I am currently researching the usability of Unreal Engine for a computational intensive project and Google have not been terribly helpful.
I need to do some heavy computation, in the background of the game loop, for the project, which is currently implemented using OpenMP. A fluid simulation.
Unreal Engine on windows compiles and builds using visual studio and should as such have support for what the visual studio compiler has, but it is unclear to me if you can make UE compile with the proper settings for OpenMP.
Alternatively, I could easily make this work with Intels threading building blocks TBB, which is apparently already used in UE... though perhaps only the memory allocator part?
In general I guess my question is what support there is for cross platform heavily parallelized computation with UE. If you need to do a large number of identical computations running on all available cores, how do you do that in UE?
I am not interested in manually creating some number of threads, run them on blocks code, wait for completion by joining and then move on. I would much prefer a parallel_for loop for my purpose.
Further more, I wonder how easy it is to use other frameworks such as CUDA or OpenCL from within a UE "script".
I come from Unity where I made c# wrappers around native dlls, written in c++, for high performance, but I am getting a bit tired of this wrapping native in c#, so I would much prefer a c++ based engine... but if that itself is limited in what I can do in my c++ code, then it is not much help... I assume it can all work, when I learn how, but I am a bit confused by not being able to find any info about any of the above questions. Anything with the word "parallel" in it generally lead to blueprints.
There's a ParallelFor() in UE, defined here: "Engine\Source\Runtime\Core\Public\Async\ParallelFor.h"
Signature is void ParallelFor(int32 Num, TFunctionRef<void(int32)> Body, bool bForceSingleThread = false)
Example use can be found easily in the source codes.
Related
What's this about?
We have a C++ application dealing with image processing and computer vision on videos using OpenCV, we're going to rewrite it from scratch and need some help deciding what technologies to use. More specifically, I need help on how to choose the technology I'd use.
About the app
The app's functionality is divided in modules that are called in an order defined by a configuration XML file and can also be changed in runtime, but not in realtime (i.e. the application doesn't need to close, but the processing will start from scratch). These modules share data in a central datapool.
Why are we starting from scratch?
This application wasn't planned to be as dynamic as it currently strives to be, so it's grown to be a collection of buggy patches, macros and workarounds; it's now full of memory leaks, unnecessary QT dependencies, slow conversions between QT and OpenCV image formats and compilation and testing times have grown too much.
Language choice
The original code used C++, just because the guy who originally started the project only knew C++. This may be a good choice, because we need it to be as fast as possible, but there may be better choices to account for the dynamic nature of the application.
We're limited by the languages supported by OpenCV (C++, Java and Python mainly; although I've read there is also support for Ruby, Ch, C# and any JVM language)
What is needed
Speed: We're aiming for realtime tracking. This may rule out Python and Ruby.
Class Instantiation by name: Although our C++ macros and class registration system work, a language designed to be dynamic that has it's own runtime would be nice. Maybe Objective-C++, or Java.
What would be ideal
Module/Plugin/Extension/Component Framework: Why reinvent the wheel, using a good framework for this would let us focus on what's special about our app. There are many options here. Objective-C has it's NSBundles; C++ has libraries like Boost.Extension, Pluma, DynObj, FxEngine, etc; C has C-Pluff; I'd even say there are too many options.
Runtime class loading and reloading: From a developing point of view, it would be interesting to be able to compile and reload just one module. I've seen this done in via code injection in Objective-C and using Java's reflection.
What am I missing?
I have too many interesting options!
Here's where I need help, based on your experiences in modular app development, with this constraints, what kind of language/framework feature should I be looking for?
What question should I make myself about this project that would let me narrow my search?
Edit
I hadn't noticed that OpenCV had GPU bindings only for C++, so I'm stuck with it.
Now that the language is fixed, the search has narrowed a lot. I could use Objective-C++ to get the dynamism needed (Obj-C runtime + NSBundle from Cocoa/GnuStep/Cocotron), which sounds complicated; or C++ with a framework.
So I'll now narrow my question to:
Is using NSBundle in a crossplatform way with Objective-C++ easier than it sounds?
What C++ framework will provide me with hot-swappable modules?
The main reason for swapping modules in runtime is to be able to change code in a fast way, would Runtime-Compiled C++ be a better solution?
Meta: I did my research on how to ask a question like this, I hope it's acceptable.
"What question should I make myself about this project that would let me narrow my search?"
if you need gpu support(cuda/ocl), your only choice is c++.
you can safely discard C, as it won't be supported in the near future
have no fear of python, even if you need direct pixel access, that's all numpy arrays (running c-code again)
i'd be a bit sceptical of ruby, c# ch and the like, since those bindings are community based, and might not be up to date / maintained properly, while the java & python bindings are machine - generated from the c++ api, and are part of the official distribution.
If you're looking for portability and have large memory for disposal then you can go with Java.
