some may argue that this is not necessary or even dangerous. Quoting this guy here: TMTOWTDI. Be aware that mixing different approaches of parallelism can lead to confusion of the poor guy inheriting your code, or may result in unwanted effects (?). One side effect I noted when using Scala Futures was the necessity to use the Platform.runLater( ... ) trick to make sure the image service runs on the gui thread.
Anyway, if you go that road with Scala Futures, with small tweaks to the source code (at least on the surface) you'll get a parallelized version which, when used in conjunction with the for comprehension, looks like a sequential code.
If your result consists of several, independent sub problems which you combine in a final step you'll get the best results when parallelizing your app.
Even if in this application this is not the case, I've nevertheless noticed a considerable improvement in responsiveness and speed (whatever reasons this had: either wishful thinking or just bad implementation beforehand ;-) ) as well as readability of the code.
It could well be that the guys over at the scalaFX camp have done something to use concurrency as convenient as the scala team did for scala futures - if not: this would be a great idea.
 |
| me blurred beyond recognition |
In the meantime, I wrote a new post about using your webcam with JavaCV, maybe this interests you as well?
No comments:
Post a Comment