Intel® Threading Building Blocks

Performance issue of scalable_realloc() vs. glibc realloc()


I have an application that initially allocates a 4MB block of memory and linearly grows this block using 4MB steps. glibc's realloc() handles this pattern quite well. Linking against tbbmalloc_proxy (or replacing glibc realloc() with scalable_realloc()) degrades performance very badly.

Execution Time variations


I am a naive user. Recently I have been studying regarding Threading Building Blocks. I tried executing the Fibonacci program and the results were obtained in milliseconds. When I execute the same program in Java using multithreading, I got the result in nano seconds. Can anyone tell me the reason behind such a huge variation?




Starting a pipeline with thread_bound_filter


I am trying to parallelize an algorithm that accepts a callback and looks like this:

class Object;

class MyCallback
virtual void NotifyAboutCompletion (Object* o) = 0;


void Foo (Object* o, size_t n, MyCallback* c)
   for (size_t i = 0; i < n; ++i) {
     DoSomeHeavyWork (o);
     c->NotifyAboutCompletion (o);


TBB add-in fail to load in Visual Studio 2010

I downloaded TBB add-in and installed it in Visual Studio 2010 as guided in the README file. But when I start Visual Studio, there is a message: The Add-in 'Intel (R) Threading Building Blocks Intergration' failed to load or caused an exception. Would you like to remove this add-in? ... Error number 80131515". So I can not use the TBB add-in.

Some one can help me to solve this problem?

TBB Android for loop accessing storage of same class vectors <std::float>

Hello everyone,

Me and a friend try to make and android app. Unfortunately the performance in a 3 staged for-loop constelation is very low. However, the forloops are mathematically not linked i.e. the i-th step in the outer for loop does not need to know what the i+1-th step's results are. However, in  this loop the same global class variable will be used which is a long 50k long vector of 3D points.

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