The performance hit between C++ and Java is not that bad. For conversion between Mat and other image format I'm still not sure, coz it needs deep copy to perform that, so if your code can display the image in openCV native format then you can fasten the application
pro :
You can stop worrying about memory leak
The project is much more portable compared to C/C++(this can be wrong if you can avoid using primitive datatypes which size is non consistent and for example always use int*_t in C)
cons:
slower than C/C++
more memory and CPU clock needed
http://www.ibm.com/developerworks/java/library/j-jtp09275/index.html
In my previous question I've asked, I touched the parallel_for subject from ppl.h provided by Microsoft.
But shortly after I've realized that by using it one makes his application unportable (if I'm right it is specific to Microsoft (the ppl.h header)).
In my opinion this breaks very important aspect of programming in C++ - portability, and I'm just not prepare to do it.
So my questions are:
1. Am I right in saying that using parallel_for from ppl makes your code unportable (by unportable I mean that it cannot be compiled by other compiler than the one from MS)
2. Am I right in saying that if on later stage I want to provide UI (done in Qt) for the application I'm working on at the momment, using parallel_for in my code will be an obstruction which would mean that either I'll replace parallel_for with some other (portable) alternative or I won't be able to do UI in Qt and core in VS?
3. What are the (portable) alternatives to ppl?
You may want to consider Intel's Thread Building Blocks. Unlike OpenMP, TBB actually uses C++, rather than simply compiling under a C++ compiler (ie: being a C library that can compile as C++). It has many of the things you see in PPL, but it is cross-platform.
There is also Boost.Thread, which is C++ (though not quite as direct as TBB is), and it is cross-platform.
The people working on the Casablanca project have been making a portable version of PPL, called PPLX. It's licensed under an Apache 2.0 license.
They previously have said they are working closely together with the PPL team to keep both versions in sync feature and bugfix wise (see last post in this thread).
Whether you use PPL or TBB (or HPX) ... something very similar is going to be standardised. For instance see: http://www.open-std.org/jtc1/sc22/wg21/docs/papers/2015/n4411.pdf
Am I right in saying that using
parallel_for from ppl makes your code
unportable (by unportable I mean that
it cannot be compiled by other
compiler than the one from MS)
Unportable if you switch the platform itself. May be portable on Windows, if you want to use other compilers. But know that PPL is part of Concurrency Runtime, which is placed in MSVCRT100.DLL, and you need to link to this (or statically link, without needing DLL at runtime). I am not sure how this can be done with other compilers/linkers, but I do believe it is doable.
Am I right in saying that if on later
stage I want to provide UI (done in
Qt) for the application I'm working on
at the momment, using parallel_for in
my code will be an obstruction which
would mean that either I'll replace
parallel_for with some other
(portable) alternative or I won't be
able to do UI in Qt and core in VS
You can write your core-framework in using PPL/VC++, and other GUI counterpart in QT/other-compiler. For this just make a DLL which would use PPL, and your GUI application would use the DLL. I do believe you understand what I mean here. This also reduces burden from your head about portability (on Windows).
What are the (portable) alternatives to ppl?
Many, but I prefer using PPL on Windows/VC++. You may consider using Intel's TBB. OpenMP is troublesome, and doesn't give advantages as compared to TBB/ConcRT
I have a C# prototype that is heavily data parallel, and I've had extremely successful order of magnitude speed ups using the Parallel.For construct in .NETv4. Now I need to write the program in native code, and I'm wondering what my options are. I would prefer something somewhat portable across various operating systems and compilers, but if push comes to shove, I can go with something Windows/VC++.
I've looked at OpenMP, which looks interesting, but I have no idea whether this is looked upon as a good solution by other programmers. I'd also love suggestions for other portable libraries I can look at.
If you're happy with the level of parallelism you're getting from Parallel.For, OpenMP is probably a pretty good solution for you -- it does roughly the same kinds of things. There's also work and research being done on parallelized implementations of the algorithms in the standard library. Code that uses the standard algorithms heavily can gain from this with even less work.
Some of this is done using OpenMP, while other is using hand-written code to (attempt to) provide greater benefits. In the long term, we'll probably see more of the latter, but for now, the OpenMP route is probably a bit more practical.
If you're using Parallel.For in .Net 4.0, you should also look at the Parallel Pattern Library in VS2010 for C++; many things are similar and it is library based.
If you need to run on another platform besides Windows the PPL is also implemented in Intel's Thread Building Blocks which has an open source version.
Regarding the other comment on similarities / differences vs. .Net 4.0, the parallel loops in the PPL (parallel_for, parallel_for_each, parallel_invoke) are virtually identical to the .Net 4.0 loops. The task model is slightly different, but should be straightforward.
