GCCXML uses GCC as a front-end to parse C or C++ files. It then generates XML files for the interface, that is, it generates tags for the types and prototypes it parses. Then, pygccxml is a wrapper over it which parses the XML file to generate a Python object with every information one may need.

So I will quicly show here how it is possible to generate serialization/deserialization and then how to wrap functions with my custom serialization functions.

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I’ve played a little bit with Intel Parallel Studio. Let’s say it has been a pleasant trip out in the wildness of multithreaded applications.

Intel Parallel Studio is a set of tools geared toward multithreaded applications. It consists of three Visual Studio plugins (so you need a fully-fledged Visual Studio, not an Express edition):

  • Parallel Inspector for memory analysis
  • Parallel Amplifier for thread behavior and concurrency
  • Parallel Composer for parallel debugging

This is an update of the review I’ve done for the beta version. Since this first review, I’ve tried the official first version.

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There is no official C++ standard, unlike several languages (Java, Python, …) where there are referentials for code and design style, good practices, … It didn’t exist until this book where two world-renowned C++ authors set the basis for your every day development.

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I bought this book as soon as it was published, and I sold it soon after. Suffice to say I had a very mitigated impression after reading it. There are good things in it, but also some very bad stuff. It doesn’t describe how to write your ultimate game engine, but the author’s game engine. What about some modesty?

Let’s start with the bad stuff.

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Profiling with Valgrind/Callgrind

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Profiling comes in three different flaviors. The first is emulation, where a processor behavior is emulated, the second is sampling, where at regular intervals, the profiler samples the status of a program, and fianlly instrulentation, where the profiler gets information when a subroutine is called and when it returns. As with the Heisenberg uncertainty, profiling changes the exact behavior of your program. This is something you have to remember when analyzing a profile.

Valgrind is an Open Source emulation profiler. It is freely available on standard Linux platforms. As it is an emulation, it is far slower than the actual program. This means that the I/O are underestimated. The advantage is that you can have every detail on the memory behavior (cache misses for instance). Valgrind does not emulate all processors, but you can tweak it to approach your own one.

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Some months ago, I had a TotalView tutorial, thanks to my job. Now, I’ve actually used it to debug one of my parallel applications and I would like to share my experience with fantastic tool.
First TotalView is not only a parallel debugger available on several Linux and Unix platforms. It also is a memory checker (MemoryScape and the TotalView plugin) as well as a reverse debugger, that is, you can roll back the execution of a program, even after it crashed (where it would be useless with a standard debugger like GDB).

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This is the question I asked myself recently. If you write a scientific code in Fortran, you can expect a huge performance boost compared to the same program in C or C++. Well, unless you use some compiler extensions, in which case you get the same performance, or better.
Let’s try this on a 3D propagation sample, with a 8-points stencil.

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I chose Eclipse as my new Linux IDE, instead of Konqueror + KWrite. The purpose was to be able to launch a SCons build from the IDE, get the errors in a panel and double-clicking on one of them would direct me to the location of the error.

So Eclipse seemed to fit my needs:

  • Plug-ins to add the support of various languages
  • Support of different construction tools
  • Support from the main C/C++/Fortran compiler developers (GNU, Intel, IBM, …)

So I will know show you two ways of enabling SCons support for Eclipse.

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