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I have a graph of the dependencies of all tasks, and the costs of each task. Now I want to calculate a scheduling for a given amount of CPUs. I've found many papers on scheduling algorithms, optimal schedulers seem to be too expensive for my problem size (around 100 nodes) as it's an NP-hard problem. I'd settle for a heuristic, preferably one that has a bound how close it gets to the optimum. My problem now is: do I really have to code it myself?? This should have been solved many times before, it can be easily applied to project management, maybe there something exists?
If you happen to know a library in python that'd be perfect or the next best thing would be C++, otherwise i'd settle for anything else.
This is a pretty common problem. It also shows up in hardware design.
There has been a lot of work on algorithms to solve it.
If you are going to write something yourself, start by checking out "Hu's Algorithm".
If you just want a solution, these functions are built into architectural synthesis programs.
Look at the Wikipedia pages on high level synthesis and logic synthesis.
There are several professional tools that can handle this, if you can get access to them through school or work.
There are university programs you can often get for free that can also handle this problem.
I'm not up-to-date on what is currently available. An very old one is MIS II from Berkeley. It's scripting language was Tcl, not Python.
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Does anyone have experience programming voice recognition in C++ (Windows and/or Mac) for a limited number of commands aiming for SPEED? Is it realistic at this point to achieve recognition of the command from the first syllable - ie, command is recognized by the time user gets to second syllable at reasonably fast speaking tempo? All commands would be programmed to start with a different syllable, if necessary, a radically different one (like, "oo", "xy", "fay" - only some 30 commands would be required).
Similar questions have been asked, but this is a fast moving field. Would the best idea be to look for open source libraries or to interface with compiled implementations?
I'm working professionally in this field, and I seriously doubt whether it is possible at all. C++ isn't the problem, the question is whether a computer allows it. The error rate on small sound clips is large, it's the Hidden Markov Model that fixes recognition. But in your case you simply can't feed it enough data.
Not that humans can do it either. Speech processing isn't as instant as your brain makes you believe.
You can do this with CMUSphinx with Pocketsphinx decoder.
The partial hypothesis of decoding is avaiable during the recognition process and you can usually get a first syllable as soon as it is uttered. If you give it 0.1s to stabilize (not visible for the user), you will get an accurate results on a command set.
There are even tools build on the top of CMUSphinx specifically designed for realtime control, for example in games, you can check InProTK and their demonstrations.
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I'm studying physics and I know C++ at a basic level. at my study it's sometimes really useful to create a program which can graphicly represent some data or do calculations and then graphicly represent them. I read that, for example, to be able to master the basics of openGL I would need to do a 10 week long course of openGL. But that is too much time.
I'm wondering if there are any libraries available (for windows) which allow me to do some easy stuff like:
-DrawPixel(x,y,color)
-DrawCircle/Line/Shape/Polygon([list of points])/Triangle/Square (+rotation)
-DrawImage(filename,width,height,etc...)
-DrawText()
Is there any library which has this easyness? It would be really cool because if I do something (create a program) and I need to explain my team (who have never programmed) how I have done it (the program / results), this would make it much easier to explain!
I looked at SDL, HGE, OpenFrameworks (somewhat the "closest" yet still far away) and a few other popular libraries but they are all so far away.. why is there no such easy library?
Are there any available which are just not being found with the keywords i search in google?
I would suggest that you take a look at cinder. Try out the Hello Cinder tutorial. I think you will find it supports your needs by providing an abstraction layer above DirectX or OpenGL.
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I'm looking for book titles or papers about how to decompile X86 Disassembly into C/C++ code MANUALLY.
Well , I know about many tools that do the job , but I think doing it manually is more efficient even if it's a slow process.
If you are VERY used to looking at disassembly from a particular compiler, you MAY be able to come up with decent C or C++ code. But it's a TERRIBLY slow process even then. Just taking one small function (say a for-loop, a couple of if-statements and some basic math) and reconstructing it back into source code can take half an hour for me, and I don't think I'm terribly bad at it. Of course, one of the main points is identifying commonly used algorithms, such as linked lists, binary trees, string management, vector management, etc.
Doing it by machine will give you a lot of the work done for you, but even then, it can take days to do even a few hundred lines of orginal C++ code into something that is actually readable.
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I have a pretty new code base written in C++. Already I'm starting to see some bad practices creeping into the project (class file with 1000+ lines of code, functions with a lot of parameters, ...).
I would like to stop on these right away with some automated tools which can hook into the build and check for poor coding practices. What suggestions do you have for such tools? I'm interested in metrics but really more interested in a stylistic sort of lint which would highlight functions with 37 parameters.
I'm sorry I can't help you with respect to style, but a great metrics tool which supports C++ and is free: SourceMonitor.
In particular, you will get good info like Cyclomatic Complexity (which I find of more value for bad programming practice than number of parameters), as well as lines of code, percentage of comments, longest function, etc.
Give it a try -- and it is very fast as well.
As with the others I'm not sure of a tool that will judge style. But CCCC will produce numerous metrics that can help you find the trouble spots. Metrics like cyclomatic complexity will give you quantitative evidence where the problem spots are. The downside is that you will have to incorporate these metrics with a style guide that you adopt or create on your own.
Metrix++ matches this use case and has got several metrics you are probably interested in. Check it here: http://metrixplusplus.sourceforge.net/
Make sure that you always compile with -Wall compiler option and make it practice that no code is to be checked in if warnings persist.
Find a standard style to follow like this one.
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I'm looking for high performance code (needs to run in real-time), preferably open source, but if there is nothing that's free and high-perf, I'll take something well supported and of high quality for a cost.
Any suggestions?
These are the ones I've found so far, in no particular order:
CodeCogs
GSL
Cephes
Boost MathToolkit
Blitz++
TNT
Check the links on mathtools.net. The page for statistics libraries for C++ has links. Another page http://www.thefreecountry.com/sourcecode/mathematics.shtml lists few more.
Have you checked the 'R project'? I think you can call 'R objects' from C/C++.
I'm surprised nobody's mentioned ALGLIB: http://www.alglib.net/
Root has pretty good statistical support. At least as us particle physics types judge these thing. Works in cint interpretation or as a native c++ library.
TNT is for matrix calculations but doesn't have any statistics functionality. (e.g. erf, mean/std/cov etc)
I haven't used Boost Math Toolkit, but skimming through the documentation, it looks like it has the opposite problem, e.g. lots of goodies for scalar calculations, but no support (that I could find) for multivariate situations.
I have used the IT++ library in the past, this library supports ACML and MKL routines trough BLAS and LAPACK. If it are calculations that need to happen fast, there is the possibility of using this library together with HPC, this is an although undocumented feature so some thought will be required.
The focus on this library is however positioned on matrix calculations, but many normal mathematic and statistic functions can be found in this framework thanks to its excellent signal processing support.