You should check out Intel's Thread Building Blocks. Visual Studio 2010 also offers a Concurrency Runtime native. The .NET 4.0 libraries and the ConcRT are designed very similarly, if not identically.
if you want something that is versatile, as in portable across various OS and environments, it would be very difficult to not to consider Java. And they are very similar to C# so it be a very easy transition.
Unless you want to pull out your ninja scalpel and wanting to make your code extremely efficient, I would say java over VC++ or C++.
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I'm doing a Windows Application the uses lots of charts. Its practically a dataviewer. I started doing Matlab, because its easier, but I realized it's too slow. I wanted to change to another language. Somebody recommended me Visual C++ or Java. But Im not sure. What language should I use??
In my opinion the speed gain from going to another "faster" language is not as much as refining your algorithm.
The "problem" with MATLAB is that it allows you to do some nasty things, such as resizing your matrix in a tight loop. You should really try to pinpoint your bottlenecks using the following command:
profile on
... run your program
profile off
profile report
This will give you nice information about which function takes how long to execute and which line creates the biggest bottleneck. You can also see how many times a function is called and a M-Lint Code Check Report is included.
These measurements and hints can show you the bottlenecks of your algorithm. if your sure there isn't a way to reduce the callcount/speed of a function using a smarter algorithm. Such as do I really need that big 2d matrix where a smart vector would be large enough, or if I found a artifact, why would I still continue searching for artifacts. You could write the functions you're experiencing the most performance problems with in c/c++ and use it as a function in matlab. You can get a big speedup out of correctly choosing which functions to implement in c/c++. There is an amount of overhead with calling a c/c++ function from MATLAB, or more correctly there is a overhead in c/c++ to get the data from MATLAB, so a function which is called 10000 times will not be the best to implement in c/c++, you'd be better of with the function higher up the callstack.
It depends on what your requirements are.
The advantage of using matlab is that it's strong in numerical calculations. If you don't need that, then there is no advantage to using matlab. In this case, all those languages are okay, and many others (Python, C#, ...) as well. It depends on which language you are most comfortable with.
If you do want the advantages of matlab then:
Try optimizing in matlab. Most optimization techniques are language independent.
There are tools to translate matlab to C automatically. You can then try to compile with all optimizations on. I seriously doubt this will help much, however, especially considering the GUI part.
First and foremost, as other answers have mentioned, you need to profile your code to find out where the bottleneck is. I would check out Doug Hull's blog at The MathWorks, specifically this entry about using the profiler. This will help you find out where all the work is being done in your code.
If the source of the slowdown is associated with data processing, there may be a number of ways to speed things up (vectorizing, writing a mex file, etc.).
If the source of the slowdown is your GUI, this may be even easier to solve. There are a number of blog posts, both from Doug and other MathWorkers, which I've seen that deal with GUI design. There have also been a few questions on SO dealing with it (here's one). If you're dealing with displaying very large data sets, this submission from Jiro Doke on The MathWorks File Exchange may help speed things up.
It's hard to give you more specific advice since I don't know how you are designing your GUI, but if that turns out to be the bottleneck in displaying your data there are many resources to turn to for improving its speed before you go through the hassle of switching to a whole other language.
Don't forget that you can create functions in C++ that can be called from Matlab. And TADA, you have access to both environments !
I would use C#. It is easier than C++ and integrates well with the Windows platform. Just find a free graphing library for it and you're good to go.
There are plenty of other options depending on your preference of language. Eg. Qt with Python or C++.
As far as I know, the most common methodology is to first do the proof of concept or just the main algorithm on Matlab, because of its ease of use and convenience for math calculations, and after that to translate it to a "real" programming language in order to improve the performance. Usually C or C++ act as the "real" language, but in your case, aiming to do a Windows application, perhaps C# will be the best option.
I found that GUI programming in MATLAB can get really nasty if your application gets more complex. BTW MATLAB can also be called from Java easily (and vice versa, current versions basically provide an interactive Java console).
Just as a side note, if you still need the math power of Matlab, you may want to check out Scilab. It's open-source and free, and it has examples of how it can be integrated with other C# or C++. I have created projects on which Scilab was running in the background to perform all the data math operations; and displaying them with C#'s ZedGraph library. Worked like magic!
I suggest you using Java and the JFreeChart (http://www.jfree.org/jfreechart/) library. I found very easy (and fast) developing applications with a lot of charts of different typologies. If you don't need particularly fast performances, you can use Java. I suppose that there are similar libraries for C#, but I'm not sure.
An alternative to Matlab and Scilab is another free software: Octave.
I don't know about Scilab, but Octave syntax is nearly the same as matlab so you can import code with minimal effort.
If you need fancy toolboxes though, Scilab and Octave might let you down, so check this.
You can execute Octave functions in a C++ program:
http://en.wikipedia.org/wiki/GNU_Octave
I do not think that you can call your own m-files functions from your C++ program though. In the past, the Matlab compiler would let users run matlab programs without installing Matlab, but not without installing a huge library (250 MB if I remember correctly). Nevermind if your Matlab program took 20 kB, you had to distribute the huge library.
Please someone edit/comment on the situation today!
It has been a while since I used the GUI "ability" of Matlab, but back then (2005) I found it awful. Ugly, hard to use, very hard to maintain, dependent on user settings of windows parameters.
Please comment or edit on that too, they may have made progress!
If they have not, I believe that Matlab is NOT the way to go for a program that you want to deliver to anyone.
If you can use Visual Studio for doing your GUI, do that. I second the earlier opinions: go with what you're comfortable with.
If you need the Matlab functions, go with what you're comfortable with, that supports Matlab libraries.
First of all Visual C++ is not a language is an IDE for developing applications.
Second... Which languages do you know? You can have several options. Take a look to:
C++ + Qt (Mine preferred option, powerful and easy to understand)
C# + .NET or WPF
Java
If you can tell more information we could find a language that matches your needs.
I'm a game's developer and am currently in the processing of writing a cross-platform, multi-threaded engine for our company. Arguably, one of the most powerful tools in a game engine is its scripting system, hence I'm on the hunt for a new scripting language to integrate into our engine (currently using a relatively basic in-house engine).
Key features for the desired scripting system (in order of importance) are:
Performance - MUST be fast to call & update scripts
Cross platform - Needs to be relatively easy to port to multiple platforms (don't mind a bit of work, but should only take a few days to port to each platform)
Offline compilation - Being able to pre-parse the script code offline is almost essential (helps with file sizes and load times)
Ability to integrate well with c++ - Should be able to support OO code within the language, and integrate this functionality with c++
Multi-threaded - not required, but desired. Would be best to be able to run separate instances of it on multiple threads that don't interfere with each other (i.e. no globals within the underlying code that need to be altered while running). Critical Section and Mutex based solutions need not apply.
I've so far had experience integrating/using Lua, Squirrel (OO language, based on Lua) and have written an ActionScript 2 virtual machine.
So, what scripting system do you recommend that fits the above criteria? (And if possible, could you also post or link to any comparisons to other scripting languages that you may have)
Thanks,
Grant
Lua has the advantage of being time-tested by a number of big-name video game developers and a good base of knowledgeable developers thanks to Blizzard-Activision's adoption of it as the primary platform for developing World of Warcraft add-ins.
Lua is a very good match for your needs. I'll take them in the same order.
Lua is one of the fastest scripting languages. It's fast to compile and fast to run.
Lua compiles on any platform with an ANSI C compiler, which afaik includes all gaming platforms.
Lua can be pre-compiled, but as a very dynamic languages most errors are only detectable at runtime. Also precompiled code (as bytecode) is often larger in terms of size than source code.
There are many Lua/C++ binding tools.
It doesn't support multi-threading (you cannot access a single instance of the interpreter from multiple threads), but you can have several instances of the interpreter, one per thread, or even one per game object.
Lua have been used in video-game industry for years. Lightweight and efficient.
That being said, ChaiScript and Falcon are good candidates matching your needs and with higher level language than Lua but with less history and community support.
Lua
Boost Python
SWIG
We've had good luck with Squirrel so far. Lua is so popular it's on its way to becoming a standard.
I recommend you worry more about memory than speed. Most scripting languages are "fast enough" and if they get slow you can always push some of that functionality back down into C++. Many of them burn through lots of memory, though, and on a console memory is an even more scarce resource than CPU time. Unbounded memory consumption will crash you eventually, and if you have to allocate 4MB just for the interpreter, that's like having to throw 30 textures out the window to make room.
Lua, and then LuaJIT for extra blaziness!
just don't expect too much from automatic C++ binding libraries, most are slow and restrictive. better do your own binding for your own objects.
as for concurrency, either LuaLanes, or roll your own. if your C++ program is already multithreaded, just call separate LuaStates from each thread, and use your own C++ shared structures as communications channels if needed.
as you might already know, the most often repeated answer in Lua is 'roll your own', and it's often the best advice! except when it's about bindings to common C/C++ libraries, in that case it's quite probable there's already one.
If you haven't looked at it yet I would suggest you check out Angelscript.
I have successfully used it in a cross platform environment (Windows and Linux with only a recompile) and it is designed to integrate well with C++ (both objects and code).
It is lightweight and supports multi-threading (in the sense that the question was asked), performs well and compiles to byte code which could be done in advance.
Start with Python.
If you can prove that you need more speed, then look at Stackless Python. That's what EVE Online uses for their game.
JavaScript may be a reasonable option, because of the mountains of effort that have gone into optimizing the various implementations for use in web-browsers.
These come to mind:
Lua
Python with boost::python
MzScheme or Guile
Ruby with SWIG